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Management consultants have crunched the data, conducted the stakeholder analyses and have delivered their verdict. And it is one that the world struggles to see: we are in a crisis.
Across the world, epidemiologists, economists and politicians have been flummoxed by COVID-19. They bicker over testing strategies, worry about protecting frontline service workers and argue about the best way to control crowds. And as they flounder, they prove what we knew all along, that they're not really experts and that the only real experts in this world are management consultants. Unhampered by the actual evidence and the fact that such an event has never happened before, factors that might scare lesser mortals, management consultants have got down to work with alacrity. Quickly repurposing platitudes they've used to help companies lay off staff and make CEOs richer, they've cut through the noise to reveal what's happening and the future shining brightly just around the corner.

While the so-called experts fight COVID-19 on the ground, they miss - and make us miss - the big picture which, thankfully for management consultants, we now have. It is this: the world will be different after COVID-19 and we will need to adjust. These are deep truths - but fortunately, consultants are able to communicate them plainly.

For instance, BCG quickly wrote on their website, "Immediate action is critical, but leaders must also embrace a new agenda - one aimed squarely at what comes next, for business and all of society". Reading it carefully and spending a few minutes to digest its import, one can conclude that they exhort us to focus on both the present and the future simultaneously - but not, please note, definitely not, the past. Bain is equally quick and equally equal in the advice but of course not in the words used to express it. Their website says, "Across industries, companies should act now to protect their employees and customers - and prepare now for the world beyond coronavirus."

But how do companies do this? Well, they can get inspiration from EY-Parthenon: "It is clear that no simple set of prescriptions will suffice to address the post-COVID-19 world. But we have a reasonable degree of confidence that - beyond the immediate fight for liquidity - through the crisis, long-term value is going to become a much brighter "North Star" by which to navigate." Again a few minutes of deep contemplation will reveal that EY-Parthenon suggests that companies should focus on the long-term, which is truly a breakthrough idea for most companies.

To do this, however, firms need resilience, suggests McKinsey's senior leadership and go the extra mile by helpfully defining the term: "Resiliency - the ability to absorb a shock, and to come out of it better than the competition - will be the key to survival and long-term prosperity."

Deloitte too exhorts resilience but assumes the reader knows its meaning already and therefore, offers added value in a different way: prescribing the five qualities of resilient leadership. The first and most important quality is not being a prick. "In everything they do during a crisis, resilient leaders express empathy and compassion for the human side of the upheaval - for example, acknowledging how radically their employees' personal priorities have shifted away from work to being concerned about family health, accommodating extended school closures, and absorbing the human angst of life-threatening uncertainty," Deloitte's CEO writes. Once the leader rises above prickdom, they should focus on the next four qualities: putting the mission first; aiming for speed over elegance; owning the narrative; and embracing the long view.

And while much of the consultants' prognosis is aimed at businesses and CEOs, they also venture boldly into the public domain. For example, McKinsey predicts, without an iota of hesitation, that there may be greater investment in public healthcare in the post-Covid-19 world, a prophecy that economists would do well to note.

Another novel suggestion from management consultants is to gradually open up the economy by resuming important economic activity like food supply chains, basic manufacturing and small businesses. In their noble selflessness, they do not include their own profession but we know such an omission will have dire consequences for all of us. In fact, we should insist theirs is the first sector that is reopened because by simply heeding their advice, we will be able to navigate the new normal with such speed and panache that even the North Star would be attainable.

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How management consultants are solving the COVID-19 crisis

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Management consultants have crunched the data, conducted the stakeholder analyses and have delivered their verdict. And it is one that the world struggles to see: we are in a crisis. Across the world, epidemiologists, economists and politicians have been flummoxed by COVID-19.

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CHANGED LUNGS

Other doctors painted a similar picture.

In Wuhan, where the novel coronavirus emerged, doctors at Tongji Hospital at the Huazhong University of Science and Technology said they initially turned quickly to intubation. Li Shusheng, head of the hospital's intensive care department, said a number of patients did not improve after ventilator treatment.

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Special Report: As Virus Advances, Doctors Rethink Rush to Ventilate

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CHANGED LUNGS Other doctors painted a similar picture. In Wuhan, where the novel coronavirus emerged, doctors at Tongji Hospital at the Huazhong University of Science and Technology said they initially turned quickly to intubation. Li Shusheng, head of the hospital's intensive care department, said a number of patients did not improve after ventilator treatment.

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I'm reposting the Monday newsletter on the site because I believe it's important. It's an effort to cut through a lot of the confusion and bullshit out there with regards to the current pandemic. Things have gotten contentious around the world with a lot of blaming, arguing, and finger-pointing going on. So, I'd like to use this as an opportunity to dispel anyone's sense of certainty about, well, anything.

Let's dive right in.

No one has any idea what the fuck is happening or what we should do about it

Right now, we have two large, complex systems. The first is a virus sweeping through the global population and our combined efforts to mitigate it. The second is a declining global economy. Both systems are incredibly difficult to measure and understand, much less predict. Both are so large and unruly that we struggle to even comprehend them in their entirety. And so far, pretty much everything we've thought about either has been utterly wrong.

Let's start with the first system: the spread of the virus. Despite months of research and testing, we still know very, very little. For example, we know that the virus is highly contagious, but we still have no clue how contagious. Studies pin its R0 number (how many people each sick person goes on to infect) as high as 6.6 and as low as 1.4. For reference, that's like saying the virus will infect anywhere from 20% of the population to 80%, a range so broad that you might as well pick a number out of a hat.

What about how many people have been infected? A series of studies came out in the past week showing that infections have likely been vastly undercounted and that there are thousands (perhaps millions) of people out there who have been infected but had no symptoms. This would be big news, because it would suggest that the virus is far less deadly than we thought. A recent Stanford study argued that the real mortality rate could be from 0.12% to 0.2%, making coronavirus hardly more deadly than the seasonal flu (which has a mortality rate of 0.1%). The problem is that these studies relied on inaccurate tests, did not test people randomly, and had other major methodological errors.

Okay, but what about deaths? A recent New York Times investigation found that there are potentially 20 to 30% more people dying from COVID-19-related deaths than are being reported (note: this study has also been widely challenged.) So, while there may be far more people being infected than we're counting, there's also likely far more people dying than we're counting.

This means... well, I don't know what the fuck this means. And neither does anybody else. Pretty much every projection model, including the ones government officials have relied upon, have been wildly incorrect so far. Lockdowns work! But, then again, they might not. Hydroxychloroquine was supposed to be a successful treatment. Then it turned out it wasn't. Remdesivir was supposed to be a successful treatment. Then it turned out it wasn't. Ventilators were supposed to save lives. Then it turned out they probably don't. The hospitals are going to be overloaded! Until they weren't. Smokers were all going to die! Wait, no, smokers might be the ones who live.

A few weeks ago, the US government's estimate of 240,000 deaths seemed so absurd that they revised it down to 60,000. Now that number seems completely absurd and will likely need to be revised much higher again. The cherry on top of the shit sundae, of course, is the US president talking about beaming ultraviolet rays through our bodies as though we live in an episode of Star Trek ... and then following that up by suggesting that maybe we inject ourselves with disinfectants.

If there's one thing we know for certain about this pandemic, it's that we know almost nothing for certain about this pandemic.

And that's only the first system we're wrestling with. The second is our economic system. Within a span of a couple weeks, the travel, hospitality, entertainment, restaurant, and brick and mortar retail industries have practically been annihilated. Just in the United States, 26 million people have lost their jobs in a little more than a month; an unemployment rate that rivals The Great Depression (note: this number is also likely being undercounted). The consensus is that we are certainly entering into a recession with whisperings of the D-word... no, not that D-word... the Depression D-word. The International Monetary Fund has said that we are potentially entering a global depression that will rival the 1930s in its depth and scope.

It's for this reason that working class people have begun protesting and rioting in the western world, demanding economic relief. Leaders and pundits have come out arguing that lockdowns are a "cure worse than the virus itself." Others argue that because the virus disproportionately affects the elderly, we should only tell old people to stay home and let the rest of the population build immunity as quickly as possible.

But there are many problems with these arguments. The first is that we don't even know if herd immunity can exist. We do not know how long immunity lasts for COVID-19. People who contract many of the other coronaviruses only remain immune for a short period of time. Sadly, there have already been a number of reported cases of people contracting COVID-19 twice. If people only remain immune for a few weeks or months, then herd immunity will be impossible.

Second, while the virus is far more dangerous to the elderly, it's no cakewalk for some of the young as well. There are reports of long-lasting damage to lungs, hearts and potentially even brain stems of those who have been hospitalized. Doctors are seeing strange numbers of infected young patients dying of strokes. On a new subreddit for people who have tested positive to share their experiences, there are horror stories of 25-year-olds on ventilators and people with persisting symptoms over a month later.

Third, re-opening the economy is not a magic bullet. As I wrote a couple weeks ago, nobody is going back out to a crowded public area any time soon, even if they are open. Would you go to a concert next week? I sure as fuck wouldn't. What about next month? Next year? Lock down or not, tens of millions of people are going to stay home no matter what, guaranteeing that consumer spending remains in the toilet and tens of millions remain unemployed.

Fourth, we don't even know that the economy was healthy in the first place. Some of the greatest investors in the world such as Ray Dalio have been arguing for years that we were due for a once-in-a-century collapse. For years, many pointed to negative interest rates and high levels of debt as a ticking time bomb waiting to go off. A pandemic may actually not be the cause of our economic woes, but merely the proverbial straw that broke the camel's back.

Then again, this could all be wrong. Epidemiological projections have been famously wrong for the past month, but economic projections have been consistently wrong for... well, pretty much as long as there's been economists.

We still don't know what the COVID-19 does to the body or its long-term repercussions. We don't know if building herd immunity is even possible, much less worth the cost. We don't know how many people would die if we opened the economy up sooner rather than later, and we don't know how stimulative opening up the economy would be anyway.

We just don't know a damn thing. Nobody does. So, stop acting like you do.

An impossible philosophical conundrum

Probably the most difficult book I've ever read cover to cover was Reasons and Persons by the Oxford philosopher Derek Parfit. It's a book that's widely considered the most important philosophical work of the last 50 years.

The book is divided into four parts. Each part presents its own logical conundrum that leads the reader to unexpected and uncomfortable places. For example, the first part argues that it is impossible to act in self-interest. Similarly, the third part argues that the notion of an identity or "self" is irrational and incoherent to begin with. The logical arguments are meticulous and airtight. You come away from each section with your head spinning.

In the fourth and final part of the book, Parfit explains through a number of clever thought experiments that our basic ethical intuitions are often incoherent.

He imagines a number of scenarios where you are forced to consider questions like: would it be ethical to let one person die to guarantee a million people do not live in excruciating poverty? What about letting one person die to guarantee a million people go from feeling okay in life to feeling exquisitely happy and healthy? What about a thousand people? What about ten people? What if the person who dies is old and already sick? What if they are a violent criminal? What if they are an innocent child? What if they are picked at random?

Basically: what is the trade-off between quality of life and life itself? At what point does a life cease to be worth living? And at what point is the marginal increase in happiness of millions worth the profound misery of a few?

There is no correct answer to these questions, yet we all have deeply-held intuitions about what feels right and wrong about them. Parfit, of course, does his Parfit thing and shows how all of our instincts around these questions are self-contradictory and irrational. But regardless, we all have thresholds where we feel comfortable making certain trade-offs between well-being and life itself. Yet, we rarely think about that threshold because the question is incredibly uncomfortable and upsetting to think about.

But, if you do think about it, this ethical conundrum is at the heart of the most contentious political and economic policy questions. Do you go to war, sacrificing the lives of thousands of young people to promote and improve the lives of hundreds of millions? Do you institute policies that will ruin the lives of a few to improve the lives of the many? Does it matter who the few are? Does it matter who the many are?

In the case of COVID-19, it appears to many that there is a clear trade-off between economic stability for billions, and the lives of, let's say, a few million. (I would argue that this trade-off is an illusion, but we'll get to that.) People have opposing intuitions about these questions and cannot really be argued out of them. One camp is willing to sacrifice life for greater life. The other is willing to sacrifice life for greater life. You say tomato, I say... tomato.

Unfortunately, our information networks and media industry are set up to capitalize on these sorts of "us vs them" categories and exploit them. Therefore, people on one side of the ethical quandary find themselves repeatedly bombarded with certain studies, facts, and data that seem to justify their view. And people on the other side are exposed to the studies, facts, and data that seem to justify theirs.

But this is a false either/or argument to begin with. There are substantial public health risks. There are substantial economic risks. One triggered the other but that does not mean that they can be interchanged. An economic depression is not like returning an ill-fitted pair of pants to the store. You can't walk in and say, "Hold up, I want my 26 million jobs back." That ship has sailed. The economy is fucked. Public health is fucked. We do not know the extent or depth of the fuckage of either. Nor do we know to the extent that they interact with (or should I say, "fuck with") one another.

We are mostly blind here. And even if we could see the trade-offs clearly, we still wouldn't agree on what is ethical and appropriate. We would simply muddle on, each individually making the best of a terrible situation, each blindly believing they are right and just in their intuitions.

So, let go of the fight. Focus on yourself. Focus on your loved ones. And assume the worst. Assume nothing-not the virus, nor the economic downturn-is going to get resolved any time soon. That way, you will be prepared-mentally, emotionally, financially, and physically-for all possible scenarios. And if things turn out okay sooner than you thought, all the better.

Whatever the response is, it won't be evenly distributed

But despite all of the uncertainty and ethical headaches, here are a few things that do seem to be clear and true:

This is definitely worse than the flu. This is important to return to, since it was just a month ago that many people (including many readers of this newsletter) were claiming that we were all getting worked up over nothing. This was dangerously false. Despite the wide-ranging estimates and the flawed sets of data, even the most optimistic numbers put COVID-19 as significantly more dangerous than the flu. It is far more contagious, gives people worse symptoms for much longer, and is significantly more lethal. There is a reason why COVID-19 has killed as many people in six weeks as the flu usually does in 6-8 months. And we're still at the very beginning of this thing.

This will last a long time. Until there are reliable therapies and/or a vaccine, our lives will continue to be disrupted, we will continue to socially distance, we will continue to stay home. We don't know how long it will take to develop these therapies and vaccines (or if a vaccine is even possible), but right now the most optimistic guesses are some time in 2021. Until then, I would not expect the global economy to get much better. But hey, what the fuck do I know?

Place matters. As far as we can tell, population density and indoor lifestyles are some of the largest predictors of the spread. New studies suggest that almost all infections occur indoors. Similarly, some cultures seem to be better suited for social distancing than others. Some cities have more resources, so staying at home is easier for people. Some places have more elderly and vulnerable people than others. Curves in some places started earlier than others.

Given the three points above, I think it's reasonable to expect that not all policy responses should or will look the same. Each local population manages their situation based on the unique factors of the area they live in. Policies that make sense in New York City probably don't make sense in Saskatoon and vice-versa. We shouldn't expect people in Texas to behave the same way as people in Taiwan, nor should we shame them for not doing so. We shouldn't expect that government policies that work fine in Singapore will work well in New Jersey, nor should we be upset that they won't.

We should reserve judgment about these things. Especially online when we're all coming from different places globally, politically, culturally, etc. It's easy for me, in New York City, to get pissed off when I see masses of people enjoying the beach in Florida. But it's also different. Culturally, geographically, demographically, it is different. And it's in these moments, when I find myself getting sucked into my emotions, or climbing up onto my high horse of social media judgments, that I remind myself: I don't know a damn thing.

And neither do you.

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Nobody Knows What Is Going On | Mark Manson

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I'm reposting the Monday newsletter on the site because I believe it's important. It's an effort to cut through a lot of the confusion and bullshit out there with regards to the current pandemic. Things have gotten contentious around the world with a lot of blaming, arguing, and finger-pointing going on.

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Data-Driven Prediction of COVID-19 Pandemic End Dates

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Data-Driven Prediction of COVID-19 Pandemic End Dates

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The Data-Driven Innovation Lab develops data science and artificial intelligence methods and tools to inform and inspire innovation decisions and planning at individual, company and government levels.

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There is risk and there is uncertainty. Since the days of Frank Knight, economists have differentiated the two. Risk has a known probability distribution. For uncertainty, the probability distribution is unknown. Covid-19 makes us confront uncertainty, not risk. In either event, agents maximise expected payoffs. For risk, there is a given probability distribution that can be used by everyone. For uncertainty, there is a subjective probability distribution, which can, and does, vary from individual to individual. How do I devise this subjective probability distribution? Through information and experience I already possess. There are various rationality assumptions used by economists. They are often violated. Otherwise, behavioural economics wouldn't have taken off. Typically, given a situation, when your decision doesn't agree with mine, I say you are irrational. However, with uncertainty, the problem may not be with rationality assumptions, but with differences in subjective probability distributions. Because of Covid-19, there is a certain risk of getting infected. Let us call this the infection rate-total infections divided by total population. Do I know what this infection rate is, for India, or any other country for that matter? I don't. I am not being pedantic. To the best of my knowledge, no country has done universal testing.

No country has done universal testing for a proper random sample either. ICMR has told us more than 75% of Indian patients will be asymptomatic. Who do we test? Those who show symptoms, those who have been in contact with confirmed patients, and those who suffer from severe respiratory diseases. Most countries do something similar. In other words, when I work out an infection rate based on those tested, there is a sampling bias. This isn't a proper infection rate. To the best of my understanding, the only country where we have had something like a random sample is Iceland. There, the infection rate was 0.8%. There are similar caveats about the death rate. If I mechanically divide India's Covid-19 deaths by its total number of confirmed cases, I will get a death rate just over 3%. The global figure is a little less than 7%. But, neither of these is a death rate for the total population, since only those with severe symptoms are included in infection numbers. Thus, 3% or 7% are over-estimates. In a controlled environment like Diamond Princess, death rate as a ratio of total passengers, and not those infected, was less than 0.4%. The true infection rate and true death rate are not alarming numbers.

What does this have to do with differential subjective probability distributions? There are slices in India's population pyramid, with rural/urban and other spatial differences too. Consider two extremes. (a) There are those who are globalised in information access and morbidity. Life expectancy is 80+ and there are lifestyle diseases like diabetes and high blood pressure. This co-morbidity increases possible death rates, and thanks to globalised access to information, certainly increases perceptions about death rates, making them out to be higher than they are. Some of them have fixed incomes, regardless of what happens to lockdown. Therefore, if you think in terms of maximising expected payoffs with a subjective distribution, high probability is attached to loss of life and low probability to loss of livelihood. I have simplified, but you get the general idea. (b) Contrast this with someone whose life expectancy is 60, without a fixed income stream and whose health concerns are tuberculosis and water-borne diseases, not Covid-19. Nor is access to information that globalised. High subjective probability will be attached to loss of livelihood and low probability to death from Covid-19. Both (a) and (b) reflect subjective probabilities. Neither is "irrational". There is tension between (a) and (b). (a)-types would like lockdown to continue indefinitely, until the long tail of the infection curve tapers off, perhaps beyond September. (b) Types would like lockdown to be eased soon, with necessary restrictions in hotspots. There is indeed tension between lives and livelihood. Even if health outcomes and information access are like (a)-types, but income is contingent on growth, preferences might mirror the (b)-type.

Public policy needs to balance such differential individual preferences. This used to be the aggregation issue of the once fashionable, and somewhat esoteric, social/collective choice theory. Doing injustice to that entire literature and reducing it to column-type language, if preferences are heterogeneous, one set of individuals imposes its choice on the rest. (a)-types disproportionately influence policy. This determination of aggregate preferences is a dynamic process.

Therefore, sooner or later, (b)-types contest this, and as lockdown is prolonged and livelihood costs mount, discontent surfaces, as it has across a range of countries. There were also welfare economics notions that pre-dated social choice theory, such as compensation principles of Kaldor, Hicks and Scitovsky. The point can be made using those stereotypes of (a) and (b). Specifically, (a)-types need to compensate (b)-types for their losses. To state it starkly, livelihood losses suffered by (b)-types need to be compensated by the government through redistributive measures and this has to be financed by higher taxes imposed on (a)-types. The right question for (a)-types is not whether they want lockdown to continue, but whether they are willing to pay a Covid-tax to support lockdown extension.

This is meant to be a caricature, but it illustrates the public policy dilemma. Note that without growth revival, tax-paying capacity of (b)-types is limited and with job losses, some (a)-types become (b)-types. The choice is starker.
The author is Chairman, Economic Advisory Council to the PM
Views are personal
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Risk, uncertainty and COVID-19: A stark choice

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There is risk and there is uncertainty. Since the days of Frank Knight, economists have differentiated the two. Risk has a known probability distribution. For uncertainty, the probability distribution is unknown. Covid-19 makes us confront uncertainty, not risk. In either event, agents maximise expected payoffs.

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The Israeli intelligence agency has played an outsize role in acquiring the medical gear, and knowledge, needed in the pandemic.

Ultra-Orthodox Jews in Bnei Brak, Israel, last week. Credit... Jack Guez/Agence France-Presse - Getty Images

TEL AVIV, Israel - When Israel's health minister was found to be infected with the coronavirus early this month, all high-level officials in close contact with him were quarantined, including one who stood out: the director of the Mossad, the storied Israeli spy service.

Mossad officers, primarily associated with covert operations abroad in the name of protecting Israel, are not normally in the business of public health.

So Israelis were immediately intrigued.

Why would the Mossad director, Yossi Cohen, a widely respected figure in the country, have even been in the same room as the health minister, Yaakov Litzman?

Mr. Cohen's powerful agency, it turns out, has been deeply involved in Israel's fight against the virus, and has been one of the country's most valuable assets in acquiring medical equipment and manufacturing technology abroad, according to Israeli medical and security officials.

As countries around the world compete ferociously for limited supplies during the pandemic, they are turning to any help available, and flexing their muscles unapologetically.

And with the Mossad having determined that Iran - struggling with its own coronavirus crisis - no longer represents an immediate security threat, the agency could afford to immerse itself in the health emergency, according to multiple people knowledgeable about its operations.

Initial predictions for the toll of the virus in Israel were dire, though so far they have proved too pessimistic. With nearly 11,000 cases of the virus now confirmed and 103 deaths, Israel does not rank among the hardest-hit countries in the world.

"The peak expansion rate has been behind us for about two weeks now, and will probably wane almost completely within two weeks," said an article published on Sunday by Prof. Isaac Ben Israel of Tel Aviv University.

But in early February, officials at Sheba Medical Center, Israel's biggest hospital, realized that they needed more ventilators and other gear. And around that time, Prof. Yitshak Kreiss, the director general of the hospital, met with Mr. Cohen, the Mossad chief, at a private event involving a mutual friend - not unusual in a small country where senior figures often move in the same social circles.

By then, Mr. Cohen had already begun to assess how the Mossad could help the Israeli health system. Professor Kreiss said he enumerated the most urgent equipment needs to Mr. Cohen, who obtained further lists from the Health Ministry, and the Mossad began activating its international network to find the items needed.

In early March, a command and control center was set up to handle the distribution of medical gear across the country, with Mr. Cohen at its head and headquartered at Sheba. There were representatives from the Mossad, the Ministry of Defense purchasing division, and the military intelligence's highly secretive Unit 81, which deals with the development of advanced espionage equipment.

Professor Kreiss, a former brigadier general in the army and a former surgeon general for the military, said the Mossad had been pivotal in helping his institution secure vital medical equipment and expertise from abroad.

"It is only in Israel that the Sheba hospital could have enlisted the help of the Mossad," he said in an interview. "Can you imagine Mount Sinai Hospital going to the C.I.A. for help?" he added, referring to the New York medical center.

Professor Kreiss declined to say precisely how Mossad officers had helped the Israeli medical establishment or where the imported equipment came from. But according to six current or former Israeli officials with knowledge of the Mossad's operations, the agency used international contacts to avert shortages that might have overwhelmed Israel's health system.

The six people, who spoke on the condition of anonymity because the Mossad's activities are classified, said the spy agency's contacts had proved invaluable in enabling Israel to acquire ventilators and testing material that Mr. Litzman's health ministry had been unable to secure. Despite those efforts, however, there is still a lack of testing capacity in Israel.

These people would not confirm non-Israeli media reports that some of the items were acquired from neighboring Arab nations with no official diplomatic relations with Israel.

But at least one senior Mossad official acknowledged in an interview with Ilana Dayan, host of "Uvda," or "Fact," Israel's Channel 12 TV newsmagazine, that in some instances, the agency had acquired items that other countries had already ordered.

By the end of the first week of April, the people with knowledge of the operations said, Mr. Cohen was confident that Mossad operatives had ensured Israel would possess enough ventilators to cope with the worst forecasts.

If Mr. Litzman, whose initially cavalier attitude toward the virus has been sharply criticized, symbolizes for some the shortcomings of the government's response, for many Israelis the Mossad represents the opposite. Word of its assistance in fighting the pandemic has bolstered the Mossad's image as among the country's most admired government institutions.

There was no time to waste, Professor Kreiss recalled, praising what he described as the single-mindedness of purpose shown by Mossad agents. "Part of their ethos is to execute their task at any price," he said.

That ethos has helped build Mossad's reputation.

It is best known for the capture of the Nazi fugitive Adolph Eichmann in 1960, its lethal response after the massacre of Israeli athletes at the 1972 Munich Olympics, and the 2018 theft of secret nuclear records from Iran, which Israelis regard as their most dangerous adversary.

The agency has also had some high-profile failures, among them the botched assassination attempt in 1997 on Khaled Meshal, a senior figure in Hamas.

To some extent, the Mossad's intervention in the pandemic is an acute embarrassment for officials of the Health Ministry, who ordinarily speak freely to the media but declined to comment on any aspect of the spy service's role.

That the country's health system had to enlist Mossad was evidence that it had not readied itself to respond to the type of threat represented by the coronavirus, according to a high-ranking figure in the Israeli health system, who requested anonymity because he was criticizing the ministry's directorate.

The first shipment acquired abroad by the Mossad arrived in Israel on a special flight on March 19: 100,000 coronavirus testing kits, saidan official from the prime minister's office.

Subsequent shipments included more testing kits, 1.5 million surgical masks, tens of thousands of N-95 masks, protective overalls for first-aid crews, protective goggles and a range of medications, according to a high-ranking official knowledgeable about the Mossad operation.

The Mossad also helped obtain technology from outside Israel that have enabled many Israeli laboratories to conduct coronavirus tests. Mossad operatives also secured the necessary know-how to produce ventilators in Israel.

Using technological expertise brought in by the Mossad, production lines that can produce 25 million protective masks a month are gradually being set up, a high-ranking security official said.

According to one senior Israeli official, the Mossad knew it had to act urgently, with the demand for such equipment expected to grow and with the understanding that countries would eventually refuse to export essential medical products.

The Mossad's efforts were easier in nondemocratic countries where intelligence agencies have more influence with the rulers, this official said. The efforts were based on prior familiarity and mutual trust between the Mossad and those agencies.

In some instances, the official said, Mr. Cohen personally contacted his counterparts. Such contacts were often enough to expedite purchase of the goods. In other cases, the official said, Mr. Cohen spoke directly to the rulers of particular countries, which he declined to identify.

As other countries began to hunt for the same gear, competition intensified, and the battle was not always waged fairly. While none of the people with knowledge of the Mossad's operations explicitly acknowledged that the agency may have played dirty, they did not rule it out.

The Mossad has invested heavily over the past decade in developing relations with states in the Middle East and Asia that remain hostile to Israel, at least officially.

There have been a number of reports that Mr. Cohen has met frequently with the rulers and spy bosses of the United Arab Emirates, Egypt, Saudi Arabia, Jordan and Qatar. In 2018, Mr. Cohen set up an unusual public meeting between Prime Minister Benjamin Netanyahu of Israel and Sultan Qaboos of Oman, who died in January.

Not all the Mossad coronavirus operations were successful.

One of the people knowledgeable about the failures said Mossad emissaries had been outmaneuvered at least once in Germany, where government couriers seized goods the Israelis were about to ship home from a factory. Another time, a load of sanitizer in India was delayed by customs officers and the Mossad abandoned the shipment.

Nevertheless, the Mossad will almost certainly be remembered for coming to the country's rescue in an unusual battle against an invisible enemy.

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Israel's Not-So-Secret Weapon in Coronavirus Fight: The Spies of Mossad

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The Israeli intelligence agency has played an outsize role in acquiring the medical gear, and knowledge, needed in the pandemic. TEL AVIV, Israel - When Israel's health minister was found to be infected with the coronavirus early this month, all high-level officials in close contact with him were quarantined, including one who stood out: the director of the Mossad, the storied Israeli spy service.

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The coronavirus didn't break America. It revealed what was already broken.

Oliver Munday

When the virus came here, it found a country with serious underlying conditions, and it exploited them ruthlessly. Chronic ills-a corrupt political class, a sclerotic bureaucracy, a heartless economy, a divided and distracted public-had gone untreated for years. We had learned to live, uncomfortably, with the symptoms. It took the scale and intimacy of a pandemic to expose their severity-to shock Americans with the recognition that we are in the high-risk category.

The crisis demanded a response that was swift, rational, and collective. The United States reacted instead like Pakistan or Belarus-like a country with shoddy infrastructure and a dysfunctional government whose leaders were too corrupt or stupid to head off mass suffering. The administration squandered two irretrievable months to prepare. From the president came willful blindness, scapegoating, boasts, and lies. From his mouthpieces, conspiracy theories and miracle cures. A few senators and corporate executives acted quickly-not to prevent the coming disaster, but to profit from it. When a government doctor tried to warn the public of the danger, the White House took the mic and politicized the message.

Every morning in the endless month of March, Americans woke up to find themselves citizens of a failed state. With no national plan-no coherent instructions at all- families, schools, and offices were left to decide on their own whether to shut down and take shelter. When test kits, masks, gowns, and ventilators were found to be in desperately short supply, governors pleaded for them from the White House, which stalled, then called on private enterprise, which couldn't deliver. States and cities were forced into bidding wars that left them prey to price gouging and corporate profiteering. Civilians took out their sewing machines to try to keep ill-equipped hospital workers healthy and their patients alive. Russia, Taiwan, and the United Nations sent humanitarian aid to the world's richest power-a beggar nation in utter chaos.

Yascha Mounk: No testing, no treatment, no herd immunity, no easy way out

Donald Trump saw the crisis almost entirely in personal and political terms. Fearing for his reelection, he declared the coronavirus pandemic a war, and himself a wartime president. But the leader he brings to mind is Marshal Philippe Pétain, the French general who, in 1940, signed an armistice with Germany after its rout of French defenses, then formed the pro-Nazi Vichy regime. Like Pétain, Trump collaborated with the invader and abandoned his country to a prolonged disaster. And, like France in 1940, America in 2020 has stunned itself with a collapse that's larger and deeper than one miserable leader. Some future autopsy of the pandemic might be called Strange Defeat, after the historian and Resistance fighter Marc Bloch's contemporaneous study of the fall of France. Despite countless examples around the U.S. of individual courage and sacrifice, the failure is national. And it should force a question that most Americans have never had to ask: Do we trust our leaders and one another enough to summon a collective response to a mortal threat? Are we still capable of self-government?

This is the third major crisis of the short 21st century. The first, on September 11, 2001, came when Americans were still living mentally in the previous century, and the memory of depression, world war, and cold war remained strong. On that day, people in the rural heartland did not see New York as an alien stew of immigrants and liberals that deserved its fate, but as a great American city that had taken a hit for the whole country. Firefighters from Indiana drove 800 miles to help the rescue effort at Ground Zero. Our civic reflex was to mourn and mobilize together.

Partisan politics and terrible policies, especially the Iraq War, erased the sense of national unity and fed a bitterness toward the political class that never really faded. The second crisis, in 2008, intensified it. At the top, the financial crash could almost be considered a success. Congress passed a bipartisan bailout bill that saved the financial system. Outgoing Bush-administration officials cooperated with incoming Obama administration officials. The experts at the Federal Reserve and the Treasury Department used monetary and fiscal policy to prevent a second Great Depression. Leading bankers were shamed but not prosecuted; most of them kept their fortunes and some their jobs. Before long they were back in business. A Wall Street trader told me that the financial crisis had been a "speed bump."

All of the lasting pain was felt in the middle and at the bottom, by Americans who had taken on debt and lost their jobs, homes, and retirement savings. Many of them never recovered, and young people who came of age in the Great Recession are doomed to be poorer than their parents. Inequality-the fundamental, relentless force in American life since the late 1970s-grew worse.

This second crisis drove a profound wedge between Americans: between the upper and lower classes, Republicans and Democrats, metropolitan and rural people, the native-born and immigrants, ordinary Americans and their leaders. Social bonds had been under growing strain for several decades, and now they began to tear. The reforms of the Obama years, important as they were-in health care, financial regulation, green energy-had only palliative effects. The long recovery over the past decade enriched corporations and investors, lulled professionals, and left the working class further behind. The lasting effect of the slump was to increase polarization and to discredit authority, especially government's.

Both parties were slow to grasp how much credibility they'd lost. The coming politics was populist. Its harbinger wasn't Barack Obama but Sarah Palin, the absurdly unready vice-presidential candidate who scorned expertise and reveled in celebrity. She was Donald Trump's John the Baptist.
David Frum: This is Trump's fault
Trump came to power as the repudiation of the Republican establishment. But the conservative political class and the new leader soon reached an understanding. Whatever their differences on issues like trade and immigration, they shared a basic goal: to strip-mine public assets for the benefit of private interests. Republican politicians and donors who wanted government to do as little as possible for the common good could live happily with a regime that barely knew how to govern at all, and they made themselves Trump's footmen.

Like a wanton boy throwing matches in a parched field, Trump began to immolate what was left of national civic life. He never even pretended to be president of the whole country, but pitted us against one another along lines of race, sex, religion, citizenship, education, region, and-every day of his presidency-political party. His main tool of governance was to lie. A third of the country locked itself in a hall of mirrors that it believed to be reality; a third drove itself mad with the effort to hold on to the idea of knowable truth; and a third gave up even trying.

Trump acquired a federal government crippled by years of right-wing ideological assault, politicization by both parties, and steady defunding. He set about finishing off the job and destroying the professional civil service. He drove out some of the most talented and experienced career officials, left essential positions unfilled, and installed loyalists as commissars over the cowed survivors, with one purpose: to serve his own interests. His major legislative accomplishment, one of the largest tax cuts in history, sent hundreds of billions of dollars to corporations and the rich. The beneficiaries flocked to patronize his resorts and line his reelection pockets. If lying was his means for using power, corruption was his end.

Read: The coronavirus's real and immediate threat to democracy

This was the American landscape that lay open to the virus: in prosperous cities, a class of globally connected desk workers dependent on a class of precarious and invisible service workers; in the countryside, decaying communities in revolt against the modern world; on social media, mutual hatred and endless vituperation among different camps; in the economy, even with full employment, a large and growing gap between triumphant capital and beleaguered labor; in Washington, an empty government led by a con man and his intellectually bankrupt party; around the country, a mood of cynical exhaustion, with no vision of a shared identity or future.

If the pandemic really is a kind of war, it's the first to be fought on this soil in a century and a half. Invasion and occupation expose a society's fault lines, exaggerating what goes unnoticed or accepted in peacetime, clarifying essential truths, raising the smell of buried rot.

The virus should have united Americans against a common threat. With different leadership, it might have. Instead, even as it spread from blue to red areas, attitudes broke down along familiar partisan lines. The virus also should have been a great leveler. You don't have to be in the military or in debt to be a target-you just have to be human. But from the start, its effects have been skewed by the inequality that we've tolerated for so long. When tests for the virus were almost impossible to find, the wealthy and connected-the model and reality-TV host Heidi Klum, the entire roster of the Brooklyn Nets, the president's conservative allies- were somehow able to get tested, despite many showing no symptoms. The smattering of individual results did nothing to protect public health. Meanwhile, ordinary people with fevers and chills had to wait in long and possibly infectious lines, only to be turned away because they weren't actually suffocating. An internet joke proposed that the only way to find out whether you had the virus was to sneeze in a rich person's face.

When Trump was asked about this blatant unfairness, he expressed disapproval but added, " Perhaps that's been the story of life." Most Americans hardly register this kind of special privilege in normal times. But in the first weeks of the pandemic it sparked outrage, as if, during a general mobilization, the rich had been allowed to buy their way out of military service and hoard gas masks. As the contagion has spread, its victims have been likely to be poor, black, and brown people. The gross inequality of our health-care system is evident in the sight of refrigerated trucks lined up outside public hospitals.
Ronald J. Krotoszynski, Jr.: States are using the pandemic to roll back Americans' rights
We now have two categories of work: essential and nonessential. Who have the essential workers turned out to be? Mostly people in low-paying jobs that require their physical presence and put their health directly at risk: warehouse workers, shelf-stockers, Instacart shoppers, delivery drivers, municipal employees, hospital staffers, home health aides, long-haul truckers. Doctors and nurses are the pandemic's combat heroes, but the supermarket cashier with her bottle of sanitizer and the UPS driver with his latex gloves are the supply and logistics troops who keep the frontline forces intact. In a smartphone economy that hides whole classes of human beings, we're learning where our food and goods come from, who keeps us alive. An order of organic baby arugula on AmazonFresh is cheap and arrives overnight in part because the people who grow it, sort it, pack it, and deliver it have to keep working while sick. For most service workers, sick leave turns out to be an impossible luxury. It's worth asking if we would accept a higher price and slower delivery so that they could stay home.

The pandemic has also clarified the meaning of nonessential workers. One example is Kelly Loeffler, the Republican junior senator from Georgia, whose sole qualification for the empty seat that she was given in January is her immense wealth. Less than three weeks into the job, after a dire private briefing about the virus, she got even richer from the selling-off of stocks, then she accused Democrats of exaggerating the danger and gave her constituents false assurances that may well have gotten them killed. Loeffler's impulses in public service are those of a dangerous parasite. A body politic that would place someone like this in high office is well advanced in decay.

The purest embodiment of political nihilism is not Trump himself but his son-in-law and senior adviser, Jared Kushner. In his short lifetime, Kushner has been fraudulently promoted as both a meritocrat and a populist. He was born into a moneyed real-estate family the month Ronald Reagan entered the Oval Office, in 1981-a princeling of the second Gilded Age. Despite Jared's mediocre academic record, he was admitted to Harvard after his father, Charles, pledged a $2.5 million donation to the university. Father helped son with $10 million in loans for a start in the family business, then Jared continued his elite education at the law and business schools of NYU, where his father had contributed $3 million. Jared repaid his father's support with fierce loyalty when Charles was sentenced to two years in federal prison in 2005 for trying to resolve a family legal quarrel by entrapping his sister's husband with a prostitute and videotaping the encounter.
Francis Fukuyama: The thing that determines a country's resistance to the coronavirus
Jared Kushner failed as a skyscraper owner and a newspaper publisher, but he always found someone to rescue him, and his self-confidence only grew. In American Oligarchs, Andrea Bernstein describes how he adopted the outlook of a risk-taking entrepreneur, a "disruptor" of the new economy. Under the influence of his mentor Rupert Murdoch, he found ways to fuse his financial, political, and journalistic pursuits. He made conflicts of interest his business model.

So when his father-in-law became president, Kushner quickly gained power in an administration that raised amateurism, nepotism, and corruption to governing principles. As long as he busied himself with Middle East peace, his feckless meddling didn't matter to most Americans. But since he became an influential adviser to Trump on the coronavirus pandemic, the result has been mass death.

In his first week on the job, in mid-March, Kushner co-authored the worst Oval Office speech in memory, interrupted the vital work of other officials, may have compromised security protocols, flirted with conflicts of interest and violations of federal law, and made fatuous promises that quickly turned to dust. " The federal government is not designed to solve all our problems," he said, explaining how he would tap his corporate connections to create drive-through testing sites. They never materialized. He was convinced by corporate leaders that Trump should not use presidential authority to compel industries to manufacture ventilators-then Kushner's own attempt to negotiate a deal with General Motors fell through. With no loss of faith in himself, he blamed shortages of necessary equipment and gear on incompetent state governors.

To watch this pale, slim-suited dilettante breeze into the middle of a deadly crisis, dispensing business-school jargon to cloud the massive failure of his father-in-law's administration, is to see the collapse of a whole approach to governing. It turns out that scientific experts and other civil servants are not traitorous members of a "deep state"- they're essential workers, and marginalizing them in favor of ideologues and sycophants is a threat to the nation's health. It turns out that "nimble" companies can't prepare for a catastrophe or distribute lifesaving goods- only a competent federal government can do that. It turns out that everything has a cost, and years of attacking government, squeezing it dry and draining its morale, inflict a heavy cost that the public has to pay in lives. All the programs defunded, stockpiles depleted, and plans scrapped meant that we had become a second-rate nation. Then came the virus and this strange defeat.
Read: Trump's coronavirus message is revisionist history
The fight to overcome the pandemic must also be a fight to recover the health of our country, and build it anew, or the hardship and grief we're now enduring will never be redeemed. Under our current leadership, nothing will change. If 9/11 and 2008 wore out trust in the old political establishment, 2020 should kill off the idea that anti-politics is our salvation. But putting an end to this regime, so necessary and deserved, is only the beginning.

We're faced with a choice that the crisis makes inescapably clear. We can stay hunkered down in self-isolation, fearing and shunning one another, letting our common bond wear away to nothing. Or we can use this pause in our normal lives to pay attention to the hospital workers holding up cellphones so their patients can say goodbye to loved ones; the planeload of medical workers flying from Atlanta to help in New York; the aerospace workers in Massachusetts demanding that their factory be converted to ventilator production; the Floridians standing in long lines because they couldn't get through by phone to the skeletal unemployment office; the residents of Milwaukee braving endless waits, hail, and contagion to vote in an election forced on them by partisan justices. We can learn from these dreadful days that stupidity and injustice are lethal; that, in a democracy, being a citizen is essential work; that the alternative to solidarity is death. After we've come out of hiding and taken off our masks, we should not forget what it was like to be alone.
This article appears in the June 2020 print edition with the headline "Underlying Conditions."

We want to hear what you think about this article. Submit a letter to the editor or write to letters@theatlantic.com.

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The coronavirus didn't break America. It revealed what was already broken. When the virus came here, it found a country with serious underlying conditions, and it exploited them ruthlessly. Chronic ills-a corrupt political class, a sclerotic bureaucracy, a heartless economy, a divided and distracted public-had gone untreated for years.

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Vet your sources or more people will be deluded
Unfortunately, all of the above are signs of DKE-19, a highly contagious illness threatening the response against COVID-19. We must act today to flatten the curve of armchair epidemiology, or we will all be in peril.

Dunning-Kruger Effect (DKE) is a phenomenon where people lack the ability to understand their lack of ability. While strains of DKE typically circulate seasonally, a new and more virulent strain called DKE-19 is now reaching pandemic proportions.

When you're done reading this article, this is what you'll take away:

It's coming at an exponential speed: gradually, then suddenly, then suddenlier.

When it does, your feeds will be overwhelmed.

Exhausted fact checkers will break down. Some will die of sadness.

The only way to prevent this is social media distancing. Not tomorrow. Today.

That means vetting sources BEFORE you share, starting now.

What are the symptoms?
Signs of DKE-19 generally appear 3-5 days after learning that the word "epidemiology" is not the study of skin diseases. Symptoms vary, but include extreme claims, making charts, and publishing on Medium. Although most cases are mild or even entirely asymptomatic, the recent outbreak indicates that severe DKE-19 primarily affects men ages 24-36 working in tech, for reasons unknown to scientists who are unaccountably also men.
How is the infection spread?
DKE-19 is in the same family of misinformation viruses as the one that caused the b00m3R-FB outbreak in 2016. It is transmitted person-to-person through a variety of means, including listening to/repeating bullshit while on the toilet ("feco-aural transmission"), and sharing dirty tweedles.

Transmission most often occurs through casual digital contact from asymptomatic individuals. This strain tends to be hidden in well-intended partial truths, making population detection more difficult. DKE-19 can hide in viral reservoirs throughout the internet. Once infection takes hold, DKE-19 is exceedingly difficult to treat. Several cases of second-hand craniofacial injury have been reported, related to collisions between desks and actual experts' heads.

Recent lockdowns to contain COVID-19 have resulted in Bay Area tech employees having vastly more time on their thumbs. We expect that exponential growth of bullshit takes are likely to grow exponentialer until the heat death of the universe and/or last Tuesday.
Are you at risk?
We have combined the collective expertise of three people with PhDs to create a machine learning model which predicts the spread of DKE-19-related misinformation. We believe this to be the best, most accurate infectious disease model published on Medium as of the time of this writing.
Things you can do to flatten the curve

Wash your phone for at least 20 seconds fully immersed in soapy water

6 ft of social media distancing

If take appears hot/feverish, seek expert help

Check the qualifications of authors BEFORE sharing

Listen to people who know what they are talking about

Push for better social media infrastructure that can slow the spread of DKE-19 and future strains

Only you can help #flattenthecurve of DKE-19

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Flatten the Curve of Armchair Epidemiology

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Vet your sources or more people will be deluded Unfortunately, all of the above are signs of DKE-19, a highly contagious illness threatening the response against COVID-19. We must act today to flatten the curve of armchair epidemiology, or we will all be in peril.

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Daily wage labourers stand in a queue for free food at a construction site where activity has been halted due to the nationwide lockdown to slow the spreading of the coronavirus, in New Delhi, April 10, 2020. Photo: Reuters/Adnan Abidi.
Intuitively, it feels true that the earlier we impose a lockdown, the more effectively we can contain the coronavirus pandemic. However there is a strong possibility that a lockdown applied too early may yield only subpar results. To understand how, it's important to know what a lockdown can and cannot do.

It is not the purpose of lockdowns to stop the epidemic by eliminating the virus. Viral epidemics stop only when the population acquires herd immunity: that is, when a sufficient percentage of the population becomes immune to the virus, and the virus can't spread anymore. Herd immunity can be acquired either through vaccination or by becoming infected by the virus.

Since we have no vaccine, the epidemic will stop only when a sufficient number of us get infected (and subsequently recover). What percentage of the population needs to become infected in order to stop the epidemic depends on the virus's infectivity. It's generally of the order of 50-80%.

These days, many people get angry by the mere mention of the term 'herd immunity' because they see it as a lazy strategy that lets people contract the disease to build up the immunity in the population. But herd immunity is not a strategy: it's simply a scientific fact that our strategies need to work around. A lockdown is one such workaround strategy. Lockdowns are not meant to bring down the proportion of immune individuals required to slow the epidemic. Instead, they can help keep too many people from being infected to the point of requiring hospitalisation at the same time, thus overwhelming our hospitals.

We need to be clear about the lockdown's objectives. Imposing a lockdown in the hope that it will somehow eliminate the epidemic is futile. Many of us have been led to believe that if we effectively implement a lockdown, we will reduce the number of people infected. It's true that the lockdown can limit the number of infected people at a particular point in time - but ultimately, the total number of people who will be infected is the same with and without lockdown. The lockdown is a way to ensure this total is spread over a longer period.

In short, a well-designed lockdown can flatten the curve. And the more we flatten the curve, the longer the virus takes to infect all the people it can infect. So under a lockdown, the epidemic will go on for longer but at lower intensity, instead of happening over a short period of time in a burst.

The fact that a large number of people will ultimately be infected by the virus is not as terrible as it sounds. Most of us who get infected may not even realise that we are infected, and the symptoms that most people get are not more troublesome than those due to the ordinary flu. Only a small percentage of the population will get seriously sick and die (although in absolute terms this fraction translates to a large number in the Indian population). Even in Italy, the death toll of 19,468 on April 11 was less than .03% of the country's total population.

Flattening the curve allows maximum possible hospital care to be given to those who get seriously sick. By curtailing the movement and interactions of and among people, lockdowns temporarily slow the infection's dispersal through the population. When the lockdown is lifted, the infections will start again, though at a slower rate than before. In effect, the requisite herd immunity is acquired in two smaller chunks instead of in one steep spike.
Lockdown schedule has to be supported by data
Now, the curve can be flattened only if we schedule the lockdown properly with realistic data specific to India. Simply applying it as soon as possible does not guarantee positive outcomes, much less when driven by the conviction that lockdowns can stop epidemics in their tracks. In fact, some epidemiological models indicate that if a lockdown is applied too early, it may not be able to flatten the curve at all, and may postpone the peak into the future.

Specifically, a lockdown can be considered to be too early if it kicks in long before the epidemic's peak. The more populated a country, the longer it will take to reach its peak. Now, it's important to remember that ultimately, it is not the health system but the human body that fights the virus. So an early lockdown effectively means a less-than-healthy population will be facing the epidemic when the virus resurges at the end of the lockdown; our bodies will have been weakened both physically and mentally due to the concomitant economic and social downturn.

Scientific analysis of reliable data is essential to understand how the epidemic is playing out within the country. Without reliable data, it is impossible to determine what the epidemic trajectory for India is like and where we are on the trajectory at any given point.

Indeed, there is a strong chance India is experiencing a milder epidemic than are countries in the West. This is not wishful thinking: a lot of countries around us, like Pakistan, Singapore, Thailand, Malaysia and the Philippines, seemingly have flat growth curves, at least at present; most of Africa does not seem to have even entered the epidemic stage. Scientists are trying to understand why in different ways but the absence of an explanation shouldn't consign this possibility to the dumps. This said, India has tested very little, so what data we have available does not suffice to satisfy ourselves that we are indeed having a mild epidemic.

Computer simulations show that imposing a short lockdown closer to the peak could be more effective than an early lockdown of any duration. Locking down early implies that we divide the total number of possible infections into a tiny first chunk and a much larger second chunk.

We must quickly collect reliable data. It is not enough to find out how many people are getting sick and how many are dying. We need to know, for example, what percentage of our population has infections with no symptoms or symptoms so mild that they don't get reported. This can only be done by randomly testing the population with antibody-based testing kits, and using those test results to then estimate how close we as a country are to achieving herd immunity.

We must also consider whether we can achieve better results by strictly isolating the vulnerable population and practising physical-distancing instead of halting all economic activity. We must choose our strategies based on scientific knowledge and reliable data specific to India. Hopefully we will acquire the data we need soon, and from that perhaps glean the possibilities of even milder responses instead of persisting with a blanket lockdown with staggering economic and human costs.
Roschen Sasikumar is a retired scientist from CSIR-NIIST, Trivandrum.

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Coronavirus Pandemic: An Early Lockdown Is Not Always the Best Strategy - The Wire Science

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Daily wage labourers stand in a queue for free food at a construction site where activity has been halted due to the nationwide lockdown to slow the spreading of the coronavirus, in New Delhi, April 10, 2020. Photo: Reuters/Adnan Abidi. Intuitively, it feels true that the earlier we impose a lockdown, the more effectively we can contain the coronavirus pandemic.

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Significance

This is a phylogenetic network of SARS-CoV-2 genomes sampled from across the world. These genomes are closely related and under evolutionary selection in their human hosts, sometimes with parallel evolution events, that is, the same virus mutation emerges in two different human hosts. This makes character-based phylogenetic networks the method of choice for reconstructing their evolutionary paths and their ancestral genome in the human host. The network method has been used in around 10,000 phylogenetic studies of diverse organisms, and is mostly known for reconstructing the prehistoric population movements of humans and for ecological studies, but is less commonly employed in the field of virology.

Abstract

In a phylogenetic network analysis of 160 complete human severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) genomes, we find three central variants distinguished by amino acid changes, which we have named A, B, and C, with A being the ancestral type according to the bat outgroup coronavirus. The A and C types are found in significant proportions outside East Asia, that is, in Europeans and Americans. In contrast, the B type is the most common type in East Asia, and its ancestral genome appears not to have spread outside East Asia without first mutating into derived B types, pointing to founder effects or immunological or environmental resistance against this type outside Asia. The network faithfully traces routes of infections for documented coronavirus disease 2019 (COVID-19) cases, indicating that phylogenetic networks can likewise be successfully used to help trace undocumented COVID-19 infection sources, which can then be quarantined to prevent recurrent spread of the disease worldwide.

The search for human origins seemed to take a step forward with the publication of the global human mitochondrial DNA tree ( 1). It soon turned out, however, that the tree-building method did not facilitate an unambiguous interpretation of the data. This motivated the development, in the early 1990s, of phylogenetic network methods which are capable of enabling the visualization of a multitude of optimal trees ( 2, 3). This network approach, based on mitochondrial and Y chromosomal data, allowed us to reconstruct the prehistoric population movements which colonized the planet ( 4, 5). The phylogenetic network approach from 2003 onward then found application in the reconstruction of language prehistory ( 6). It is now timely to apply the phylogenetic network approach to virological data to explore how this method can contribute to an understanding of coronavirus evolution.

In early March 2020, the GISAID database ( https://www.gisaid.org/) contained a compilation of 253 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete and partial genomes contributed by clinicians and researchers from across the world since December 2019. To understand the evolution of this virus within humans, and to assist in tracing infection pathways and designing preventive strategies, we here present a phylogenetic network of 160 largely complete SARS-Cov-2 genomes ( Fig. 1).

Zhou et al. ( 7) recently reported a closely related bat coronavirus, with 96.2% sequence similarity to the human virus. We use this bat virus as an outgroup, resulting in the root of the network being placed in a cluster of lineages which we have labeled "A." Overall, the network, as expected in an ongoing outbreak, shows ancestral viral genomes existing alongside their newly mutated daughter genomes.

There are two subclusters of A which are distinguished by the synonymous mutation T29095C. In the T-allele subcluster, four Chinese individuals (from the southern coastal Chinese province of Guangdong) carry the ancestral genome, while three Japanese and two American patients differ from it by a number of mutations. These American patients are reported to have had a history of residence in the presumed source of the outbreak in Wuhan. The C-allele subcluster sports relatively long mutational branches and includes five individuals from Wuhan, two of which are represented in the ancestral node, and eight other East Asians from China and adjacent countries. It is noteworthy that nearly half (15/33) of the types in this subcluster, however, are found outside East Asia, mainly in the United States and Australia.

Two derived network nodes are striking in terms of the number of individuals included in the nodal type and in mutational branches radiating from these nodes. We have labeled these phylogenetic clusters B and C.

For type B, all but 19 of the 93 type B genomes were sampled in Wuhan ( n = 22), in other parts of eastern China ( n = 31), and, sporadically, in adjacent Asian countries ( n = 21). Outside of East Asia, 10 B-types were found in viral genomes from the United States and Canada, one in Mexico, four in France, two in Germany, and one each in Italy and Australia. Node B is derived from A by two mutations: the synonymous mutation T8782C and the nonsynonymous mutation C28144T changing a leucine to a serine. Cluster B is striking with regard to mutational branch lengths: While the ancestral B type is monopolized (26/26 genomes) by East Asians, every single (19/19) B-type genome outside of Asia has evolved mutations. This phenomenon does not appear to be due to the month-long time lag and concomitant mutation rate acting on the viral genome before it spread outside of China ( Dataset S1, Supplementary Table 2). A complex founder scenario is one possibility, and a different explanation worth considering is that the ancestral Wuhan B-type virus is immunologically or environmentally adapted to a large section of the East Asian population, and may need to mutate to overcome resistance outside East Asia.

Type C differs from its parent type B by the nonsynonymous mutation G26144T which changes a glycine to a valine. In the dataset, this is the major European type ( n = 11), with representatives in France, Italy, Sweden, and England, and in California and Brazil. It is absent in the mainland Chinese sample, but evident in Singapore ( n = 5) and also found in Hong Kong, Taiwan, and South Korea.

One practical application of the phylogenetic network is to reconstruct infection paths where they are unknown and pose a public health risk. The following cases where the infection history is well documented may serve as illustrations (SI Appendix). On 25 February 2020, the first Brazilian was reported to have been infected following a visit to Italy, and the network algorithm reflects this with a mutational link between an Italian and his Brazilian viral genome in cluster C (SI Appendix, Fig. S1). In another case, a man from Ontario had traveled from Wuhan in central China to Guangdong in southern China and then returned to Canada, where he fell ill and was conclusively diagnosed with coronavirus disease 2019 (COVID-19) on 27 January 2020. In the phylogenetic network (SI Appendix, Fig. S2), his virus genome branches from a reconstructed ancestral node, with derived virus variants in Foshan and Shenzhen (both in Guangdong province), in agreement with his travel history. His virus genome now coexists with those of other infected North Americans (one Canadian and two Californians) who evidently share a common viral genealogy. The case of the single Mexican viral genome in the network is a documented infection diagnosed on 28 February 2020 in a Mexican traveler to Italy. Not only does the network confirm the Italian origin of the Mexican virus (SI Appendix, Fig. S3), but it also implies that this Italian virus derives from the first documented German infection on 27 January 2020 in an employee working for the Webasto company in Munich, who, in turn, had contracted the infection from a Chinese colleague in Shanghai who had received a visit by her parents from Wuhan. This viral journey from Wuhan to Mexico, lasting a month, is documented by 10 mutations in the phylogenetic network.

This viral network is a snapshot of the early stages of an epidemic before the phylogeny becomes obscured by subsequent migration and mutation. The question may be asked whether the rooting of the viral evolution can be achieved at this early stage by using the oldest available sampled genome as a root. As SI Appendix, Fig. S4 shows, however, the first virus genome that was sampled on 24 December 2019 already is distant from the root type according to the bat coronavirus outgroup rooting.

The described core mutations have been confirmed by a variety of contributing laboratories and sequencing platforms and can be considered reliable. The phylogeographic patterns in the network are potentially affected by distinctive migratory histories, founder events, and sample size. Nevertheless, it would be prudent to consider the possibility that mutational variants might modulate the clinical presentation and spread of the disease. The phylogenetic classification provided here may be used to rule out or confirm such effects when evaluating clinical and epidemiological outcomes of SARS-CoV-2 infection, and when designing treatment and, eventually, vaccines.

Materials and Methods

The Global Initiative on Sharing Avian Influenza Data (GISAID) was founded in 2006, and, since 2010, has been hosted by the German Federal Ministry of Food, Agriculture and Consumer Protection. GISAID has also become a coronavirus repository since December 2019. As of 4 March 2020, the cutoff point for our phylogenetic analysis, the GISAID database ( https://www.gisaid.org/) had compiled 254 coronavirus genomes, isolated from 244 humans, nine Chinese pangolins, and one bat Rhinolophus affinis (BatCoVRaTG13 from Yunnan Province, China). The sequences have been deposited by 82 laboratories listed in Dataset S1, Supplementary Table 1. Although SARS-CoV-2 is an RNA virus, the deposited sequences, by convention, are in DNA format. Our initial alignment confirmed an earlier report by Zhou et al. ( 7) that the pangolin coronavirus sequences are poorly conserved with respect to the human SARS-CoV-2 virus, while the bat coronavirus yielded a sequence similarity of 96.2% in our analysis, in agreement with the 96.2% published by Zhou et al. We discarded partial sequences, and used only the most complete genomes that we aligned to the full reference genome by Wu et al. ( 8) comprising 29,903 nucleotides. Finally, to ensure comparability, we truncated the flanks of all sequences to the consensus range 56 to 29,797, with nucleotide position numbering according to the Wuhan 1 reference sequence ( 8). The laboratory codes of the resulting 160 sequences and the bat coronavirus sequences are listed in Dataset S1, Supplementary Table 2 (Coronavirus Isolate Labels).

The 160 human coronavirus sequences comprised exactly 100 different types. We added to the data the bat coronavirus as an outgroup to determine the root within the phylogeny. Phylogenetic network analyses were performed with the Network 5011CS package, which includes, among other algorithms, the median joining network algorithm ( 3) and a Steiner tree algorithm to identify most-parsimonious trees within complex networks ( 9). We coded gaps of adjacent nucleotides as single deletion events (these deletions being rare, up to 24 nucleotides long, and mostly in the amino acid reading frame) and ran the data with the epsilon parameter set to zero, and performed an exploratory run by setting the epsilon parameter to 10. Both settings yielded a low-complexity network. The Steiner tree algorithm was then run on both networks and provided the identical result that the most-parsimonious trees within the network were of length 229 mutations. The structures of both networks were very similar, with the epsilon 10 setting providing an additional rectangle between the A and B clusters. The network output was annotated using the Network Publisher option to indicate geographic regions, sample collection times, and cluster nomenclature.

Acknowledgments

We gratefully acknowledge the authors and originating and submitting laboratories of the sequences from GISAID's EpiFlu(TM) Database on which this research is based. We are grateful to Trevor Bedford (GISAID) for providing instructions and advice on the database. A table of the contributors is available in Dataset S1, Supplementary Table 1. We thank Arne Röhl for assessing the network.

Footnotes

Author contributions: P.F. and M.F. performed research; P.F., L.F., and M.F. analyzed data; P.F. and M.F. performed statistical analyses; P.F., C.R., and M.F. wrote the paper; and C.R. wrote the Introduction.

Reviewers: T.K., Katholieke Universiteit Leuven; and C.S., University Medical Center Hamburg-Eppendorf.

The authors declare no competing interest.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2004999117/-/DCSupplemental.

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Phylogenetic network analysis of SARS-CoV-2 genomes

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This is a phylogenetic network of SARS-CoV-2 genomes sampled from across the world. These genomes are closely related and under evolutionary selection in their human hosts, sometimes with parallel evolution events, that is, the same virus mutation emerges in two different human hosts.

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Taking a blood sample as part of random sampling for antibodies to the coronavirus.

It was the first large Western democracy to contain the spread of the coronavirus and is now the first to methodically go about reopening its economy. Others are watching.

Taking a blood sample as part of random sampling for antibodies to the coronavirus. Credit...

BERLIN - Felix Germann was not expecting anyone when his doorbell rang last week. Outside was a doctor who looked like she had just stepped out of an operating theater, green scrubs, face mask and all - and a policeman.

"I didn't do it!" Mr. Germann said, throwing up his hands, and everybody laughed.

The unusual visitors had come with an unusual proposal: Would he allow them to test his blood for Covid-19 antibodies? Every month? For a year? Starting next week?

He would be helping to further the science that would ultimately allow for a controlled lifting of social and economic restrictions and save lives.

"Of course I said yes," said Mr. Germann, a 41-year-old project manager at a media company. "I want to help. This is a collective crisis. The government is doing what it can. Everyone needs to do their bit."

With that, Mr. Germann and his girlfriend joined 3,000 households chosen at random in Munich for an ambitious study whose central aim is to understand how many people - even those with no symptoms - have already had the virus, a key variable to make decisions about public life in a pandemic.

The study is part of an aggressive approach to combat the virus in a comprehensive way that has made Germany a leader among Western nations figuring out how to control the contagion while returning to something resembling normal life.

Other nations, including the United States, are still struggling to test for infections. But Germany is doing that and more. It is aiming to sample the entire population for antibodies in coming months, hoping to gain valuable insight into how deeply the virus has penetrated the society at large, how deadly it really is, and whether immunity might be developing.

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Felix Germann and his partner, Philomena Maul, receiving a team carrying out random testing for antibodies in Munich.

The government hopes to use the findings to unravel a riddle that will allow Germany to move securely into the next phase of the pandemic: Which of the far-reaching social and economic restrictions that have slowed the virus are most effective and which can be safely lifted?

The same questions are being asked around the world. Other countries like Iceland and South Korea have tested broadly for infections, or combined testing with digital tracking to undercut the spread of the virus.

In hard-hit Italy, antibody tests - and the potential of "immunity licenses" - have lingered over a national debate over how and when to reopen the country. Regional presidents have turned to serological tests as a way to better chart infections but also to get a sense of which workers might have the desired antibodies to possibly provide protection and return to work.

But even the best laid plans can go awry. Singapore took extensive measures to stop the virus, and appeared to have succeeded, only to have the virus intensify.

In the United States, President Trump is in a hurry to restart the economy in an election year, but experts warn that much wider testing is needed to open societies safely.

Both Britain and the United States, where some of the first tests were flawed, virtually forfeited the notion of widespread testing early in their outbreaks and have since had to ration tests in places as they scramble to catch up. In Italy, one of the worst hit countries in the world, the central government and regional leaders sparred over how widely to test.

Germany, which produces most of its own high-quality test kits, is already testing on a greater scale than most - 120,000 a day and growing in a nation of 83 million.

Chancellor Angela Merkel, a trained scientist, said this week that the aim was nothing less than tracing "every infection chain."

That high level of testing has helped her country slow the spread of the virus and keep the number of deaths relatively low. More people in Germany now recover from the virus every day than are infected by it. Every 10 people infected with the virus now pass it to seven others - a sharp decline in the infection rate for a virus that has spread exponentially.

Even so, Ms. Merkel, too, has had her stumbles in dealing with the virus.

Germany has been criticized for failing to offer forceful leadership to the European Union at a moment of profound crisis. The generosity and solidarity on such striking display inside of Europe's largest and richest economy have been missing in Germany's response to poorer European nations in the south, which were hit hardest by the virus.

At home, however, the chancellor's mixture of calm reassurance and clear-eyed realism - as well as her ability to understand the science and explain it to citizens - has been widely praised and encouraged Germans to follow social distancing rules. Her approval ratings are now higher than 80 percent.

That broad confidence in government has given Germany a tremendous advantage. It is much of the reason a knock on the door by a police officer and strangers dressed like aliens asking for blood can engender good will rather than alarm, even in a country where past authoritarian governments have left citizens protective of their privacy.

The Munich antibody study, run by the Division of Infectious Diseases and Tropical Medicine at Munich University Hospital, and cofinanced by the government of the state of Bavaria, is the biggest of several regional studies being rolled out in various corners of Germany. Still, scientists caution that there is no proof yet that the detection of antibodies signals effective immunity and even if it does, it is not known how long that immunity might last.

Nationally, the Robert Koch Institute, the government's central scientific institution in the field of biomedicine, is testing 5,000 samples from blood banks across the country every two weeks and 2,000 people in four hot spots who are farther along in the cycle of the disease.

Its most ambitious project, aiming to test a nationwide random sample of 15,000 people across the country, is scheduled to begin next month.

"In the free world, Germany is the first country looking into the future," said Prof. Michael Hoelscher, who heads up the Munich study, noting that a number of countries had already asked him for the protocol to be able to replicate it. "We are leading the thinking of what to do next."

Mr. Hoelscher was co-author of what has become a widely influential research paper about how the virus can be transmitted before someone develops symptoms.

"There's no doubt after reading this paper that asymptomatic transmission is occurring," Dr. Anthony Fauci, director of the National Institute for Allergy and Infectious Diseases in the United States, told CNN on Feb. 1, three days after the paper was published. "This study lays the question to rest."

Asymptomatic transmission is what has made containment so difficult because a large number of infections are not detected.

Measuring the number of hidden infections and getting a sense of the true scale of the disease is key to fine-tuning the gradual loosening of restrictions and minimizing income loss and social isolation, scientists say.

"We will have a better idea of the number of undetected infections once we have done these representative studies," said Lothar Wieler, president of the Robert Koch Institute for infectious diseases, which is conducting a number of the antibody tests. "A lot is being done to measure well."

Some interim results have already come out.

In Gangelt, a small town of about 12,000 in northwest Germany, tests of a first group of 500 residents found that 14 percent had antibodies to the virus. Another 2 percent tested positive for the coronavirus, raising hopes that about 15 percent of the local population may already have some degree of immunity.

"The process toward reaching herd immunity has begun," Prof. Hendrik Streeck, director of the Institute of Virology at the University Hospital Bonn, who is leading the study, said in an interim report.

And even if 15 percent of Gangelt has some degree of immunity, levels of immunity are almost certain to be lower elsewhere in the country.

Gangelt was hit early and exceptionally hard by the virus following a carnival event in mid-February that acted as a super spreader. But it may hold valuable insights for places that lag behind as the pandemic runs its course.

The mortality rate in the town, for example, turned out to be 0.37 percent, much lower than the national rate of 3 percent which is calculated based only on detected infections.

The Munich study is expected to be more nuanced in its findings because it follows participants like Mr. Germann for a whole year. In addition to regular blood tests, there will be questions about everything from mental health to income loss.

"We are at a crossroads," said Mr. Hoelscher, the professor. "Are we going the route of loosening more and increasing immunity in the summer to slow the spread of this in the winter and gain more freedom to live public life? Or are we going to try to minimize transmissions until we have a vaccine?" he asked.

"This is a question for politicians, not for scientists," he added. "But politicians need the data to make an informed risk assessment."

Mr. Hoelscher got the idea for the antibody study in the shower. It was March 19, the day before the state of Bavaria announced its lockdown.

"I thought to myself if we're going into lockdown, we need to start working on an exit strategy now," he said.

The next day, he said he wrote a short pitch to the Bavarian government. Six hours later, he had the green light. It took another three weeks until the test kits had arrived, a new lab was opened and teams of medics started fanning out across the city.

Six days after they first rang his doorbell, a doctor and two medical students came back to Mr. Germann's apartment, household number 420 out of 3,000.

They put on disposable protection suits, gloves and goggles and one of them sat down on a plastic stool they had brought along to take a small vial of his blood. Then they removed and bagged their suits, disinfected the stool and any surface they had touched and left. It took all of 10 minutes.

"I was like, wow, it was a perfect choreography," said Mr. Germann. "It's impressive to think they have teams doing this all across the city. And we're only like one month into this."

An interim result of the study could be released as early as June.

Mr. Germann will get his first results already next week. He is curious.

"You kind of wonder, was that last cold I had corona?"

Christopher F. Schuetze contributed reporting from Berlin.

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With Broad, Random Tests for Antibodies, Germany Seeks Path Out of Lockdown

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It was the first large Western democracy to contain the spread of the coronavirus and is now the first to methodically go about reopening its economy. Others are watching. Taking a blood sample as part of random sampling for antibodies to the coronavirus. Credit...

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By Jenny Gross and Mariel Padilla

When is an epidemic considered a pandemic, and what is the difference? What do health officials mean when they recommend "self-quarantining" or "social distancing"?

As the coronavirus spreads around the world, new terms are entering the lexicon - and we're here to help.

Here's a guide to the words and phrases you need to know to keep informed of the latest developments.

Pandemic
On Wednesday, the World Health Organization declared the coronavirus outbreak a pandemic after it spread across six continents and more than 100 countries. A pandemic is the worldwide spread of a new disease that affects large numbers of people. The WHO had avoided using the word before Wednesday because it didn't want to give the impression that the disease was unstoppable.

"Pandemic is not a word to use lightly or carelessly," Dr. Tedros Adhanom Ghebreyesus, the director general of the WHO, said at a news conference.

Epidemic
An epidemic is a regional outbreak of an illness that spreads unexpectedly, according to the WHO. The Centers for Disease Control and Prevention defines it as an increase, often sudden, in the number of cases of a disease above normal expectations in a set population.

Also read: Arsenal manager Mikel Arteta, Chelsea winger Callum Hudson-Odoi test positive for Covid-19

The technical name for the coronavirus is SARS-CoV-2. The respiratory disease it causes has been named the "coronavirus disease 2019," or COVID-19.

Coronaviruses are named for the crown-like spikes that protrude from their surfaces, resembling the sun's corona. Coronaviruses are among a large number of viruses that are common in people and many animals. The new virus, first detected in China, is believed to have originated in bats.

While antibiotics don't work against viruses, researchers are testing drugs that could disrupt viral proteins and stop the infection.

State of emergency
A state of emergency can be declared during natural disasters, epidemics and other public health emergencies. Declaring a state of emergency, as more than a dozen states - including New York, New Jersey and Michigan - have done, gives government officials the authority to take extra measures to protect the public, such as suspending regulations or reallocating funds to mitigate the spread of a disease.

Incubation
The incubation period is the time it takes for symptoms to appear after a person is infected. This time can be critical for prevention and control, and it allows health officials to quarantine or observe people who may have been exposed to the virus.

The new coronavirus has an incubation period of two to 14 days, according to the CDC, with symptoms appearing about five days after infection in most cases.

During the incubation period, people may shed infectious virus particles before they exhibit symptoms, making it almost impossible to identify and isolate people who have the virus.

Social distancing
The virus can easily spread in dense places - in a packed subway car, for example, or at a rally or concert.

Social distancing refers to measures that are taken to increase the physical space between people to slow the spread of the virus. Examples include working from home, school closures and the postponement or cancellation of mass gatherings, such as the South by Southwest music, technology and film conference.

By maintaining a distance of 6 feet from others when possible, people may limit the spread of the virus.

Self-quarantine
This is key to keeping the virus from spreading, along with measures like social distancing, frequent hand-washing and wearing masks.

While isolation refers to separating sick people from people who aren't sick, quarantine refers to the separation and restriction of movement of people who were exposed to the virus to see if they become sick.

Who should self-quarantine? If you've left an area with widespread or continuing transmission, including China, Iran, Italy and South Korea, you should self-quarantine at home for a period of 14 days from the time you left, according to the CDC.

While in quarantine, you shouldn't receive any visitors and must stay 3 to 6 feet from others at all times.

According to the CDC, once someone has been in isolation for 14 days and hasn't become ill, he or she is not considered to be a risk to other people.

Fatality rate
The case fatality rate is the number of deaths divided by the total number of confirmed cases. Eventually, scientists hope to have a more comprehensive number called the infection fatality rate, which includes everyone who was infected with the virus.

The WHO estimates the fatality rate of the new coronavirus to be about 3%, based on current data, but experts suggest 1% is more realistic.

R-naught
The R-naught, or R0, is a virus's basic reproductive number - an epidemiologic metric used to describe the contagiousness of infectious agents.

At its simplest, the basic reproductive number can show us how worried we should be about infection, according to Dr. Adam Kucharski, a mathematician at the London School of Hygiene and Tropical Medicine. If the R0 is above one, each case is expected to infect at least one other person on average, and the virus is likely to keep spreading. If it's less than one, a group of infected people are less likely to spread the infection.

Research is still in its early stages, but some estimates suggest that each person with the new coronavirus could infect between two and four people.

Containment
The virus's high transmission rate has made it difficult to effectively contain the outbreak. Containment refers to the use of any available tools to mitigate the spread of a disease, said Adam Ratner, the director of the division of pediatric infectious diseases at NYU Langone Health.

Early on, the Trump administration sought to slow the spread of the virus by barring entry into the United States by any foreign nationals who had traveled to China in the previous 14 days, excluding the immediate family members of American citizens or permanent residents. While that measure may have bought the government time to prepare, the administration made key missteps in its efforts to make widespread testing available in the early days of the outbreak, when containment would have been easier.

Ratner said the coronavirus is particularly hard to contain because it is "reasonably transmissible" and some people who don't have a lot of symptoms can still pass the virus to others. "That's been part of the problem," he said, "but it also points to the fact to how interconnected we all are and how quickly this thing spread from Asia to the rest of the world."

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How deadly is coronavirus? From COVID-19 to R-naught, here are all the terms that you need to know

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By Jenny Gross and Mariel Padilla When is an epidemic considered a pandemic, and what is the difference? What do health officials mean when they recommend "self-quarantining" or "social distancing"? As the coronavirus spreads around the world, new terms are entering the lexicon - and we're here to help.

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Covid-19: 1 patient can infect 406 people in 30 days, finds ICMR study

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With preventive measures in place, the possibility of the infection can be reduced to an average of two and a half persons per patient in a month, a top offical said

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Coronavirus Pandemic Is Wake-Up Call to Reinvent the State - Bloomberg

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The vaccines were produced by Wuhan Institute of Biological Products Co. Ltd of Sinopharm and Sinovac Research and Development Co. Ltd respectively.

An academic from China Academy of Engineering who was involved in the development of the vaccine, Wang Junzhi, said, "We are taking the lead in developing COVID-19 vaccines in a global perspective."

He also added that he believes that several factors contributed to his team's achievement; namely, starting early and with an accurate direction, the fact that it was approached from a scientific perspective and that collaboration on all parts was very much prevalent.

This vaccine is seen as one of the most powerful tools to combat the COVID-19 pandemic.

Indeed, China has been determined to accelerate the pace of vaccine developments based on rational judgment and structured planning with the premise of safety assurance, as far back as January this year. On January 21 st, China's Ministry of Science and Technology (MOST) established a group of experts who would contribute to epidemic prevention and work out measure which could be taken to contain and eradicate it.

This team was comprised of 14 experts and was led by an academic from the China Academy of Engineering, Zhong Nanshan. This group devised a plan to tackle vaccine development based on five directions which included: inactivated vaccines, nucleic acid vaccines, genetic engineering subunit vaccines, vaccines using attenuated influenza virus as vectors and adenovirus vector vaccines.

Following this, eight teams were established in an effort to initiate greater collaboration on this mission whereby detailed and accurate plans were followed. All the five methods were to be worked on simultaneously until they found the most suitable means of tackling the virus.

Thanks to an academic from China's Academy of Engineering, Chen Wei, who possessed the necessary knowledge about vaccine development due to her previous experience, her team was able to reach a breakthrough first. She suggested that COVID-19 is still a coronavirus despite its variation which meant that mutual target antigen, pathogenesis and receptor would be identified quickly. Bioinformatics and the use of big data would help identify them and make great strides in solving this humanitarian crisis.

Chen Wei's team worked on developing an adenovirus vector vaccine, drawing on previous experience with the last epidemic crisis- Ebola. The team got their recombinant COVID-19 vaccine approved for clinical trial on March 17 th and was subsequently used for a phase I clinical trial in Wuhan on 108 subjects by April 2 nd. A week later, the phase II clinical trial was underway, featuring an even larger amount of subjects as well as placebo control groups.

At the same time, teams who were focusing on other directions have also seen some progress in their vaccine developments.

The head of the Department of Science and Technology of the Ministry of Education, Lei Chaozi outlined that there have been significant developments in areas such as attenuated influenza vector, nucleic acid and recombinant protein vaccines.

She mentioned that research on the safety and validity of experimental animals for attenuated influenza vector vaccine is underway. Pre-clinical trial research for vaccine candidates is ongoing and for this direction, they expect to apply for clinical trials by the end of April.

Adding that experiments were being carried out on lab rats and rabbits in this direction and the mass production of this vaccine has been achieved and is of the highest quality and purity, whereas the nucleic acid vaccine segment is still a fairly new field that is yet to be explored by the world as no such vaccine have been introduced to the market.

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China announces approved COVID-19 vaccines

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The vaccines were produced by Wuhan Institute of Biological Products Co. Ltd of Sinopharm and Sinovac Research and Development Co. Ltd respectively. An academic from China Academy of Engineering who was involved in the development of the vaccine, Wang Junzhi, said, "We are taking the lead in developing COVID-19 vaccines in a global perspective."

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Is the Virus on My Clothes? My Shoes? My Hair? My Newspaper? (Published 2020)

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We asked the experts to answer questions about all the places coronavirus lurks (or doesn’t). You’ll feel better after reading this.

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Preliminary results from government lab experiments show that the coronavirus does not survive long in high temperatures and high humidity, and is quickly destroyed by sunlight, providing evidence from controlled tests of what scientists believed - but had not yet proved - to be true.

A briefing on the preliminary results, marked for official use only and obtained by Yahoo News, offers hope that summertime may offer conditions less hospitable for the virus, though experts caution it will by no means eliminate, or even necessarily decrease, new cases of COVID-19, the disease caused by the coronavirus. The results, however, do add an important piece of knowledge that the White House's science advisers have been seeking as they scramble to respond to the spreading pandemic.

The study found that the risk of "transmission from surfaces outdoors is lower during daylight" and under higher temperature and humidity conditions. "Sunlight destroys the virus quickly," reads the briefing.

While that may provide some good news about the outlook for outdoor activities, the Department of Homeland Security briefing on the results cautions that enclosed areas with low humidity, such as airplane cabins, "may require additional care to minimize risk of transmission."

In a statement to Yahoo News, the DHS declined to answer questions about the findings and strongly cautioned against drawing any conclusions based on unpublished data.

"The department is dedicated to the fight against COVID-19, and the health and safety of the American people is its top priority. As policy, the department does not comment on allegedly leaked documents," the DHS said in a statement. "It would be irresponsible to speculate, draw conclusions, or to inadvertently try to influence the public based upon a document that has not yet been peer-reviewed or subjected to the rigorous scientific validation approach."

The results are contained in a briefing by the DHS science and technology directorate, which describes experiments conducted by the National Biodefense Analysis and Countermeasures Center, a lab created after the 9/11 terrorist attacks to address biological threats.

While the DHS describes the results as preliminary, they may eventually make their way into specific recommendations. "Outdoor daytime environments are lower risk for transmission," the briefing states.

Simulated sunlight "rapidly killed the virus in aerosols," the briefing says, while without that treatment, "no significant loss of virus was detected in 60 minutes."

The tests were performed on viral particles suspended in saliva. They were done indoors in environments meant to mimic various weather conditions.

While the results of these tests have not been previously made public, Harvey Fineberg, head of the National Academies Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats, broadly described plans to conduct the experiments in an April 7 letter to the White House.

In that letter, addressed to President Trump's top science adviser Kelvin Droegemeier, Fineberg wrote that the DHS lab "is well suited for the kinds of studies they have planned, and the scope and relevance are noteworthy. In particular, they plan to create simulated infected body fluids, including saliva and lower respiratory secretions."

Droegemeier's office did not respond to a request for comment on whether it has received the latest results from the DHS. The National Academies also did not respond to a request for comment.

While the lab results are new, scientists for many weeks have predicted, based on available data on the disease's spread, that warmer, wetter climates would be less hospitable to the spread of the coronavirus. An early analysis by scientists observed that the virus was spreading more slowly in countries with warmer climates.

"We are not saying that at higher temperatures, the virus will suddenly go away and everything would be fine and you are going out," Qasim Bukhari, a computational scientist at MIT and a co-author of the analysis, told Yahoo News in an interview. "No, we are not saying it. We are just seeing that there is a temperature- and humidity-related dependency, but I think many people now have started to realize this."

Bukhari said that since he and his colleagues published that analysis, the numbers on the coronavirus's spread continue to support their contention. "They are doing a lot of tests now in India. Also, when you look at the numbers in Pakistan it's the same. There are more than 5,000 cases in Pakistan right now," he said. "But the increase is not as rapid as you see in other countries."

The question of the effects of sunlight and heat on the coronavirus has been particularly fraught, because there has been a tendency to misinterpret the relationship between good weather and disease spread. Early on, some politicians tried to encourage people to go outside, including to beaches, arguing that sunlight would kill the virus. The problem, however, is that without widespread immunity, people can still transmit the coronavirus to others, even in warm weather.

The real question now, Bukhari said, is whether enough people have already been infected that the summer temperatures won't prevent continued transmission.

"So let's say 50 percent of the population is already infected, and then those temperatures arrive and then those humidity levels arrive, then what difference can those temperatures and humidity levels be? Probably none. That's the thing."

While the new lab results are important, the science behind how sunlight kills the virus is fairly well established, says Arthur Anderson, former director of the Office of Human Use and Ethics at the United States Army Medical Research Institute of Infectious Diseases at Fort Detrick, Md.

"[Ultraviolet] light breaks DNA into fragments. If the virus is floating around in the air and there's bright sunlight, the UV component in sunlight will break the DNA or the RNA into pieces," he told Yahoo News.

Infectious disease expert Dr. Anthony Fauci, who has become the leading face of the White House response, has provided cautious statements about what the summer months might mean for the coronavirus, saying recently, "It's almost certainly going to go down a bit." He has stopped far short, however, of saying that good weather alone would have an impact.

Yet the lab results may ultimately provide at least some basis for optimism.

"Does this give a little more hope about the virus potentially decreasing?" said Dr. Kavita Patel, a Yahoo medical contributor and nonresident fellow at the Brookings Institution. "Yes. I would say even Dr. Fauci has alluded to that."

Colds and flus don't disappear in the summer, even if they are less common, Patel noted. "We do have cases of the flu in the summer," she said. "That's why all of us in medicine are being a little more guarded."

The lab's work was done in a controlled environment, according to the DHS briefing, and tested how long the coronavirus survives on stainless steel in a droplet of saliva from a cough or sneeze under conditions related to temperature, humidity and sunlight. The lab is now doing additional testing, such as experimenting with low-tech techniques for sterilization of protective equipment, which would include using rice cookers, clothes steamers and electric pressure cookers.

The National Biodefense Analysis and Countermeasures Center, which conducted the experiments, has traditionally kept a low profile because of its classified work on biological warfare defense and bioterrorism. Fineberg, in his letter to the White House, did not go into detail on the planned experiments, noting that the lab shares its findings with the interagency task force on the coronavirus.

Anderson, the former Fort Detrick scientist, said it's unclear why the information would be marked for official use only. "I have to say I don't know. I think if they have something that is critically important, it would get published, but it would not be available in the acute time frame of the emergency," he said.

It is also unclear whether the center intends to publish in a peer-reviewed journal or choose some other route for making its results known. Patel said she could understand government concerns about releasing preliminary results, but in general she leans toward openness.

"As a clinical doctor, we want to learn as fast as possible anything that works clinically. You want to be able in the first line to say: This is preliminary, with caveats. But why hold back the information?" she said.

It may be that the government wants to control how the message is released, she suggested. "I would say in a global pandemic, that's less of a priority."

_____
for the Read more: latest coronavirus news and updates. According to experts, people over 60 and those who are immunocompromised continue to be the most at risk. If you have questions, please refer to the and resource guides.

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Sunlight destroys virus quickly, new govt. tests find, but experts say pandemic could last through summer

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Preliminary results from government lab experiments show that the coronavirus does not survive long under high-temperature, high-humidity conditions, and is quickly destroyed by sunlight, providing evidence from controlled tests of what scientists believed - but had not yet proved - to be true.

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Chicago hospital treating severe Covid-19 patients with Gilead Sciences' antiviral medicine remdesivir in a closely watched clinical trial is seeing rapid recoveries in fever and respiratory symptoms, with nearly all patients discharged in less than a week, STAT has learned.

Remdesivir was one of the first medicines identified as having the potential to impact SARS-CoV-2, the novel coronavirus that causes Covid-19, in lab tests. The entire world has been waiting for results from Gilead's clinical trials, and positive results would likely lead to fast approvals by the Food and Drug Administration and other regulatory agencies. If safe and effective, it could become the first approved treatment against the disease.

The University of Chicago Medicine recruited 125 people with Covid-19 into Gilead's two Phase 3 clinical trials. Of those people, 113 had severe disease. All the patients have been treated with daily infusions of remdesivir.

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"The best news is that most of our patients have already been discharged, which is great. We've only had two patients perish," said Kathleen Mullane, the University of Chicago infectious disease specialist overseeing the remdesivir studies for the hospital.

Her comments were made this week during a video discussion about the trial results with other University of Chicago faculty members. The discussion was recorded and STAT obtained a copy of the video.

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The outcomes offer only a snapshot of remdesivir's effectiveness. The same trials are being run concurrently at other institutions, and it's impossible to determine the full study results with any certainty. Still, no other clinical data from the Gilead studies have been released to date, and excitement is high. Last month, President Trump touted the potential for remdesivir - as he has for many still-unproven treatments - and said it "seems to have a very good result."

In a statement Thursday, Gilead said: "What we can say at this stage is that we look forward to data from ongoing studies becoming available."

Gilead had said to expect results for its trial involving severe cases in April. Mullane said during her presentation that data for the first 400 patients in the study would be "locked" by Gilead Thursday, meaning that results could come any day.

Mullane, while encouraged by the University of Chicago data, made clear her own hesitancy about drawing too many conclusions.

"It's always hard," she said, because the severe trial doesn't include a placebo group for comparison. "But certainly when we start [the] drug, we see fever curves falling," she said. "Fever is now not a requirement for people to go on trial, we do see when patients do come in with high fevers, they do [reduce] quite quickly. We have seen people come off ventilators a day after starting therapy. So, in that realm, overall our patients have done very well."

She added: "Most of our patients are severe and most of them are leaving at six days, so that tells us duration of therapy doesn't have to be 10 days. We have very few that went out to 10 days, maybe three," she said.

Reached by STAT, Mullane confirmed the authenticity of the footage but declined to comment further. In a statement, the University of Chicago Medicine said "drawing any conclusions at this point is premature and scientifically unsound."

Asked about the data, Eric Topol, director of the Scripps Research Translational Institute, described them as "encouraging."

"The severely hit patients are at such high-risk of fatality. So if it's true that many of the 113 patients were in this category and were discharged, it's another positive signal that the drug has efficacy," he said, adding that it will be important to see more data from randomized controlled studies.

Gilead's severe Covid-19 study includes 2,400 participants from 152 different clinical trial sites all over the world. Its moderate Covid-19 study includes 1,600 patients in 169 different centers, also all over the world.

The trial is investigating five- and 10-day treatment courses of remdesivir. The primary goal is a statistical comparison of patient improvement between the two treatment arms. Improvement is measured using a seven-point numerical scale that encompasses death (at worst) and discharge from hospital (best outcome), with various degrees of supplemental oxygen and intubation in between.

The lack of a control arm in the study could make interpreting the results more challenging.

A lack of data has led to yo-yoing expectations for the drug. Two studies in China had enrollment suspended partway through because there were not enough patients available. A recent report of patients given the drug under a special program to make it available to those who are very ill generated both excitement and skepticism.

In scientific terms, all the data are anecdotal until the full trial reads out, meaning that they should not be used to draw final conclusions. But some of the anecdotes are dramatic.

Slawomir Michalak, a 57-year-old factory worker from a suburb west of Chicago, was among the participants in the Chicago study. One of his daughters started feeling ill in late March and was later diagnosed with mild Covid-19. Michalak, by contrast, came down with a high fever and reported shortness of breath and severe pain in his back.

"It felt like someone was punching me in the lungs," he told STAT.

At his wife's urging, Michalak went to the University of Chicago Medicine hospital on Friday, April 3. His fever had spiked to 104 and he was struggling to breath. At the hospital, he was given supplemental oxygen. He also agreed to participate in Gilead's severe Covid-19 clinical trial.

His first infusion of remdesivir was on Saturday, April 4. "My fever dropped almost immediately and I started to feel better," he said.

By his second dose on Sunday, Michalak said he was being weaned off oxygen. He received two more daily infusions of remdesivir and recovered enough to be discharged from the hospital on Tuesday, April 7.

"Remdesivir was a miracle," he said.

The world is waiting to find out if it is really so.

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Gilead data suggests coronavirus patients are responding to treatment

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Chicago hospital treating severe Covid-19 patients with Gilead Sciences' antiviral medicine remdesivir in a closely watched clinical trial is seeing rapid recoveries in fever and respiratory symptoms, with nearly all patients discharged in less than a week, STAT has learned.

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A researcher works on the development of a vaccine against the novel coronavirus in Belo Horizonte, Brazil, in March. (Douglas Magno/AFP/Getty)

NOBEL LAUREATE Peter Medawar once defined a virus as "a piece of bad news wrapped up in protein." He wrote in 1983 that "no virus is known to do good." The key to stopping the novel coronavirus is that no virus can multiply on its own. It must invade a living cell. All hopes rest on a drug, vaccine or other therapy to disrupt the virus attack or impede its replication machinery. This is complicated science, not the instant "game changer" that President Trump has touted in the unproven antimalarial drug hydroxychloroquine.

Traditionally, it takes years to develop, test and manufacture a vaccine; the one that worked in Congo against Ebola was under development for a decade. These hurdles haven't changed, although one factor giving science a head start is that the whole genome of the coronavirus was sequenced and shared rapidly by China. Also, a new process of preliminary research reports unleashed a torrent of open source information.

Full coverage of the coronavirus pandemic

What might save us? More than 70 vaccines are being researched. The Norway-based Coalition for Epidemic Preparedness Innovations, an international public-private collaboration started in 2017, has been funding a number of experimental projects. One of them, created by Moderna of Cambridge, Mass., and the Vaccine Research Center of the National Institute of Allergy and Infectious Diseases, is attempting to use synthesized genetic material, known as messenger RNA, that would help the body recognize the virus and target it, rather than the established method of using attenuated pathogens or protein particles from the real virus. The approach underscores the value of acquiring the whole genome sequence so early. Other vaccine development efforts are also delving into whether it is possible to manipulate genetic material to create an effective vaccine in a new way. Two companies are experimenting with taking a snippet of genetic code and entwining it with a harmless virus, hopefully spurring the body to produce antibodies that would go after a coronavirus invasion.

A second overall approach is to create antiviral drugs and other therapies that could interfere with the steps that the coronavirus takes to infect a cell or replicate inside it. Some are looking to see whether existing drugs or vaccines against other illnesses, already tested for safety, might be repurposed, such as the antiviral remdesivir, which Gilead Sciences has put into five clinical trials around the world. It didn't succeed in the 2019 Ebola outbreak, but in test-tube and animal studies earlier had shown some potency against other coronaviruses. Yet another approach would be to create entirely new drugs or therapies, such as using the plasma of recovered patients to provide the protective antibodies needed to help ward off the virus.

The Opinions section is looking for stories of how the coronavirus has affected people of all walks of life. Write to us.

The science is immensely challenging. But we can take heart knowing that so many creative, persistent and indefatigable researchers are working on more than 140 experimental drug treatments and vaccines, cooperating across company lines and national borders.

The Post's View: We all want to reopen the economy. But it won't be quick or easy.

Lawrence O. Gostin and Matthew M. Kavanagh: The WHO needs U.S. funding. Weakening it will undermine the global response.

Catherine Rampell: The covid-19 pandemic has revealed another area of critical government underinvestment

Michael Leonberger: Weathering the coronavirus pandemic with an anxiety disorder

Danielle Allen: The best way out of this pandemic is to massively scale up testing. Here's how to do it.

Coronavirus: What you need to read

The Washington Post is providing some coronavirus coverage free, including:
Updated April 15, 2020 Show More Show Less

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Opinion | The science is challenging. But we should be hopeful for a covid-19 vaccine or drug.

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NOBEL LAUREATE Peter Medawar once defined a virus as "a piece of bad news wrapped up in protein." He wrote in 1983 that "no virus is known to do good." The key to stopping the novel coronavirus is that no virus can multiply on its own. It must invade a living cell.

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On 12 March, a 33-year-old salesman disembarked from a flight from Dubai at an airport in southern India, feeling very sick.

He was suffering from the chills, dry cough and breathlessness.

Airport officials sent him to hospital in the city of Trivandrum in Kerala state, where they tested him for coronavirus.

Then they put him in an ambulance and sent him home to his village in Kasargod district, some 564 km (350 miles) away.

Chengala is a cluster of four wooded settlements where 66,000 people live. Most are engaged in farming paddy and vegetables.

Many others, like the young salesman, are among the more than two million people from Kerala who work outside the country, including in the Gulf states.

When the man reached Chengala, local village council members immediately reached out and the local public health centre took down his details.

They asked him to isolate himself from his wife and three children. So the man began living alone in a shed outside his house.

Six days later, his test came back as positive. By that time, he was already in isolation in his home. Later, he was taken to hospital, where he tested negative. More than a month later, the salesman is still living in isolation "just for safety".

"We were ready from the very beginning. We realised a storm was coming. So we began erecting our defences," Shahina Saleem, the president of the 23-member local village council, told me. These elected village councils are the lowest tier of governance in India.

Over the last month, Chengala has reported 22 cases of Covid-19 infection and quarantined more than 400 people. Twenty patients have recovered in hospital and returned home. More than 370 samples have been tested at hospitals some 8km away. Results usually arrive in 48 hours.

The local village council galvanised local health and community workers and opened a community kitchen to feed the people in isolation.

They have been providing free lunches for more than 1,200 people in the area - local residents and stranded migrant workers. Local health officers are making sure that villagers on medication get their pills on time.

Using a local helpline and two WhatsApp groups, the council encouraged local villagers to accommodate people who were in isolation and didn't have enough space for social distancing at home. Two-dozen families vacated floors and even homes for this. Everyone in isolation now has to observe a 28-day quarantine.

Kerala, many believe, has turned out to be a striking outlier in the battle against the virus in India. The world's second-most populous country has reported more than 9,750 cases and 377 deaths from the contagion so far.

In the beginning, the odds seemed to be stacked against the picturesque southern state, which is a major tourist location. In January, it reported the first Covid-19 case in India. The number of cases rose steadily. More than half a dozen states have since reported more infections.

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Kerala has porous borders, a large number of migrant workers, and a huge expatriate population who keep travelling back and forth and whose remittances oil the state's economy.

More than two months after the outbreak of the pandemic, Kerala has reported three deaths and more than 370 confirmed cases of the infection. More than 100,000 people remain in isolation, at home or in designated facilities.

Many believe Kerala has flattened the curve at a time when the infection is on the rise all over India.

To be sure, the state has been alert and vigilant. It imposed a lockdown a day before the nationwide one, on 25 March. It did rigorous contact tracing, using detailed "route maps" of people coming in from abroad. It set up Covid-19 care centres in all districts to accommodate outsiders who were stuck and had been advised to isolate.

Health workers supported people with special needs and the elderly living alone. Counsellors made more than 340,000 telephone calls to personnel working in affected areas to counsel them on how to handle stress.

It's not that Kerala tested aggressively. Testing was bound strictly by and limited to federal protocols. More than a dozen labs are testing 800 samples a day.

But, experts say, what really mattered in the end was Kerala's robust public health system, and a culture of thriving grassroots democracy with power devolving effectively to the village councils. This mainly helped in community outreach, rigorous contact tracing and mass quarantine. The Communist government released abundant information about the developments every day, analysts say.

"A strong game-changer was the decentralised health care system. And village councils took upon themselves to enforce and monitor mass quarantine with the consent of the people. The shutdown also helped," B Ekbal, a neurosurgeon and head of an expert panel advising the government on prevention of the virus, told me.

Economists like Jacob John believe that the devolution of power in Kerala - local government, community-driven village councils, vigilant municipalities - have helped the state tackle two consecutive floods and an outbreak of the vicious Nipah virus in the last three years.

The three-tier public health system, involving functioning government hospitals, is the result of a more than half-century long legacy of spending on healthcare. "Kerala," says Dr John, "has spent more on health and education than most Indian states."

Breathless media reports of Kerala "flattening the curve" could be premature, officials warn.

Like in the rest of India, much of the testing has been limited and delayed.

Mass screening with antibody tests has been delayed because about 100,000 kits which the state ordered haven't arrived yet.

Fresh cases haven't dried up yet. Kerala also "got lucky", as one doctor told me - the average age of infected people here is 37 years old, and the majority of them are Gulf returnees.

"It's not counter-intuitive. Some 70% of our Covid-19 patients have come from outside the country," says Dr Ekbal. This in a state where more than 12% of the population are over 60 years old.

Also, worryingly, Kerala has one of the highest rates of communicable diseases - one that spreads from one person to another - in India. A large number of people also suffer from diabetes, heart diseases, respiratory and liver diseases.

The summer monsoon rains, which begin in June, usually trigger a spike in diseases like influenza, dengue and scrub typhus. Fever is a common symptom in many of these diseases. "This can complicate diagnosis. To make sure we don't end up facing a fresh wave of infections during the rains, we have to very vigilant during the monsoon," says a doctor.

Such heightened vigilance - controlling inflows of people across the border and isolating suspects - will come at an economic cost. The government has worked out a painstakingly detailed plan for the phased opening up of the state when infections stop.

So far Kerala has stuck to the script and done it well it, say analysts. Cases have slowed down, recoveries are high and the mortality rate is low. It helped that it had a smaller population (33 million) than many other states and also a highly literate one.

"We have won the quarter-final," says Sreejith N Kumar, a doctor. "The semi-final would be a staggered easing up without a second wave of infection. And the final would be a return to normal life."

"Only then we can say we won the game."

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How India's Kerala state 'flattened the curve'

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On 12 March, a 33-year-old salesman disembarked from a flight from Dubai at an airport in southern India, feeling very sick. He was suffering from the chills, dry cough and breathlessness. Airport officials sent him to hospital in the city of Trivandrum in Kerala state, where they tested him for coronavirus.

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Coronavirus Outbreak: Invisibility of circular migrants in host states is at the heart of their exodus from urban centres - Firstpost

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" There are decades where nothing happens; and there are weeks where decades happen." Some quotes really age well. On that count, this quote by Vladimir Lenin sits right on top in current times. Since the start of the COVID-19 crisis, many issues have begun to emerge from their dormant existence and unfold dramatically to capture the public's mind.

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NOTE: Author Margaretta Colangelo is cofounder and managing partner at Deep Knowledge Group, the consortium behind the data presented in this story. Its subsidiary includes venture capital fund Deep Knowledge Ventures. COVID-19 Complexity Demands Sophisticated Analytics
A massive amount of data about the pandemic is generated every day. Although organizations such as WHO, CDC, Johns Hopkins University, and Worldometers are disseminating important statistics daily, the data is not analyzed in an efficient way to provide insights. The COVID-19 pandemic is a complex system involving biology, human behavior, companies, and governments, and it's influenced by healthcare, economics, governance, and geopolitics. Sophisticated analytical methods could help improve economic, societal, and geopolitical stability. Deep Knowledge Group has developed advanced analytical frameworks to analyze this data. The results are presented in the form of open source country rankings to help people and governments make informed decisions that maximize beneficial outcomes for humanity.

When the seriousness of the pandemic became clear, Deep Knowledge Group adapted its existing analytical frameworks, previously applied to complex domains such as as AI for Drug Discovery and NeuroTech, to the global COVID-19 pandemic landscape. A team of experts collected and analyzed data generated for 200 countries around the world. The results, based on deep analysis of 60 countries, was released today. To communicate the insights in a practical way, the analysts developed a ranking system. The rankings can be used as a tool for businesses and governments to aid in effective decision making and could assist response efforts in order to maximize health, stabilize economies, and help communities reopen for business. The analytical methodology will be adjusted over the next few months for advanced and qualitative assessment and AI may be used to analyze this data in the most efficient way.
Scoring and Methodology
The COVID-19 analytical frameworks have been designed to rapidly assess the changing situation in countries as they strive to mitigate the health and economic consequences of the virus. Big Data Analysis is applied to quantified and relevant parameters. By comparing them in tangible ways, they are able to serve as practical tools for decision makers. The analytics are fact-based and unbiased and can be accessed free of charge. Proprietary metrics and analytical techniques may be disclosed to relevant organizations and responsible governmental bodies.

The analysis revealed that some countries proved very effective at combating COVID-19 early on. These countries focused on early prevention by deploying quarantine measures before the number of confirmed cases surpassed 50,000, and using efficient methods for treating hospitalized patients. For example, China and Germany rapidly mobilizing emergency efforts early on to contain the virus and increase hospital capacity. They utilized technologies including AI, robotics, and big data analysis, in combination with medical treatment and healthcare management techniques structured in a sophisticated way.
Safety Ranking
Deep Knowledge Group's recent ​ COVID-19 Countries Health Safety Ranking​ has attracted significant public interest. The ranking was acknowledged by Israel's Prime Minister's Office, the Ministry of Foreign Affairs, and personally by Prime Minister Netanyahu.

Each country was ranked with a numerical score constructed using a well defined methodology. Each ranking is given a specific weighting, or importance factor, that is used as inputs in proprietary analytical equations. These mathematical ranking frameworks were developed over the past five years for use in highly complex and multidimensional industries and domains including the AI for drug discovery sector. The frameworks have been designed to rapidly and adaptively evaluate the situation in countries as they work to mitigate the health and economic consequences of the virus. In addition to updating the country rankings weekly, Deep Knowledge Group plans to periodically release new frameworks that rank countries in additional areas such as economic vulnerability, geopolitical risk, and possible asymmetric benefits that may result from the crisis.

The COVID-19 Safety Ranking Frameworkconducts benchmarking to determine levels of health and safety for each country during the pandemic. Data for over 200 countries was analyzed and sixty countries were ultimately included in the rankings. The countries were evaluated using 24 specific parameters in 4 distinct categories: Quarantine Efficiency, Government Management Efficiency, Monitoring and Detection, and Emergency Treatment Readiness. The Safety and Risk Rankings take into account protection from COVID infection, mortality and negative patient outcomes, metrics on quarantining and infection monitoring, detection, and management, and safety and stability in the broadest sense, including protection from extreme negative outcomes as a result of the pandemic beyond health. Countries that are unable to neutralize this pandemic could trigger a chain of events leading to negative outcomes for entire nations, as well as their geographic and economic neighbors. We saw such a scenario unfold with ISIS in Syria which led to a flood of refugees into Europe. Therefore, in formulating the Safety and Risk Rankings, parameters relating to countries' stability and protection from negative economic and geopolitical consequences were considered.
Risk Ranking
The framework features 24 parameters grouped into 4 major categories:

1. Quarantine Efficiency

2. Government Management Efficiency

3. Monitoring and Detection

4. Emergency Treatment Readiness

Treatment Efficiency Ranking
The COVID-19 Risk Ranking Frameworkconducts benchmarking of countries according to their levels of risk according to a variety of medical and non-medical factors, including risk of infection, hospitalization, death and lasting health conditions, as well as the country's risk of negative economic, quality-of-life and geopolitical issues resulting from the pandemic. The framework is used to provide information on which countries where citizens will have the greatest likelihood of positive outcomes during the global COVID-19 pandemic, across the full-scope of factors impacting general safety, wellness and quality of life. It utilizes 24 specific parameters grouped into 4 distinct categories: Infection Spread Risk, Government Management, Healthcare Efficiency and Regional Specific Risks.

The framework features 24 parameters grouped into 4 major categories:
Eurozone Safety / Risk Ranking
The COVID-19 Treatment Efficiency Ranking Framework conducts benchmarking of countries according to how well they are monitoring infection spread, enabling citizens with the tools and information needed to manage non-critical cases at home without overburdening the healthcare infrastructure, how well they are treating critical cases and how well they are rapidly developing improved tests, vaccines and more effective COVID-19 treatments. Disease Monitoring, Disease Management, Emergency Treatment and Novel Approaches to Treatment R&D.
Asia Safety / Risk Ranking
The framework features 24 parameters grouped into 4 major categories:
Government Support and Citizen Relief Ranking
The COVID-19 Eurozone Safety / Risk Ranking Framework was designed specifically for the unique circumstances present in Europe. S pecial attention was applied to the unique characteristics of Europe including highly interconnected economies, high levels of supply-chain, tourist flow, and the incidence of critical hotspots.

The COVID-19 APAC Safety / Risk Ranking Framework applies a modified version of its global COVID-19 Countries Safety and Risk Ranking Frameworks tuned to the specifics of the APAC. Given that the pandemic originated in APAC, and that it is several weeks ahead of other countries in the overall timeline of the COVID-19, special attention should be given to the unique characteristics of the region.

The COVID-19 Government Support and Citizen Relief Ranking Framework conducts benchmarking of countries according to the scale, diversity, efficiency and effectiveness of its government's efforts and measures to provide economic support (e.g. supplemental income, tax breaks, subsidies, emergency loans, etc.) to its citizens, businesses (especially SMEs), the self-employed and other relevant stakeholders amid the COVID-19 crisis.

Given the unprecedented complexity of the pandemic, Deep Knowledge Group made the decision to adapt and retune its existing analytical frameworks to the pandemic. These frameworks were previously applied to the Longevity Industry, AI for Drug Discovery, GovTech, NeuroTech and other industries and domains on the forefront of DeepTech and Frontier Technologies. The new rankings are provided free of charge in order to provide governments, decision makers, and the general public with data-driven insights. The hope is that this information will help people make informed decisions that maximize beneficial outcomes for humanity. To review the complete rankings please visit the Deep Knowledge Group website.

... Read More

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Deep Analysis Of Global Pandemic Data Reveals Important Insights

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NOTE: Author Margaretta Colangelo is cofounder and managing partner at Deep Knowledge Group, the consortium behind the data presented in this story. Its subsidiary includes venture capital fund Deep Knowledge Ventures. COVID-19 Complexity Demands Sophisticated Analytics A massive amount of data about the pandemic is generated every day.

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analysis Updated: Apr 15, 2020 19:28 IST

To end on a positive note, no matter how bad they were, how many millions they killed, or how much they disrupted the economy, all of these pandemics were beaten, with the human race coming out stronger than ever. There was once a time when smallpox terrorised the world, but now it is all but eradicated(Ajay Aggarwal/HT PHOTO)

One of the good things about studying history is that no matter how bad things get, you can almost always find something from the past that was worse. This is also true about the coronavirus disease (Covid-19), which has now engulfed the world.

Perhaps the most comparable pandemic is the Spanish Flu, which lasted from January 1918 to December 1920. It infected some 500 million people and killed 50 million. To put this into perspective, the entire population of India, as per Census 1921, was about 250 million.

The Spanish Flu took place almost exactly a century ago but it had several similarities with Covid-19. But this was not the only pandemic to have similarities with Covid-19.

The three cholera pandemics of 1817-1824, 1826-1837 and 1846-1860 claimed more lives than any other disease outbreak in the 19th century. Originally starting in India and Central and Southeast Asia, cholera spread to China, from where it reached Europe through trade routes and Russian soldiers. It spread to Poland through Russian troops, who were brought in from various parts of the Tsar's empire to suppress uprisings. It then spread from Poland to East Prussia, forcing the Prussian authorities to close their borders to Russian transport. By 1831, the situation was so severe that the British government issued quarantine orders for any Russian ships sailing to British ports. But it was too late. The pandemic had already spread to Britain, France and most of Europe and Asia. Hundreds of thousands died. More than a million died in the Russian Empire during the third pandemic alone, and at least a 100,000 in most affected nations with each successive wave. Thus, we can safely say that the death toll went into millions.

The cholera pandemics of the 19th century had the most similarities with the coronavirus pandemic today. They both started in Asia, and spread to other parts of the world, deeply affecting specific nations (Russia for cholera, Italy and the United States for the coronavirus so far). They both also spread to other parts of the world through these specific nations and the affected populations were, unlike the global population that got Spanish influenza, not weakened by any major war - at least not on the industrial scale of World War I.

The cholera pandemics, just like Covid-19, also called for ship quarantine measures and spread primarily through the people who had gone abroad and brought it back to their nations. These pandemics required social distancing to prevent the spread of the infection. Like Covid-19, the cholera pandemics brought with them large economic losses - not only could ships not enter many ports, bringing maritime trade to a standstill, overland trade was also greatly affected. The Silk Route and other Central Asian trade routes, which counted for the majority of overland trade, could not be used due to both the threat of getting the disease and the anti-cholera steps taken by the Russian Empire, which controlled most of Central Asia at that time. Large financial losses were incurred, especially by the British and the Russians, the two most affected parties in terms of trade. Both relied on their far-flung empires for resources and wealth.

India can learn from the cholera pandemic, as it started here, and within months, hundreds of thousands were either infected or dead. At least 100,000 Indians and 10,000 British troops died in the first pandemic (1817-1824). This was partly because of not practising proper social distancing, which requires active participation from the people. Both an active government push, and deep citizen engagement and support, is clearly needed for social distancing and other public health measures.

In Russia, the incompetence of Tsar Nicholas I's regime in handling the pandemic across the massive rural expanses and the population of his vast empire led to more than a million deaths. While he ordered anti-cholera measures eventually, the damage had already been done. The delay in responding, and the vulnerability of large countries, with a substantial rural and floating population, must be factored into any response.

To end on a positive note, no matter how bad they were, how many millions they killed, or how much they disrupted the economy, all of these pandemics were beaten, with the human race coming out stronger than ever. There was once a time when smallpox terrorised the world, but now it is all but eradicated. The Black Death was beaten. The Spanish Flu was beaten. The cholera epidemic was beaten. We have recovered and come out stronger than ever from all these diseases. I am sure that we will be able to defeat the coronavirus too.
Shiv Malik is a student of Class 9, Vasant Valley School, New Delhi The views expressed are personal

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What the history of pandemics tells us about coronavirus

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analysis Updated: Apr 15, 2020 19:28 IST One of the good things about studying history is that no matter how bad things get, you can almost always find something from the past that was worse. This is also true about the coronavirus disease (Covid-19), which has now engulfed the world.

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A researcher works on the development of a vaccine against the novel coronavirus in Belo Horizonte, Brazil, in March. (Douglas Magno/AFP/Getty)

NOBEL LAUREATE Peter Medawar once defined a virus as "a piece of bad news wrapped up in protein." He wrote in 1983 that "no virus is known to do good." The key to stopping the novel coronavirus is that no virus can multiply on its own. It must invade a living cell. All hopes rest on a drug, vaccine or other therapy to disrupt the virus attack or impede its replication machinery. This is complicated science, not the instant "game changer" that President Trump has touted in the unproven antimalarial drug hydroxychloroquine.

Traditionally, it takes years to develop, test and manufacture a vaccine; the one that worked in Congo against Ebola was under development for a decade. These hurdles haven't changed, although one factor giving science a head start is that the whole genome of the coronavirus was sequenced and shared rapidly by China. Also, a new process of preliminary research reports unleashed a torrent of open source information.

Full coverage of the coronavirus pandemic

What might save us? More than 70 vaccines are being researched. The Norway-based Coalition for Epidemic Preparedness Innovations, an international public-private collaboration started in 2017, has been funding a number of experimental projects. One of them, created by Moderna of Cambridge, Mass., and the Vaccine Research Center of the National Institute of Allergy and Infectious Diseases, is attempting to use synthesized genetic material, known as messenger RNA, that would help the body recognize the virus and target it, rather than the established method of using attenuated pathogens or protein particles from the real virus. The approach underscores the value of acquiring the whole genome sequence so early. Other vaccine development efforts are also delving into whether it is possible to manipulate genetic material to create an effective vaccine in a new way. Two companies are experimenting with taking a snippet of genetic code and entwining it with a harmless virus, hopefully spurring the body to produce antibodies that would go after a coronavirus invasion.

A second overall approach is to create antiviral drugs and other therapies that could interfere with the steps that the coronavirus takes to infect a cell or replicate inside it. Some are looking to see whether existing drugs or vaccines against other illnesses, already tested for safety, might be repurposed, such as the antiviral remdesivir, which Gilead Sciences has put into five clinical trials around the world. It didn't succeed in the 2019 Ebola outbreak, but in test-tube and animal studies earlier had shown some potency against other coronaviruses. Yet another approach would be to create entirely new drugs or therapies, such as using the plasma of recovered patients to provide the protective antibodies needed to help ward off the virus.

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The science is immensely challenging. But we can take heart knowing that so many creative, persistent and indefatigable researchers are working on more than 140 experimental drug treatments and vaccines, cooperating across company lines and national borders.

The Post's View: We all want to reopen the economy. But it won't be quick or easy.

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Michael Leonberger: Weathering the coronavirus pandemic with an anxiety disorder

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Opinion | The science is challenging. But we should be hopeful for a covid-19 vaccine or drug.

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NOBEL LAUREATE Peter Medawar once defined a virus as "a piece of bad news wrapped up in protein." He wrote in 1983 that "no virus is known to do good." The key to stopping the novel coronavirus is that no virus can multiply on its own. It must invade a living cell.

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Covid-19 may attack immune system like HIV, doctors fear

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Researchers in China and the US find that the virus that causes Covid-19 can destroy the T cells that are supposed to protect the body from harmful invaders.

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With some 2.6 billion people around the world in some kind of lockdown, we are conducting arguably the largest psychological experiment ever;

This will result in a secondary epidemic of burnouts and stress-related absenteeism in the latter half of 2020;

Taking action now can mitigate the toxic effects of COVID-19 lockdowns.

In the mid-1990s, France was one of the first countries in the world to adopt a revolutionary approach for the aftermath of terrorist attacks and disasters. In addition to a medical field hospital or triage post, the French crisis response includes setting up a psychological field unit, a Cellule d'Urgence Médico-Psychologique or CUMPS.

In that second triage post, victims and witnesses who were not physically harmed receive psychological help and are checked for signs of needing further post-traumatic treatment. In those situations, the World Health Organization recommends protocols like R-TEP (Recent Traumatic Episode Protocol) and G-TEP (Group Traumatic Episode Protocol).

Since France led the way more than 20 years ago, international playbooks for disaster response increasingly call for this two-tent approach: one for the wounded and one to treat the invisible, psychological wounds of trauma.

In treating the COVID-19 pandemic, the world is scrambling to build enough tents to treat those infected with a deadly, highly contagious virus. In New York, we see literal field hospitals in the middle of Central Park.

But we're not setting up the second tent for psychological help and we will pay the price within three to six months after the end of this unprecedented lockdown, at a time when we will need all able bodies to help the world economy recover.

The mental toll of quarantine and lockdown

Currently, an estimated 2.6 billion people - one-third of the world's population - is living under some kind of lockdown or quarantine. This is arguably the largest psychological experiment ever conducted.

Unfortunately, we already have a good idea of its results. In late February 2020, right before European countries mandated various forms of lockdowns, The Lancet published a review of 24 studies documenting the psychological impact of quarantine (the "restriction of movement of people who have potentially been exposed to a contagious disease"). The findings offer a glimpse of what is brewing in hundreds of millions of households around the world.

In short, and perhaps unsurprisingly, people who are quarantined are very likely to develop a wide range of symptoms of psychological stress and disorder, including low mood, insomnia, stress, anxiety, anger, irritability, emotional exhaustion, depression and post-traumatic stress symptoms. Low mood and irritability specifically stand out as being very common, the study notes.

In China, these expected mental health effects are already being reported in the first research papers about the lockdown.

In cases where parents were quarantined with children, the mental health toll became even steeper. In one study, no less than 28% of quarantined parents warranted a diagnosis of "trauma-related mental health disorder".

Among quarantined hospital staff, almost 10% reported "high depressive symptoms" up to three years after being quarantined. Another study reporting on the long-term effects of SARS quarantine among healthcare workers found a long-term risk for alcohol abuse, self-medication and long-lasting "avoidance" behaviour. This means that years after being quarantined, some hospital workers still avoid being in close contact with patients by simply not showing up for work.

Reasons for stress abound in lockdown: there is risk of infection, fear of becoming sick or of losing loved ones, as well as the prospect of financial hardship. All these, and many more, are present in this current pandemic.

The second epidemic and setting up the second tent online

We can already see a sharp increase in absenteeism in countries in lockdown. People are afraid to catch COVID-19 on the work floor and avoid work. We will see a second wave of this in three to six months. Just when we need all able bodies to repair the economy, we can expect a sharp spike in absenteeism and burnout.

We know this from many examples, ranging from absenteeism in military units after deployment in risk areas, companies that were close to Ground Zero in 9/11 and medical professionals in regions with outbreaks of Ebola, SARS and MERS.

Right before the lockdown, we conducted a benchmark survey among a representative sample of the Belgian population. In that survey, we saw that 32% of the population could be classified as highly resilient ("green"). Only 15% of the population indicated toxic levels of stress ("red").

In our most recent survey after two weeks of lockdown, the green portion has shrunk to 25% of the population. The "red" part of the population has increased by 10 percentage points to fully 25% of the population.

These are the people at high risk for long-term absenteeism from work due to illness and burnout. Even if they stay at work, research from Eurofound reports a loss of productivity of 35% for these workers.

In general, we know at-risk groups for long-term mental health issues will be the healthcare workers who are on the frontline, young people under 30 and children, the elderly and those in precarious situations, for example, owing to mental illness, disability and poverty.

All this should surprise no one; insights on the long-term damage of disasters have been accepted in the field of trauma psychology for decades.

Image: When disaster strikes, Beverly Raphael, 1986

But while the insights are not new, the sheer scale of these lockdowns is. This time, ground zero is not a quarantined village or town or region; a third of the global population is dealing with these intense stressors. We need to act now to mitigate the toxic effects of this lockdown.

What governments and NGOs can and should do today

There is broad consensus among academics about the psychological care following disasters and major incidents. Here are a few rules of thumb:

Make sure self-help interventions are in place that can address the needs of large affected populations;

Educate people about the expected psychological impact and reactions to trauma if they are interested in receiving it. Make sure people understand that a psychological reaction is normal;

Launch a specific website to address psychosocial issues;

Make sure that people with acute issues can find the help that they need

In Belgium, we recently launched Everyone OK, an online tool that tries to offer help to the affected population. Using existing protocols and interventions, we launched our digital self-help tool in as little as two weeks.

When it comes to offering psychological support to their populations, most countries are late to react, as they were to the novel coronavirus. Better late than never.
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The views expressed in this article are those of the author alone and not the World Economic Forum.

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Lockdown is the world's biggest psychological experiment - and we will pay the price

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With some 2.6 billion people around the world in some kind of lockdown, we are conducting arguably the largest psychological experiment ever; This will result in a secondary epidemic of burnouts and stress-related absenteeism in the latter half of 2020; Taking action now can mitigate the toxic effects of COVID-19 lockdowns.

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Around the world, life as we know it has changed drastically. Global leaders and millions of citizens are facing the challenge of a lifetime. The COVID-19 pandemic is threatening not only healthcare systems, but also the livelihoods of citizens and the stability of economies.

As our colleagues wrote in " Safeguarding our lives and our livelihoods: The imperative of our time," the shock to our lives and livelihoods from the virus-suppression efforts could be the biggest of the past 100 years. If we do not stop the virus, many people will die. If attempts to stop the pandemic cause severe damage to social and economic networks, people will experience large-scale suffering in the medium and long term. The world must act on both of these fronts-suppressing the virus and mitigating the negative impact on citizens' livelihoods-at the same time. The progress we make on those fronts will determine the shape of the economic recovery (Exhibit 1).

So far, most governments, businesses, and citizens have rightly focused on saving lives. We have seen a range of responses, from drastic (the complete lockdown of the Wuhan region in China) to more gradual (restrictions on public gatherings and the promotion of physical distancing in some European countries and North America). Other countries such as South Korea have followed a third path. Based on massive testing and contact tracing, this approach has allowed them to control the spread of the virus without imposing widespread restrictions on public movement, at least so far. In Latin America, some countries reacted quickly and ordered weeks of complete lockdown while case numbers were still relatively low, with the goal of flattening the curve and reducing the speed of transmission.

Countries are also coming to grips with the second imperative: saving livelihoods. Many countries have responded with unprecedented levels of both fiscal and monetary stimulus to blunt the economic impact of the crisis. For example, the United States recently passed a $2 trillion stimulus package.

Yet tremendous uncertainty remains about what to do next, on both fronts. Most national health systems, particularly in some emerging markets, are insufficiently prepared for the task at hand. Countries thus face daunting questions: Should the quarantine continue? If so, for how long? Should it be a blanket quarantine for all regions and age groups? Many countries have large, informal economies, crowded living conditions, or high levels of household debt. Some have all three. How should they proceed?

The second imperative-saving livelihoods-is just as perplexing. Should all economic sectors receive the same treatment? How do we restart the economy in some geographies without resurgence of the virus? What systems need to be in place to restart safely?

In this article, we propose two frameworks for restarting an economy. The first is designed to help governments, the private sector, and nonprofits think through when to open their economies, and the second outlines an approach for how to do so.

Many countries are still in the depths of crisis, with hundreds of deaths every day. But others seem to be flattening the curve. Given what's at stake, it's not too soon to begin thinking about what it will take to restart the economy. In the words of perhaps the greatest wartime leader in history, "This is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning." Governments worldwide should recognize the hard work still to come and adequately prepare for the next phases of the crisis.

Prioritizing both lives and livelihoods: When to release constraints?

The threat of COVID-19 to lives and livelihoods will fully resolve only when enough people are immune to the disease to blunt transmission, either from a vaccine or direct exposure. Until then, governments that want to restart their economies must have public-health systems that are strong enough to detect and respond to cases. Leaders should recognize that regions may differ significantly in their readiness to restart their economies.

The first and most obvious factor in determining readiness is the number of new cases in a given area. Regions with significant ongoing transmission should expect that restarting economic activity will only lead to more transmission. Case numbers and, more importantly, hospitalizations need to be low enough for a health system to manage individually rather than through mass measures.

A second factor in thinking about this is the strength of the systems in place for detecting, managing, and preventing new cases. Elements of these systems include the following:

adequate medical capacity, especially of intensive care units (ICUs), for those with severe disease

ability to perform a diagnostic test for COVID-19 with a fast turnaround time

systems for effectively identifying and isolating cases and contacts, including digital tools for real-time sharing of critical data (however, different systems will be appropriate for different countries and contexts)

adequate medical resources, including trained doctors, beds, and personal protective equipment

public education informed by the best scientific evidence available

These elements can be combined to provide a measure of strength for public-health systems. If we combine a system's level of strength with an assessment of the intensity of virus transmission, we can evaluate any region's readiness to restart activity (Exhibit 2). These two dimensions determine four stages of readiness to reopen the economy, with Stage 4 the least ready and Stage 1 the most. One broad observation on countries' varying stages of readiness: many emerging markets are especially concerned with the question of how to add ICU capacity.

Response leaders can plot subnational regions (states, counties, cities, hospital-influenced zones, and so on) on this matrix to evaluate when each can restart some measure of economic activity. Regions with strong public-health systems and few or no cases, where tracking and isolation of transmission chains are still feasible, might behave differently than regions with weaker public-health systems that are further along on the epidemic curve. In many emerging-market countries, including several in Latin America, many elements are important but the main obstacle is ICU capacity. Achieving the necessary capacity requires highly coordinated efforts and a detailed management system.

Positions on the matrix will not be static; regions will move upward as case numbers fall and better control mechanisms are established, and to the right as public-health systems strengthen.

The matrix does not offer absolute guidelines but may be a useful tool to aid decision making. Governments can update the matrix every day, using real-time data. A robust management-information system can help countries use their own data to tailor their response to local realities.

In time, other scientific breakthroughs could also transform this dynamic-an effective vaccine, an accurate antibody test, significant new treatments for COVID-19-assuming they are available at scale and deployed widely. This article does not factor in this impact.

Exhibit 3 illustrates the path that a large city, region, or other geography might take toward economic readiness.

Countries may also have to choose adequate metrics to measure virus spread. The optimal metric would be the rate of transmission, but this demands a large testing capacity that may not be available to some countries. Alternative metrics might include the case growth rate and the cumulative total of cases.

Exhibit 4 shows how one country might look on the matrix. In this example, many regions need to maintain strong measures until the speed of the transmission slows. Other regions do not need to undergo the same restrictions and could potentially resume some of their economic activity. When coupled with an understanding of each region's relative economic importance, as we describe below, this information enables leaders to quickly identify places where more jobs are at stake-which in turn may help leaders prioritize efforts on building healthcare capacity.

In summary, regions can be categorized into four stages of readiness to reopen parts of the economy (Exhibit 5). For each stage, leaders can define the level of intensity of actions to be taken, allowing them to adjust policies and specific actions. Furthermore, the local-response matrix allows for coordination of policies among regions and avoids conflicting solutions that could exacerbate the transmission. It could also offer citizens and businesses an idea of what to expect, which in turn can facilitate economic actions on a mass scale with fewer hiccups.

Restarting the local economy: A nuanced approach

With an understanding of each region's economic structure, governments can quickly identify places where the economy can be restarted. To do that well, governments can assess both the risk of transmission and the relative economic importance of each sector. For instance, authorities might define importance using metrics such as total employment, vulnerable jobs, or contribution to the economy (Exhibit 6).

This analysis might require further elaboration for subsectors and individual jobs. A characterization at this level of detail could minimize the loss of jobs that entail only a low risk of transmission.

Some strategic sectors of the economy will need to operate even in lockdowns, including healthcare, defense and security, and procurement of strategic goods and services such as food, medicine, energy, water, gas, and communications. Remaining sectors can be gradually reopened regionally, as the public-health crisis abates. One group could start operating as a region's readiness moves from Stage 4 to Stage 3. A second group could start operating once the region is in Stage 2, when the risk of transmission is relatively under control. Others could open later, once the speed of transmission has been minimized or clear protocols have been created to account for the activity's higher risk of transmission.

When sectors start to go back to work, leaders must institute health and behavioral protocols to lower the potential for further transmission. In almost every sector, businesses will need protocols to maintain physical distancing and prevent a resurgence of new cases: remote work, hygiene- and health-oriented guidelines, frequent monitoring of people's temperatures for early detection of new cases, reporting of relevant information to the health authorities, and enforcement measures to guarantee compliance. Indeed, the adoption of these protocols and others can heavily influence a sector's position on the matrix. Jobs can be redefined in ways that make them safer to restart.

Additionally, each sector and subsector may need to implement specific requirements and procedures to guarantee the health of workers and the rest of the community. Public-health leaders and industry associations could work together to design protocols for each subsector in the days before the quarantine is lifted. They could also collaborate to provide resources that educate citizens and workers on how to apply those protocols.

Technology will play an important role in "licensing" people to return to work, but each country will have to consider privacy issues in introducing such systems.

Exhibit 7 illustrates general and sector-specific protocols to restart operations. These recommendations are based on McKinsey research and the experiences of several Asian countries-such as China, Japan, Singapore, and South Korea-that have begun to use them.

Countries need to introduce an additional level of granularity to their efforts to protect lives and livelihoods. Our approach requires continual strengthening of the healthcare system through such factors as capacity for widespread testing, increased capacity of local ICUs, and the ability to monitor and quarantine chains of transmission. Technology will play an important role in "licensing" people to return to work, but each country will have to consider privacy issues in introducing such systems. The local-response matrix should be refreshed frequently to guard against a rise in transmission. Resurgence is a real risk and will inevitably occur in many locations.

Countries are naturally anxious to restart their economies. So are citizens. But countries that deliberately shape the next normal, rather than moving to the next stage haphazardly, will have greater success in saving both lives and livelihoods.

About the author(s)

Andres Cadena and Fernando Ferrari are senior partners in McKinsey's Bogota office, where Felipe Child and Juan Franco are partners. Matt Craven, MD, is a partner in the Silicon Valley office. is a senior partner in the London office. Matthew Wilson is a senior partner in the New York office.

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How to restart national economies during the coronavirus crisis

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Around the world, life as we know it has changed drastically. Global leaders and millions of citizens are facing the challenge of a lifetime. The COVID-19 pandemic is threatening not only healthcare systems, but also the livelihoods of citizens and the stability of economies.

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Bangalore Medical College and Research Institute's (BMCRI) ethics committee has cleared convalescent plasma therapy for treating critically ill COVID-19 patients using blood donated by those who have recovered from the disease. Fortunately, 39 patients have been discharged so far in Karnataka who are all potential donors.

The idea is to use the antibodies that recovered patients must have developed (present in their blood) in response to fighting COVID-19, for patients who are on ventilators who are not in a position to fight off the disease on their own because of weak response from their own immune system.

On Thursday, BMCRI wrote to Jawaid Akhtar, Additional Chief Secretary, Health, Karnataka, to get the Indian Council of Medical Research's approval for the same. "There are two steps. One, an approval from the ethics committee, which BMCRI has already given. Second, permission from the ICMR, for which I have written to them. We applied three days ago. I wrote another letter to the Government of India to ask the ICMR to expedite the approval," he said.
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BMCRI currently has three patients in the ICU. One of them with severe acute respiratory infection (SARI). "The antibodies in a recovered patients' blood will be used to treat critical patients with SARI if they stop responding to conventional treatment," said Dr CR Jayanthi, Dean, BMCRI and member secretary of the ethics committee.

Karnataka's application comes after Tamil Nadu, Maharashtra and Delhi's pleas to the ICMR to give them permission to do the therapy. Kerala's Sree Chitra Tirunal Institute of Medical Sciences reportedly got the ICMR approval to conduct a clinical trial. The ICMR is reportedly in the process of finalising the protocol for conducting a clinical trial after which the Drug Controller General of India (DCGI) has to give a go-ahead.
Track sate-wise confirmed coronavirus cases here
"Those who have recovered have to go through tests for HIV and Hepatitis B. After these diseases are ruled out, we have to work out a model of how much plasma to give to which patient, who is eligible for it and select the eligible patients. The idea is SARI patients with COVID-19 will recover faster. We have to see if we can broaden the inclusion criteria. But based on how Indian patients will react, ICMR has to work out a uniform protocol," she said.

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Coronavirus: Karnataka writes to ICMR for plasma therapy approval

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Bangalore Medical College and Research Institute's (BMCRI) ethics committee has cleared convalescent plasma therapy for treating critically ill COVID-19 patients using blood donated by those who have recovered from the disease. Fortunately, 39 patients have been discharged so far in Karnataka who are all potential donors.

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beijing tightens grip over coronavirus research amid us-china row on virus origin  - cnn

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China imposes restrictions on research into origins of coronavirus

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China has imposed restrictions on the publication of academic research on the origins of the novel coronavirus, according to a central government directive and online notices published by two Chinese universities, that have since been removed from the web.

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Worldometer

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COVID Live - Coronavirus Statistics - Worldometer

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Live statistics and coronavirus news tracking the number of confirmed cases, recovered patients, tests, and death toll due to the COVID-19 coronavirus from Wuhan, China. Coronavirus counter with new cases, deaths, and number of tests per 1 Million population. Historical data and info. Daily charts, graphs, news and updates

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You may not like who you're about to become.

A fresco by Luigi Vacca depicting the plague of 1630. Credit... DeAgostini/Getty Images

Some disasters, like hurricanes and earthquakes, can bring people together, but if history is any judge, pandemics generally drive them apart. These are crises in which social distancing is a virtue. Dread overwhelms the normal bonds of human affection.

In "The Decameron," Giovanni Boccaccio writes about what happened during the plague that hit Florence in 1348: "Tedious were it to recount how citizen avoided citizen, how among neighbors was scarce found any that shewed fellow-feeling for another, how kinfolk held aloof, and never met ... nay, what is more, and scarcely to be believed, fathers and mothers were found to abandon their own children, untended, unvisited, to their fate."

In his book on the 1665 London epidemic, "A Journal of the Plague Year," Daniel Defoe reports, "This was a time when every one's private safety lay so near them they had no room to pity the distresses of others. ... The danger of immediate death to ourselves, took away all bonds of love, all concern for one another."

Fear drives people in these moments, but so does shame, caused by the brutal things that have to be done to slow the spread of the disease. In all pandemics people are forced to make the decisions that doctors in Italy are now forced to make - withholding care from some of those who are suffering and leaving them to their fate.

In 17th-century Venice, health workers searched the city, identified plague victims and shipped them off to isolated "hospitals," where two-thirds of them died. In many cities over the centuries, municipal authorities locked whole families in their homes, sealed the premises and blocked any delivery of provisions or medical care.

Frank Snowden, the Yale historian who wrote "Epidemics and Society," argues that pandemics hold up a mirror to society and force us to ask basic questions: What is possible imminent death trying to tell us? Where is God in all this? What's our responsibility to one another?

Pandemics induce a feeling of enervating fatalism. People realize how little they control their lives. Anton Chekhov was a victim during a TB epidemic that traveled across Russia in the late 19th century. Snowden points out that the plays he wrote during his recovery are about people who feel trapped, waiting for events outside their control, unable to act, unable to decide.

Pandemics also hit the poor hardest and inflame class divisions.

Cholera struck Naples in 1884, especially the Lower City, where the poor lived. Rumors swept the neighborhood that city officials were deliberately spreading the disease. When highhanded public health workers poured into Lower City, the locals revolted, throwing furniture at them, hurling them down stairs.

The city thought the disease was passed on by people eating unripe or overripe fruit. The peasants responded by bringing baskets of fruit to City Hall and gorging on it in public - a way to hold up a defiant middle finger against the elites who were so useless in the face of the disease.

The Spanish flu pandemic that battered America in 1918 produced similar reactions. John M. Barry, author of "The Great Influenza," reports that as conditions worsened, health workers in city after city pleaded for volunteers to care for the sick. Few stepped forward.

In Philadelphia, the head of emergency aid pleaded for help in taking care of sick children. Nobody answered. The organization's director turned scornful: "Hundreds of women ... had delightful dreams of themselves in the roles of angels of mercy. ... Nothing seems to rouse them now. ... There are families in which every member is ill, in which the children are actually starving because there is no one to give them food. The death rate is so high, and they still hold back."

This explains one of the puzzling features of the 1918 pandemic. When it was over, people didn't talk about it. There were very few books or plays written about it. Roughly 675,000 Americans lost their lives to the flu, compared with 53,000 in battle in World War I, and yet it left almost no conscious cultural mark.

Perhaps it's because people didn't like who they had become. It was a shameful memory and therefore suppressed. In her 1976 dissertation, "A Cruel Wind," Dorothy Ann Pettit argues that the 1918 flu pandemic contributed to a kind of spiritual torpor afterward. People emerged from it physically and spiritually fatigued. The flu, Pettit writes, had a sobering and disillusioning effect on the national spirit.

There is one exception to this sad litany: health care workers. In every pandemic there are doctors and nurses who respond with unbelievable heroism and compassion. That's happening today.

Mike Baker recently had a report in The Times about the EvergreenHealth hospital in Kirkland, Wash., where the staff showing the kind of effective compassion that has been evident in all pandemics down the centuries. "We have not had issues with staff not wanting to come in," an Evergreen executive said. "We've had staff calling and say, 'If you need me, I'm available."

Maybe this time we'll learn from their example. It also wouldn't be a bad idea to take steps to fight the moral disease that accompanies the physical one.
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Opinion | Pandemics Kill Compassion, Too

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You may not like who you're about to become. Some disasters, like hurricanes and earthquakes, can bring people together, but if history is any judge, pandemics generally drive them apart. These are crises in which social distancing is a virtue. Dread overwhelms the normal bonds of human affection.

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Documentary: Tracking the Origins of Covid19

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The first documentary movie on CCP virus, Tracking Down the Origin of the Wuhan Coronavirus

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As patients with COVID-19 continue pouring into emergency departments and intensive care units across the nation, an old treatment that has been adapted for a new disease is being tested in New York.

In the past few days, the Mount Sinai Hospital System has injected more than 20 very sick coronavirus patients with a "convalescent serum" based on the blood plasma of people who have recovered from the disease.

One of the first recovered patients to donate, Danny Riemer, 37, of New Rochelle, New York, said he and his wife feel "blessed" that they are now healthy and can volunteer their plasma to help others. "And despite the fact that we did have the virus, our thoughts are really with others, the people who are still fighting the virus, the people who have had much more serious cases than us," he said.
Full coverage of the coronavirus outbreak
Dr. Jeffrey Jhang, medical director of clinical laboratories and transfusion services for the Mount Sinai Health System, said: "We have so many patients who are sick. We are crossing our fingers that this will be a game changer and really accelerate the recovery of these patients."

As first reported in a series of stories by NBCNews.com, Dr. Arturo Casadevall of the Bloomberg School of Public Health at Johns Hopkins University in Baltimore has spearheaded a nationwide effort to develop a plasma treatment.

The National COVID-19 Convalescent Plasma Project is a consortium of more than 40 of the nation's top health institutions across 22 states looking to collect plasma from recovered COVID-19 patients to assist in treating those currently ill with the disease or to perhaps prevent others, like front-line medical workers, from getting the virus at all.

Convalescent plasma therapy, which involves collecting antibodies from the blood of recovered patients, is nothing new. It was used to treat the 1918 and 1957 flu epidemics, as well as SARS, H1N1 and Ebola and, most recently, some COVID-19 patients in China.

But in recent weeks, Dr. Florian Krammer, a microbiologist, and his team at Mount Sinai's Icahn School of Medicine have made a breakthrough in COVID-19 antibody testing.

Jhang said: "While other tests measure whether the antibody is there or not, our assay can also measure how much of the antibody is there. And that's important, because we can identify those donors with a high amount of antibody who would most likely benefit the patients receiving this plasma."

The more antibodies, it's thought, the greater the boost to the treatment's efficacy.

Jhang said that the hospital is using an Emergency Use Authorization from the Food and Drug Administration to conduct the tests but that the agency has discussed issuing a formal protocol so more hospitals can use the test.

On Friday, the FDA issued an updated set of guidelines reminding health care providers that more clinical trials must take place before "routinely administering" convalescent plasma to COVID-19 patients can begin.

When it comes to executing the practice on a wide scale, Jhang said, part of the challenge lies in waiting for enough patients to fully recover and develop immune responses. Then they must be screened. Each donor provides the equivalent of four doses of plasma. At Mount Sinai, two doses are being given to the sickest patients. In the past few days, Mount Sinai has given more than 20 very sick patients the plasma of those who recovered.

Jhang said that when Mount Sinai put out the call for plasma donors - contacting recovered patients and emailing its 40,000 staff members - nearly 10,000 people volunteered within a couple of days. While it turns out that not all who volunteered actually had the disease, the hospital staffers are sorting out the able from the willing, and the response was heartening.

Danny Riemer was one of the first patients to answer the call.

"I think that for people who have recovered from the virus and are thinking about what they could do to help, this is probably the least heroic way possible to be a hero," Riemer said. "It's almost as if a survivor is able to pass the life raft on to the next person who needs it."

Riemer and his wife, Sheera, 35, got a notice in early March that they may have been exposed to a person who tested positive for the deadly virus. The state Health Department told them to self-isolate, and within days they began to develop symptoms. They both tested positive but experienced only "mild symptoms" that required no hospitalization. They recovered at home with their three kids - none of whom got sick.

The Riemers heard about the project at Mount Sinai through a family friend. Danny Riemer said that the moment they were released from quarantine, he and his wife went to get tested for the program.

After getting the news that Danny Riemer's COVID-19 test showed that he was no longer sick and that his antibody test had resulted in a high return, he was able to donate plasma late last week.

"It was simple," he said. "There was a needle put into my arm. The machine did its job. And I caught up on work and just kind of relaxed there."

Sheera Riemer initially was not eligible, as her nose swab was still coming back positive for the disease. This week, on her fourth attempt, she was found to be free of COVID-19, but she is waiting to hear whether she has enough antibodies to be a donor.

The researchers and practitioners who make up the National COVID-19 Convalescent Plasma Project are working to determine which patients would be the best candidates to receive the convalescent plasma, said Dr. Michael Joyner, one of the project leaders, who is a professor of anesthesiology at the Mayo Clinic Alix School of Medicine.

"Historically when products like this have been used for other diseases, it's best to give them relatively early in the course of the disease, versus late in the course of the disease," Joyner said, adding that both intensive care and non-intensive care hospital patients are also being considered.

"So I tell people we're trying to help the front-line people put a finger in the dike," he said. "And then we're waiting also for the biotech and vaccine cavalry to arrive."
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Just last week, doctors at the Mayo Clinic, in Rochester, Minnesota, conducted their first convalescent plasma donation from a person who had recovered from COVID-19. The plasma is most likely headed to a patient they hope to keep out of intensive care.

Joyner said the Mayo Clinic is in a unique position. "The pandemic is a little late to get to us," he said. "As opposed to a week or five days away from the peak here, we're probably two or three weeks away from the peak. So we have time to plan."

But Joyner said the treatment was already being implemented at record speed given the demand for an innovation that could mitigate the effects of infection.

On Friday, the FDA approved a clinical trial allowing researchers at Johns Hopkins to prophylactically test how convalescent plasma could be used to boost the immune systems of those like front-line health care workers who are at a high risk of exposure to COVID-19.

"This is a process - done under normal times, would probably take about 18 months from start to finish, as things are done in series," he said. "Because we're doing them in parallel, we've been able to do them somewhere between eight and 18 days."

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Plasma treatment being tested in NYC may be coronavirus 'game changer'

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As patients with COVID-19 continue pouring into emergency departments and intensive care units across the nation, an old treatment that has been adapted for a new disease is being tested in New York.

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The U.S. needs more ventilators. Why can't it make them in time?

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Even with ventilator makers working overtime and auto companies' help, there's no easy fix to the shortage.

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That Imperial coronavirus report, in detail  | FT Alphaville

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The COVID-19 pandemic is the defining global health crisis of our time and the greatest global humanitarian challenge the world has faced since World War II. The virus has spread widely, and the number of cases is rising daily as governments work to slow its spread. India has moved quickly, implementing a proactive, nationwide, 21-day lockdown, with the goal of flattening the curve and using the time to plan and resource responses adequately.

Along with an unprecedented human toll, COVID-19 has triggered a deep economic crisis. The global economic impact could be broader than any that we have seen since the Great Depression. To understand the probable economic outcomes and possible interventions, McKinsey spoke with more than 600 leaders, including senior economists, financial-market experts, and policy makers, in 100 companies across multiple sectors. Based on these inputs, we modeled estimates for three economic scenarios in India (Exhibit 1).

In scenario 1, the economy could contract by about 10 percent in the first quarter of fiscal year 2021, with GDP growth of 1 to 2 percent in fiscal year 2021. In this scenario, the lockdown would be relaxed after April 15, 2020 (when the 21-day deadline is due to expire), with appropriate protocols put in place for the movement of goods and people after that. Our economic modeling suggests that even in this scenario of relatively quick rebound, the livelihoods of eight million workers, including many who are in the informal workforce, could be affected. In other words, eight million people could have their ability to subsist and afford basic necessities, such as food, housing, and clothing, put at severe risk. And with corporate and micro-, small-, and medium-size-enterprise (MSME) failure, nonperforming loans (NPLs) in the financial system could rise by three to four percentage points of loans. The amount of government spending required to protect and revive households, companies, and lenders could therefore be in the region of 6 lakh crore Indian rupees (around $79 billion), or 3 percent of GDP.

In scenario 2, the economy could contract sharply by around 20 percent in the first quarter of fiscal year 2021, with -2 to -3 percent growth for fiscal year 2021. Here, the lockdown would continue in roughly its current form until mid-May 2020, followed by a very gradual restarting of supply chains. This could put 32 million livelihoods at risk and swell NPLs by seven percentage points. The cost of stabilizing and protecting households, companies, and lenders could exceed 10 lakh crore Indian rupees (exceeding $130 billion), or more than 5 percent of GDP.

Scenario 3 could mean an even deeper economic contraction of around 8 to 10 percent for fiscal year 2021. This could occur if the virus flares up a few times over the rest of the year, necessitating more lockdowns, causing even greater reluctance among migrants to resume work, and ensuring a much slower rate of recovery.

Robust measures to stabilize and support households, businesses, and the financial system

Assuming scenario 2 plays out, the potential economic loss in India would vary by sector, with current-quarter output drops that are large in sectors such as aviation and lower in sectors such as IT-enabled services and pharmaceuticals (Exhibit 2). Current-quarter consumption could drop by more than 30 percent in discretionary categories, such as clothing and furnishings, and by up to 10 percent in areas such as food and utilities. Strained debt- service-coverage ratios would be anticipated in the travel, transport, and logistics; textiles; power; and hotel and entertainment sectors.

There could be solvency risk within the Indian financial system, as almost 25 percent of MSME and small- and medium-size-enterprise (SME) loans could slip into default, compared with 6 percent in the corporate sector (although the rate could be much higher in aviation, textiles, power, and construction) and 3 percent in the retail segment (mainly in personal loans for self-employed workers and small businesses). Liquidity risk would also need urgent attention as payments begin freezing in the corporate and SME supply chains. Attention will need to be given to the liquidity needs of banks and nonbanks with stretched liquidity-coverage ratios to ensure depositor confidence.

Given the magnitude of potential unemployment, business failure, and financial-system risk, a comprehensive package of fiscal and monetary interventions may need to be planned, keeping scenario 2 in mind. This might be triggered progressively as situations evolve and as actions are taken to move to the more favorable scenario 1 through effective public-health measures and graded lockdowns.

Further fiscal-, monetary-, and structural-measure possibilities

Several measures have already been announced to provide liquidity, limit the immediate NPL impact, and ease personal distress for needy households in India. These amount to around 0.8 percent of GDP. Additional measures could be considered to the tune of 10 lakh crore Indian rupees, or more than 5 percent of GDP in fiscal year 2021. All the estimated requirements may not necessarily be reflected in the fiscal deficit of the current year-for example, some support may be structured as contingent liabilities that only get reflected when they devolve. However, a package of this order of magnitude may be essential in supporting those dealing with the possible steep declines in aggregate demand and in protecting the financial system from the possible solvency and liquidity risks arising from stressed companies if scenario 2 or scenario 3 plays out.

Household demand could then be boosted beyond the support provided to needy households that the Indian government has already announced. Consideration could be given to an income-support program in which the government both pays for a share of the payroll for the 60 million informal contractual and permanent workers linked to companies and provides direct income support for the 135 million informal workers who are not on any form of company payroll. India's foundational digital-identity infrastructure, Aadhaar, enables effective mechanisms for direct support, including through the Pradhan Mantri Jan-Dhan Yojana (PMJDY) and Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) programs and to landless Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) beneficiaries. Concessions for home buyers, such as tax rebates for a time-bound period, could stimulate the housing market and unlock the job multiplier.

For bankruptcy protection and liquidity support, MSMEs could receive liquidity lines from their banks, refinanced by the Reserve Bank of India and a loan program for first-time borrowers could be administered through SIDBI. Substantial credit backstops from the government could be instituted for likely new NPLs Timely payments to MSMEs by large companies and governments could be encouraged by promoting bill discounting on existing platforms.

For large corporations, banks could be allowed to restructure the debt on their balance sheets, and procedural requirements for raising capital could be made less onerous. The Indian government could consider infusing capital through a temporary Troubled Asset Relief (TARP)-type program (such as through preferred equity) in a few distressed sectors (such as travel, logistics, auto, textiles, construction, and power), with appropriate conditions to safeguard workers and MSMEs in their value chains. Banks and nonbanks may also require similar measures to help strengthen their capital, along with measures to step up their liquidity and the liquidity in corporate-bond and government-securities markets.

To manage the macroeconomic consequences of a large stabilization package, the government would also need to consider clearly communicating to the markets and population that these measures are deep but temporary. Given that India's fiscal resources are constrained, the Reserve Bank of India may need to finance a portion of such incremental government spending. The spending could be tracked as a COVID-19 portion of the budget to boost transparency. The inflationary effects may be low, as lockdowns severely constrict demand and the fiscal support provided would be a substitute for expenditure rather than additional stimulus. Price increases could, however, occur in some sectors, such as food, so appropriate steps would be needed to maintain harvests and keep the food supply chain operating smoothly.

Overall, devising a credible, systemwide, stabilization package would benefit from being executed in a timely fashion so it can influence the pace of recovery and help avoid severe damage to livelihoods, the economy, the financial sector, and society. Many global economies are also facing these issues and having to put in place their own stabilization packages, with similar intent.

Following the first wave of stabilization measures, attention could shift to implementing the structural reforms needed to increase investment and productivity, create jobs quickly, and improve fiscal health. This could mean introducing further reforms in infrastructure and construction and accelerating investments in health, affordable housing, and other urban infrastructure. States could accelerate spending, and institutions such as NIIF could deploy domestic and long-term foreign capital faster. Such reforms could also enable Make in India sectors to become globally competitive and boost exports (such as electronics, textiles, electric vehicles, and food processing), strengthen the financial sector, deepen household financial savings and capital markets, and accelerate asset monetization and privatization to raise resources.

Emergence from lockdown, safeguarding both lives and livelihoods

Countries that are experiencing COVID-19 have adopted different approaches to slow the spread of the virus. Some have tested extensively, carried out contact tracing, limited travel and large gatherings, encouraged physical distancing, and quarantined citizens. Others have implemented full lockdowns in cities with high infection rates and partial lockdowns in other regions, with strict protocols in place to prevent infections.

The pace and scale of opening up from lockdown for India may depend on the availability of the crucial testing capabilities that will be required to get a better handle on the spread of the virus, granular data and technology to track and trace infections, and the build-up of healthcare facilities to treat patients (such as hospital beds by district). In parallel, protection protocols, cocreated with industry, could be designed for different settings (such as mandis [rural markets], construction sites, factories, business-process-outsourcing [BPO] companies, urban transit, and rural-urban labor movement). As an example, industrial areas (such as Baddi, Vapi, and Tirupur) could be ring-fenced and made safe, with local dormitories set up for the labor force and minimal, controlled movement in and out of the site allowed. There could be on-site testing at factories and staggered shifts for workers. While the principles may be the same for construction sites and BPO companies, the specifics would differ.

A geographic lens could be overlaid to determine how quickly the lockdown could be lifted when new protection protocols are in place. Red, yellow, and green zones could be earmarked based on unambiguous criteria, with clear rules for economic activity, entry, and exit. The classification of areas could be updated frequently as the situation evolves. The definition of a "zone" would need to be granular (such as by ward, colony, and building cluster) to allow as much economic activity as is safely possible while targeting infection as accurately as possible. Since there is a very real possibility of the virus lingering on through the year, this microtargeting approach could help decelerate its spread while keeping livelihoods going.

The alternative approach of opening up select industry chains would be less feasible, given that sectors are tightly intertwined. A textile-export factory, for instance, would require chemicals for processing, paper and plastic for packaging, spare parts for its sewing machines, and consumables such as thread. Segregating industrial establishments by size would also be difficult, since smaller suppliers are often bound to the larger manufacturers.

Actions would need to be implemented locally, with different approaches for districts based on their characteristics (such as rural versus urban, industrial versus service oriented, strong versus weak healthcare infrastructure, and heavily infected versus not infected yet). India could consider using the last week of the current lockdown to gear up for local execution, equipping more than 700 of the most appropriate government officers with insights gained from across the world and from ongoing efforts in cities such as Mumbai and states such as Kerala, which are currently fighting the pandemic.

As part of a set of options to consider, based on prior lessons learned in India from repurposing and redeployment of needed skills and expertise for nationwide efforts, such as after floods and natural calamities, these officers could potentially be deputed to work with the district magistrates (DMs) in each district. They could cooperate in dynamically developing and helping execute locally tailored healthcare-expansion efforts, local- or state-level lockdown timetables, and back-to-work protocols. The DMs and deputized officers in districts could potentially be supported by cross-functional centers of excellence (COEs) in states or at the center. These COEs would have medical, administrative, social, economic, and business experts using their considerable knowledge to collect best practices, conduct rapid analysis, and provide valuable suggestions and recommendations to the districts to ensure high-quality implementation.

It is imperative that society preserve both lives and livelihoods. To do so, India can consider a concerted set of fiscal, monetary, and structural measures and explore ways to return from the lockdown that reflect its situation and respect that most important of tenets: the sanctity of human life.

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Getting ahead of coronavirus: Saving lives and livelihoods in India

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The COVID-19 pandemic is the defining global health crisis of our time and the greatest global humanitarian challenge the world has faced since World War II. The virus has spread widely, and the number of cases is rising daily as governments work to slow its spread.

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This column offers a 'people view' - household-level data - of Indian households to feed into the ongoing macro-level discussion about the right level of financial support needed to help citizens get to their feet following the loss of income caused by the lockdown, and where it should be deployed.

Presented here is a ground-up calculation based on what categories of jobs and job arrangements mainly contribute to the income of households, and what that actual income level is.

Macro-level discussions are based on a broadbrush understanding of occupation - large swathes of informality, agriculture dependence and migrants. We base our assessment on a more specific map of occupation and income level by town class for urban, and district development level for rural areas.

The data comes from our pan-Indian study, the ICE 360 database, 2016 and 2018, on how Indian households earn, spend, save, live, and access public goods.

Occupations & vulnerability

In the accompanying table, occupation categories are described and arranged in decreasing order of vulnerability based on the nature of work and income level; the table shows how large, how dominant, and how vulnerable or "at risk" each occupation category is, separately for urban and rural India.

We measure vulnerability by what percentage of households in each category fall into the bottom 40% of income earners, separately for urban/rural.

We chose 40% to define the vulnerable instead of the conventional definition of bottom 20% because our work shows that this entire group has very little cushion between income and expenditure even in good times; it's always touch-and-go for them.
Explained | Which factories should reopen after India's coronavirus lockdown?
The poorest 20% don't manage to meet even their routine expenditure required for day-to-day living, while the 20% above them have a slim margin in good times often destroyed by health or social emergencies or inflation.

Row 1 of the table shows the most vulnerable group by far of 91 million households, dependent on casual labour, a quarter of all urban Indian and a third of all rural Indian households, largely low-income.

Two months of income support at the lower end of the group's earning level of Rs 10,000 in tier 3 and tier 4 towns, and Rs 8,500 in the less developed districts of rural, adds up to Rs 1.62 lakh crore - 0.85% of GDP.

Next most vulnerable are petty trader (hawkers, street vendors) households (row 2 of table), for whom one month's income support can also fund inventory, which they can start rotating.
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This group earns about as much or as little as casual labour with no U-R difference, and will require Rs 10,500 crore.

Next are the individual service provider households (row 3 of table) who are reasonably well off. Many have the skills for which pent-up demand already exists (beauticians and electricians for instance).

There is, however, a 30% segment within this occupation category that classifies as low-income, earns only slightly more than labour or petty traders, and needs support. One month of income support to them needs Rs 5,000 crore.

The support bill

The total support bill of Rs 1.78 lakh crore for this core vulnerable group of 10.6 crore households is about 0.92% of GDP. This group is only about one fourth of the Jan Dhan household base of 38.3 crore. There is another large group of 45 million salaried work-dependent households, mostly in the informal sector (row 4 of the table), but attached to an employer of sorts.

If the Prime Minister could repeat his plea to the employers of this group to please share and pay full salaries through the lockdown period, it would secure this group - the "India 2" that shapes our cities, and is a big enabler of "India 1".
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Most of them are fairly well off in large towns and rural areas, but with a small lower income segment equally distributed between small town urban and less developed rural. One month's income support to this segment at the casual labour rate amounts to Rs 8,250 crore.

In our assessment, all told, the total one-time income support bill, assuming lifting of the lockdown as planned, amounts to about Rs 1.86 lakh crore, or about 1% of GDP.

What of small shop and micro business owners (row 5 of the table), who are hurting with no revenue, and who have fixed expenses?

They are better aided through business concessions or directed small ticket 'working capital' lending at rates far lower than what NBFCs would charge for unsecured lending. As rows 6 and 7 of the table show, the secure formally employed salaried group are very small relative to the others and financially well off, more secure, and have a savings cushion. Yet, they get a larger than warranted share of concern as all the talk of job losses and layoffs shows! Perhaps a change in our vocabulary to replace the word 'jobs' with 'livelihoods' would help us be more in tune with the reality of India.
(Rama Bijapurkar and Dr Rajesh Shukla areco-founders of think tank and fact tank People Research on India's Consumer Economy) Here's a quick Coronavirus guide from Express Explained to keep you updated: What can cause a COVID-19 patient to relapse after recovery? | COVID-19 lockdown has cleaned up the air, but this may not be good news. Here's why | Can alternative medicine work against the coronavirus? | A five-minute test for COVID-19 has been readied, India may get it too | How India is building up defence during lockdown | Why only a fraction of those with coronavirus suffer acutely | How do healthcare workers protect themselves from getting infected? | What does it take to set up isolation wards? 📣 The Indian Express is now on Telegram. Click here to join our channel (@indianexpress) and stay updated with the latest headlines
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india below average income household coronavirus

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Experts Explain: Loss of income; ground-up assessment of recovery support to households

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This column offers a 'people view' - household-level data - of Indian households to feed into the ongoing macro-level discussion about the right level of financial support needed to help citizens get to their feet following the loss of income caused by the lockdown, and where it should be deployed.

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KPMG Economic Outlook in the face of Covid 19

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Volunteer-driven crowdsourced initiative to track the spread of Coronavirus (COVID-19) in India

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Webinar with Young Presidents Organization

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Updated: April 11, 2020, 6:25 PM IST

A total of 586 hospitals in the country have been marked as dedicated COVID-19 hospitals with capacity of over one lakh isolation beds and 11,500 ICU beds reserved for coronavirus patients, the Union Health Ministry said on Saturday.

Addressing a press briefing, Health Ministry's Joint Secretary Lav Agarwal said the government has taken early preemptive action to identify COVID-19 hotspots in the country. In the absence of a lockdown and other containment measures, there would have been over 8.2 lakh coronavirus cases in the country till April 15, he said.

According to the Health Ministry, 1,035 fresh COVID-19 cases and 40 deaths due to the disease were reported in the last 24 hours across the country, taking the total number of cases to 7,447 and deaths to 239 nationwide.

Agarwal said, "586 dedicated COVID-19 hospitals have been earmarked at the state and centre level. One lakh isolation beds and 11,500 ICU beds have been reserved for coronavirus patients across country. This figure is being augmented every day, based on the evolving situation."

He further said, "We had done an analysis on the rate of growth in cases. We observed Janta curfew on March 22 and went for lockdown from March 25. According to statistical analysis, in the absence of lockdown and other containment measures, there would have been 41 per cent increase and 8.2 lakh coronavirus cases by April 15," Agarwal said.

He asserted that measures like social distancing, lockdown and other containment efforts are important in fighting the battle against coronavirus.

"The response of Government of India has been preemptive, proactive and to the extent of being over-prepared and through our graded approach, we have aligned our response with the evolving situation. Ministry of AYUSH has prepared a set of guidelines on respiratory health and to boost immunity. Districts have been asked to incorporate this in district-level contingency plan as well," he said.

Agarwal also asserted that there is no shortage in the country of anti-malarial drug hydroxychloroquine, cited by many as a viable therapeutic solution to counter the coronavirus infection.

Responding to a question, a senior official of the Indian Council of Medical Research (ICMR) said, "Five lakh antibody testing kits ordered by ICMR have not been received yet".

The ICMR official said over 1.7 lakh samples have been tested in country so far for COVID-19, of which 16,564 samples were tested on Friday.
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Country Has 586 COVID-19 Hospitals with 1 Lakh Isolation Beds and Over 11,000 ICU Beds: Health Ministry

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Updated: April 11, 2020, 6:25 PM IST A total of 586 hospitals in the country have been marked as dedicated COVID-19 hospitals with capacity of over one lakh isolation beds and 11,500 ICU beds reserved for coronavirus patients, the Union Health Ministry said on Saturday.

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Covid101 | Reliable info on the coronavirus

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Covid101 gives you the best links to the most reliable news, government updates and healthcare information on Covid-19 in India and around the world.

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With everything that's happening about the Coronavirus, it might be very hard to make a decision of what to do today. Should you wait for more information? Do something today? What?

Here's what I'm going to cover in this article, with lots of charts, data and models with plenty of sources:

How many cases of coronavirus will there be in your area?

What will happen when these cases materialize?

What should you do?

When?

When you're done reading the article, this is what you'll take away:

The coronavirus is coming to you.
It's coming at an exponential speed: gradually, and then suddenly.
It's a matter of days. Maybe a week or two.
When it does, your healthcare system will be overwhelmed.
Your fellow citizens will be treated in the hallways.
Exhausted healthcare workers will break down. Some will die.
They will have to decide which patient gets the oxygen and which one dies.
The only way to prevent this is social distancing today. Not tomorrow. Today.
That means keeping as many people home as possible, starting now.

As a politician, community leader or business leader, you have the power and the responsibility to prevent this.

You might have fears today: What if I overreact? Will people laugh at me? Will they be angry at me? Will I look stupid? Won't it be better to wait for others to take steps first? Will I hurt the economy too much?

But in 2-4 weeks, when the entire world is in lockdown, when the few precious days of social distancing you will have enabled will have saved lives, people won't criticize you anymore: They will thank you for making the right decision.

Ok, let's do this.

Country Growth

The total number of cases grew exponentially until China contained it. But then, it leaked outside, and now it's a pandemic that nobody can stop.

As of today, this is mostly due to Italy, Iran and South Korea:

There are so many cases in South Korea, Italy and Iran that it's hard to see the rest of the countries, but let's zoom in on that corner at the bottom right.

There are dozens of countries with exponential growth rates. As of today, most of them are Western.

If you keep up with that type of growth rate for just a week, this is what you get:

If you want to understand what will happen, or how to prevent it, you need to look at the cases that have already gone through this: China, Eastern countries with SARS experience, and Italy.

This is one of the most important charts.

It shows in orange bars the daily official number of cases in the Hubei province: How many people were diagnosed that day.

The grey bars show the true daily coronavirus cases. The Chinese CDC found these by asking patients during the diagnostic when their symptoms started.

Crucially, these true cases weren't known at the time. We can only figure them out looking backwards: The authorities don't know that somebody just started having symptoms. They know when somebody goes to the doctor and gets diagnosed.

What this means is that the orange bars show you what authorities knew, and the grey ones what was really happening.

On January 21st, the number of new diagnosed cases (orange) is exploding: there are around 100 new cases. In reality, there were 1,500 new cases that day, growing exponentially. But the authorities didn't know that. What they knew was that suddenly there were 100 new cases of this new illness.

Two days later, authorities shut down Wuhan. At that point, the number of diagnosed daily new cases was ~400. Note that number: they made a decision to close the city with just 400 new cases in a day. In reality, there were 2,500 new cases that day, but they didn't know that.

The day after, another 15 cities in Hubei shut down.

Up until Jan 23rd, when Wuhan closes, you can look at the grey graph: it's growing exponentially. True cases were exploding. As soon as Wuhan shuts down, cases slow down. On Jan 24th, when another 15 cities shut down, the number of true cases (again, grey) grinds to a halt. Two days later, the maximum number of true cases was reached, and it has gone down ever since.

Note that the orange (official) cases were still growing exponentially: For 12 more days, it looked like this thing was still exploding. But it wasn't. It's just that the cases were getting stronger symptoms and going to the doctor more, and the system to identify them was stronger.

This concept of official and true cases is important. Let's keep it in mind for later.

The rest of regions in China were well coordinated by the central government, so they took immediate and drastic measures. This is the result:

Every flat line is a Chinese region with coronavirus cases. Each one had the potential to become exponential, but thanks to the measures happening just at the end of January, all of them stopped the virus before it could spread.

Meanwhile, South Korea, Italy and Iran had a full month to learn, but didn't. They started the same exponential growth of Hubei and passed every other Chinese region before the end of February.

Eastern Countries

South Korea cases have exploded, but have you wondered why Japan, Taiwan, Singapore, Thailand or Hong Kong haven't?

Taiwan didn't even make it to this graph because it didn't have the 50 cases threshold that I used.

Many of them were hit by SARS in 2003, and all of them learned from it. They learned how viral and lethal it could be, so they knew to take it seriously. That's why all of their graphs, despite starting to grow much earlier, still don't look like exponentials.

So far, we have stories of coronavirus exploding, governments realizing the threat, and containing them. For the rest of the countries, however, it's a completely different story.

Before I jump to them, a note about South Korea: The country is probably an outlier. The coronavirus was contained for the first 30 cases. Patient 31 was a super-spreader who passed it to thousands of other people. Because the virus spreads before people show symptoms, by the time the authorities realized the issue, the virus was out there. They're now paying the consequences of that one instance. Their containment efforts show, however: Italy has already passed it in numbers of cases, and Iran will pass it tomorrow (3/10/2020).

Washington State

You've already seen the growth in Western countries, and how bad forecasts of just one week look like. Now imagine that containment doesn't happen like in Wuhan or in other Eastern countries, and you get a colossal epidemic.

Let's look at a few cases, such as Washington State, the San Francisco Bay Area, Paris and Madrid.

Washington State is the US's Wuhan.The number of cases there is growing exponentially. It's currently at 140.

But something interesting happened early on. The death rate was through the roof. At some point, the state had 3 cases and one death.

We know from other places that the death rate of the coronavirus is anything between 0.5% and 5% (more on that later). How could the death rate be 33%?

It turned out that the virus had been spreading undetected for weeks. It's not like there were only 3 cases. It's that authorities only knew about 3, and one of them was dead because the more serious the condition, the more likely somebody is to be tested.

This is a bit like the orange and grey bars in China: Here they only knew about the orange bars (official cases) and they looked good: just 3. But in reality, there were hundreds, maybe thousands of true cases.

This is an issue: You only know the official cases, not the true ones. But you need to know the true ones. How can you estimate the true ones? It turns out, there's a couple of ways. And I have a model for both, so you can play with the numbers too ( direct link to copy of the model).

First, through deaths. If you have deaths in your region, you can use that to guess the number of true current cases. We know approximately how long it takes for that person to go from catching the virus to dying on average ( 17.3 days). That means the person who died on 2/29 in Washington State probably got infected around 2/12.

Then, you know the mortality rate. For this scenario, I'm using 1% (we'll discuss later the details). That means that, around 2/12, there were already around ~100 cases in the area (of which only one ended up in death 17.3 days later).

Now, use the average doubling time for the coronavirus (time it takes to double cases, on average). It's 6.2. That means that, in the 17 days it took this person to die, the cases had to multiply by ~8 (=2^(17/6)). That means that, if you are not diagnosing all cases, one death today means 800 true cases today.

Washington state has today 22 deaths. With that quick calculation, you get ~16,000 true coronavirus cases today. As many as the official cases in Italy and Iran combined.

If we look into the detail, we realize that 19 of these deaths were from one cluster, which might not have spread the virus widely. So if we consider those 19 deaths as one, the total deaths in the state is four. Updating the model with that number, we still get ~3,000 cases today.

This approach from Trevor Bedford looks at the viruses themselves and their mutations to assess the current case count.

The conclusion is that there are likely ~1,100 cases in Washington state right now.

None of these approaches are perfect, but they all point to the same message: We don't know the number of true cases, but it's much higher than the official one. It's not in the hundreds. It's in the thousands, maybe more.
San Francisco Bay Area
Until 3/8, the Bay Area didn't have any death. That made it hard to know how many true cases there were. Officially, there were 86 cases. But the US is vastly undertesting because it doesn't have enough kits. The country decided to create their own test kit, which turned out not to work.

These were the number of tests carried out in different countries by March 3rd:

Turkey, with no cases of coronavirus, had 10 times the testing per inhabitant than the US. The situation is not much better today, with ~8,000 tests performed in the US, which means ~4,000 people have been tested.

Here, you can just use a share of official cases to true cases. How to decide which one? For the Bay Area, they were testing everybody who had traveled or was in contact with a traveler, which means that they knew most of the travel-related cases, but none of the community spread cases. By having a sense of community spread vs. travel spread, you can know how many true cases there are.

I looked at that ratio for South Korea, which has great data. By the time they had 86 cases, the % of them from community spread was 86% (86 and 86% are a coincidence).

With that number, you can calculate the number of true cases. If the Bay Area has 86 cases today, it is likely that the true number is ~600.

France and Paris

France claims 1,400 cases today and 30 deaths. Using the two methods above, you can have a range of cases: between 24,000 and 140,000.

The true number of coronavirus cases in France today is likely to be between 24,000 and 140,000.

Let me repeat that: the number of true cases in France is likely to be between one and two orders or magnitude higher than it is officially reported.

Don't believe me? Let's look at the Wuhan graph again.

If you stack up the orange bars until 1/22, you get 444 cases. Now add up all the grey bars. They add up to ~12,000 cases. So when Wuhan thought it had 444 cases, it had 27 times more. If France thinks it has 1,400 cases, it might well have tens of thousands

The same math applies to Paris. With ~30 cases inside the city, the true number of cases is likely to be in the hundreds, maybe thousands. With 300 cases in the Ile-de-France region, the total cases in the region might already exceed tens of thousands.

Spain and Madrid

Spain has very similar numbers as France (1,200 cases vs. 1,400, and both have 30 deaths). That means the same rules are valid: Spain has probably upwards of 20k true cases already.

In the Comunidad de Madrid region, with 600 official cases and 17 deaths, the true number of cases is likely between 10,000 and 60,000.

If you read these data and tell yourself: " Impossible, this can't be true ", just think this: With this number of cases, Wuhan was already in lockdown.

With the number of cases we see today in countries like the US, Spain, France, Iran, Germany, Japan, Netherlands, Denmark, Sweden or Switzerland, Wuhan was already in lockdown.

And if you're telling yourself: " Well, Hubei is just one region ", let me remind you that it has nearly 60 million people, bigger than Spain and about the size of France.

So the coronavirus is already here. It's hidden, and it's growing exponentially.

What will happen in our countries when it hits? It's easy to know, because we already have several places where it's happening. The best examples are Hubei and Italy.

Fatality Rates

The World Health Organization (WHO) quotes 3.4% as the fatality rate (% people who contract the coronavirus and then die). This number is out of context so let me explain it.

It really depends on the country and the moment: between 0.6% in South Korea and 4.4% in Iran. So what is it? We can use a trick to figure it out.

The two ways you can calculate the fatality rate is Deaths/Total Cases and Death/Closed Cases. The first one is likely to be an underestimate, because lots of open cases can still end up in death. The second is an overestimate, because it's likely that deaths are closed quicker than recoveries.

What I did was look at how both evolve over time. Both of these numbers will converge to the same result once all cases are closed, so if you project past trends to the future, you can make a guess on what the final fatality rate will be.

This is what you see in the data. China's fatality rate is now between 3.6% and 6.1%. If you project that in the future, it looks like it converges towards ~3.8%-4%. This is double the current estimate, and 30 times worse than the flu.

It is made up of two completely different realities though: Hubei and the rest of China.

Hubei's fatality rate will probably converge towards 4.8%. Meanwhile, for the rest of China, it will likely converge to ~0.9%:

I also charted the numbers for Iran, Italy and South Korea, the only countries with enough deaths to make this somewhat relevant.

Iran's and Italy's Deaths / Total Cases are both converging towards the 3%-4% range. My guess is their numbers will end up around that figure too.

South Korea is the most interesting example, because these 2 numbers are completely disconnected: deaths / total cases is only 0.6%, but deaths / closed cases is a whopping 48%. My take on it is that a few unique things are happening there. First, they're testing everybody (with so many open cases, the death rate seems low), and leaving the cases open for longer (so they close cases quickly when the patient is dead). Second, they have a lot of hospital beds (see chart 17.b). There might also be other reasons we don't know. What is relevant is that deaths/cases has hovered around 0.5% since the beginning, suggesting it will stay there, likely heavily influenced by the healthcare system and crisis management.

The last relevant example is the Diamond Princess cruise: with 706 cases, 6 deaths and 100 recoveries, the fatality rate will be between 1% and 6.5%.

Note that the age distribution in each country will also have an impact: Since mortality is much higher for older people, countries with an aging population like Japan will be harder hit on average than younger countries like Nigeria. There are also weather factors, especially humidity and temperature, but it's still unclear how this will impact transmission and fatality rates.

This is what you can conclude:

Excluding these, countries that are prepared will see a fatality rate of ~0.5% (South Korea) to 0.9% (rest of China).

Countries that are overwhelmed will have a fatality rate between ~3%-5%

Put in another way: Countries that act fast can reduce the number of deaths by a factor of ten. And that's just counting the fatality rate. Acting fast also drastically reduces the cases, making this even more of a no-brainer.

Countries that act fast reduce the number of deaths at least by 10x.

So what does a country need to be prepared?

What Will Be the Pressure on the System

Around 20% of cases require hospitalization, 5% of cases require the Intensive Care Unit (ICU), and around 2.5% require very intensive help, with items such as ventilators or ECMO ( extra-corporeal oxygenation).

The problem is that items such as ventilators and ECMO can't be produced or bought easily. A few years ago, the US had a total of 250 ECMO machines, for example.

So if you suddenly have 100,000 people infected, many of them will want to go get tested. Around 20,000 will require hospitalization, 5,000 will need the ICU, and 1,000 will need machines that we don't have enough of today. And that's just with 100,000 cases.

That is without taking into account issues such as masks. A country like the US has only 1% of the masks it needs to cover the needs of its healthcare workers (12M N95, 30M surgical vs. 3.5B needed). If a lot of cases appear at once, there will be masks for only 2 weeks.

Countries like Japan, South Korea, Hong Kong or Singapore, as well as Chinese regions outside of Hubei, have been prepared and given the care that patients need.

But the rest of Western countries are rather going in the direction of Hubei and Italy. So what is happening there?

What an Overwhelmed Healthcare System Looks Like

The stories that happened in Hubei and those in Italy are starting to become eerily similar. Hubei built two hospitals in ten days, but even then, it was completely overwhelmed.

Both complained that patients inundated their hospitals. They had to be taken care of anywhere: in hallways, in waiting rooms...

I heavily recommend this short Twitter thread. It paints a pretty stark picture of Italy today

Healthcare workers spend hours in a single piece of protective gear, because there's not enough of them. As a result, they can't leave the infected areas for hours. When they do, they crumble, dehydrated and exhausted. Shifts don't exist anymore. People are driven back from retirement to cover needs. People who have no idea about nursing are trained overnight to fulfill critical roles. Everybody is on call, always.

Francesca Mangiatordi, an Italian nurse that crumbled in the middle of the war with the Coronavirus

That is, until they become sick. Which happens a lot, because they're in constant exposure to the virus, without enough protective gear. When that happens, they need to be in quarantine for 14 days, during which they can't help. Best case scenario, 2 weeks are lost. Worst case, they're dead.

The worst is in the ICUs, when patients need to share ventilators or ECMOs. These are in fact impossible to share, so the healthcare workers must determine what patient will use it. That really means, which one lives and which one dies.

"After a few days, we have to choose. [...] Not everyone can be intubated. We decide based on age and state of health." - Christian Salaroli, Italian MD.

Medical workers wear protective suits to attend to people sickened by the novel coronavirus, in the intensive care unit of a designated hospital in Wuhan, China, on Feb. 6. (China Daily/Reuters), via Washington Post

All of this is what drives a system to have a fatality rate of ~4% instead of ~0.5%. If you want your city or your country to be part of the 4%, don't do anything today.

Satellite images show Behesht Masoumeh cemetery in the Iranian city of Qom. Photograph: ©2020 Maxar Technologies. Via The Guardian and the The New York Times.

Flatten the Curve

This is a pandemic now. It can't be eliminated. But what we can do is reduce its impact.

Some countries have been exemplary at this. The best one is Taiwan, which is extremely connected with China and yet still has as of today fewer than 50 cases. This recent paper explain all the measures they took early on, which were focused on containment.

They have been able to contain it, but most countries lacked this expertise and didn't. Now, they're playing a different game: mitigation. They need to make this virus as inoffensive as possible.

If we reduce the infections as much as possible, our healthcare system will be able to handle cases much better, driving the fatality rate down. And, if we spread this over time, we will reach a point where the rest of society can be vaccinated, eliminating the risk altogether. So our goal is not to eliminate coronavirus contagions. It's to postpone them.

The more we postpone cases, the better the healthcare system can function, the lower the mortality rate, and the higher the share of the population that will be vaccinated before it gets infected.

How do we flatten the curve?

Social Distancing

There is one very simple thing that we can do and that works: social distancing.

If you go back to the Wuhan graph, you will remember that as soon as there was a lockdown, cases went down. That's because people didn't interact with each other, and the virus didn't spread.

The current scientific consensus is that this virus can be spread within 2 meters (6 feet) if somebody coughs. Otherwise, the droplets fall to the ground and don't infect you.

The worst infection then becomes through surfaces: The virus survives for up to 9 days on different surfaces such as metal, ceramics and plastics. That means things like doorknobs, tables, or elevator buttons can be terrible infection vectors.

The only way to truly reduce that is with social distancing: Keeping people home as much as possible, for as long as possible until this recedes.

This has already been proven in the past. Namely, in the 1918 flu pandemic.

Learnings from the 1918 Flu Pandemic

You can see how Philadelphia didn't act quickly, and had a massive peak in death rates. Compare that with St Louis, which did.

Then look at Denver, which enacted measures and then loosened them. They had a double peak, with the 2nd one higher than the first.

If you generalize, this is what you find:

This chart shows, for the 1918 flu in the US, how many more deaths there were per city depending on how fast measures were taken. For example, a city like St Louis took measures 6 days before Pittsburgh, and had less than half the deaths per citizen. On average, taking measures 20 days earlier halved the death rate.

Italy has finally figured this out. They first locked down Lombardy on Sunday, and one day later, on Monday, they realized their mistake and decided they had to lock down the entire country.

Hopefully, we will see results in the coming days. However, it will take one to two weeks to see. Remember the Wuhan graph: there was a delay of 12 days between the moment when the lockdown was announced and the moment when official cases (orange) started going down.

How Can Politicians Contribute to Social Distancing?

The question politicians are asking themselves today is not whether they should do something, but rather what's the appropriate action to take.

There are several stages to control an epidemic, starting with anticipation and ending with eradication. But it's too late for most options today. With this level of cases, the only options politicians have in front of them are containment, mitigation or suppression.
Containment
Containment is making sure all the cases are identified, controlled, and isolated. It's what Singapore, South Korea or Taiwan are doing so well: They very quickly limit people coming in, identify the sick, immediately isolate them, use heavy protective gear to protect their health workers, track all their contacts, quarantine them... This works extremely well when you're prepared and you do it early on, and don't need to grind your economy to a halt to make it happen.

I've already touted Taiwan's approach. But China's is good too. The lengths at which it went to contain the virus are mind-boggling. For example, they had up to 1,800 teams of 5 people each tracking every infected person, everybody they got interacted with, then everybody those people interacted with, and isolating the bunch. That's how they were able to contain the virus across a billion-people country.

This is not what Western countries have done. And now it's too late. The recent US announcement that most travel from Europe was banned is a containment measure for a country that has, as of today, 3 times the cases that Hubei had when it shut down, growing exponentially. How can we know if it's enough? It turns out, we can know by looking at the Wuhan travel ban.

This chart shows the impact that the Wuhan travel ban had delaying the epidemic. The bubble sizes show the number of daily cases. The top line shows the cases if nothing is done. The two other lines show the impact if 40% and 90% of travel is eliminated. This is a model created by epidemiologists, because we can't know for sure.

If you don't see much difference, you're right. It's very hard to see any change in the development of the epidemic.

Researchers estimate that, all in all, the Wuhan travel ban only delayed the spread in China by 3-5 days.

Now what did researchers think the impact of reducing transmission would be?

The top bloc is the same as the one you've seen before. The two other blocks show decreasing transmission rates. If the transmission rate goes down by 25% (through Social Distancing), it flattens the curve and delays the peak by a whole 14 weeks. Lower the transition rate by 50%, and you can't see the epidemic even starting within a quarter.

The US administration's ban on European travel is good: It has probably bought us a few hours, maybe a day or two. But not more. It is not enough. It's containment when what's needed is mitigation.

Once there are hundreds or thousands of cases growing in the population, preventing more from coming, tracking the existing ones and isolating their contacts isn't enough anymore. The next level is mitigation or suppression.
Mitigation or Suppression The new article, Coronavirus: The Hammer and the Dance, covers mitigation vs. suppression at length.
Mitigation requires a heavy amount of testing, contact tracing, quarantines and isolations to flatten the curve without stopping the outbreak

Suppression tries to go one step further and quench the outbreak. It requires heavy social distancing. People need to stop hanging out to drop the transmission rate (R), from the R=~2-3 that the virus follows without measures, to below 1, so that it eventually dies out.

These measures require closing companies, shops, mass transit, schools, enforcing lockdowns... The worse your situation, the worse the social distancing. The earlier you impose heavy measures, the less time you need to keep them, the easier it is to identify brewing cases, and the fewer people get infected.

This is what Wuhan had to do. This is what Italy was forced to accept. And then France, Spain, and many other countries. Because when the virus is rampant, the only measure is to lock down all the infected areas to stop spreading it at once.

With thousands of official cases - and tens of thousands of true ones - this is what countries like the US, the UK, Germany, Netherlands or Switzerland need to do.

But they're not doing it.

Some business are working from home, which is fantastic.
Some mass events are being stopped.
Some affected areas are in quarantining themselves.

Nobody can enter or exit lockdown areas, unless there are proven family or work reasons.

Movement inside the areas is to be avoided, unless they are justified for urgent personal or work reasons and can't be postponed.

People with symptoms (respiratory infection and fever) are "highly recommended" to remain home.

Standard time off for healthcare workers is suspended

Closure of all educational establishments (schools, universities...), gyms, museums, ski stations, cultural and social centers, swimming pools, and theaters.

Bars and restaurants have limited opening times from 6am to 6pm, with at least one meter (~3 feet) distance between people.

All pubs and clubs must close.

All commercial activity must keep a distance of one meter between customers. Those that can't make it happen must close. Temples can remain open as long as they can guarantee this distance.

Family and friends hospital visits are limited

Work meetings must be postponed. Work from home must be encouraged.

All sports events and competitions, public or private, are canceled. Important events can be held under closed doors.

All these measures will slow down the virus. They will lower the transmission rate from 2.5 to 2.2, maybe 2. Hopefully more. But they aren't enough to get us below 1 for a sustained period of time to stop the epidemic.

So the question becomes: What are the tradeoffs we could be making to lower the R? This is the menu that Italy has put in front of all of us:

Then two days later, they added: No, in fact, you need to close all businesses that aren't crucial. So now we're closing all commercial activities, offices, cafes and shops. Only transportation, pharmacies, groceries will remain open."

How to pick the right measures for your country? Read Coronavirus: The Hammer and the Dance. One approach is to gradually increase measures. Unfortunately, that gives precious time for the virus to spread. If you want to be safe, do it Wuhan style. People might complain now, but they'll thank you later.

How Can Business Leaders Contribute to Social Distancing?

If you're a business leader and you want to know what you should do, the best resource for you is Staying Home Club.

It is a list of social distancing policies that have been enacted by US tech companies-so far, 328.

They range from allowed to required Work From Home, and restricted visits, travel, or events.

There are more things that every company must determine, such as what to do with hourly workers, whether to keep the office open or not, how to conduct interviews, what to do with the cafeterias... If you want to know how my company, Course Hero, handled some of these, along with a model announcement to your employees, here is the one my company used ( view only version here).

It is very possible that so far you've agreed with everything I've said, and were just wondering since the beginning when to make each decision. Put in another way, what triggers should we have for each measure.

Risk-Based Model for Triggers

To solve this, I've created a model ( direct link to copy).

If your company had 100 employees in the Washington state area, which had 11 coronavirus deaths on 3/8, there was a 25% chance at least one of your employees was infected, and you should have closed immediately.

If your company had 250 employees mostly in the South Bay (San Mateo and Santa Clara counties, which together had 22 official cases on 3/8 and the true number was probably at least 54), by 3/9 you would have had ~2% chances to have at least one employee infected, and you should have closed your office too.

[Updated as of 3/12] If your company is in Paris (intramuros), and it has 250 employees, today there's a 95% chance that one of your employees has the coronavirus, and you should close your office by tomorrow.

It enables you to assess the likely number of cases in your area, the probability that your employees are already infected, how that evolves over time, and how that should tell you whether to remain open.

It tells us things like:

The model uses labels such as "company" and "employee", but the same model can be used for anything else: schools, mass transit... So if you have only 50 employees in Paris, but all of them are going to take the train, coming across thousands of other people, suddenly the likelihood that at least one of them will get infected is much higher and you should close your office immediately.

If you're still hesitating because nobody is showing symptoms, just realize 26% of contagions happen before there are symptoms.

Are You Part of a Group of Leaders?

This math is selfish. It looks at every company's risk individually, taking as much risk as we want until the inevitable hammer of the coronavirus closes our offices.

But if you're part of a league of business leaders or politicians, your calculations are not for just one company, but for the whole. The math becomes: What's the likelihood that any of our companies is infected? If you're a group of 50 companies of 250 employees on average, in the SF Bay Area, there's a 35% chance that at least one of the companies has an employee infected, and 97% chance that will be true next week. I added a tab in the model to play with that.

It might feel scary to make a decision today, but you shouldn't think about it this way.

This theoretical model shows different communities: one doesn't take social distancing measures, one takes them on Day n of an outbreak, the other one on Day n+1. All the numbers are completely fictitious (I chose them to resemble what happened in Hubei, with ~6k daily new cases at the worst). They're just there to illustrate how important a single day can be in something that grows exponentially. You can see that the one-day delay peaks later and higher, but then daily cases converge to zero.

But what about cumulative cases?

In this theoretical model that resembles loosely Hubei, waiting one more day creates 40% more cases! So, maybe, if the Hubei authorities had declared the lockdown on 1/22 instead of 1/23, they might have reduced the number of cases by a staggering 20k.

And remember, these are just cases. Mortality would be much higher, because not only would there be directly 40% more deaths. There would also be a much higher collapse of the healthcare system, leading to a mortality rate up to 10x higher as we saw before. So a one-day difference in social distancing measures can end exploding the number of deaths in your community by multiplying more cases and higher fatality rate.

This is an exponential threat. Every day counts. When you're delaying by a single day a decision, you're not contributing to a few cases maybe. There are probably hundreds or thousands of cases in your community already. Every day that there isn't social distancing, these cases grow exponentially.

This is probably the one time in the last decade that sharing an article might save lives. They need to understand this to avert a catastrophe. The moment to act is now.

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With everything that's happening about the Coronavirus, it might be very hard to make a decision of what to do today. Should you wait for more information? Do something today? What? Here's what I'm going to cover in this article, with lots of charts, data and models with plenty of sources: How many cases of coronavirus will there be in your area?

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What the US Federal Government and the States Should Do to Fight the Coronavirus

My two previous articles, Summary: It makes political and economic sense for the US to suppress the coronavirus. For that, states and the federal government each have their own roles that they need to adjust. Coronavirus: Why You Must Act Now and

1. What's the situation in the US and its states

2. Why the coronavirus should be a bipartisan issue

3. The economics of controlling the virus

4. Which decisions should be left to the federal government or to states

The Hammer and the Dance, have gathered over 50 million views together and have been translated into over 30 languages each. This article focuses on the situation in the US as of March 31st 2020.
The US is now the country with most coronavirus cases in the world. It is likely to keep that title in the history books. Two key reasons are government decentralization and concerns about the economic impact of aggressive social distancing measures.

Here's what we're going to cover today, with a lot of data, charts and sources:

Here's what you'll take away:

The coronavirus is growing everywhere in the US.
Some states are on their way to controlling it.
Others have massive outbreaks that make China's outbreak pale in comparison.
Many are unprepared, and will suffer some of the worst outbreaks.
All voters care about this, Democrats and Republicans.
Democrats were hit first.
But Republicans have more to lose.
They're older and more likely to die.
Most hesitation comes from the perceived cost of suppressing the virus.
Fortunately, it's cheaper to suppress it than to let it run loose.
We should do it.
But right now, states are left fending for themselves. It's a mess.
They are competing against each other instead of collaborating.
They might be forced to seal their borders with each other.
There is a role for states and a role for the federal government. The federal government coordinates, the states execute.
If both step up, we will save lives and increase the GDP.

OK, let's do this.

A few weeks ago, I shared this graph to alert people of what was to come in other countries.

This is an update four weeks later on all these countries that appeared so small above:

In the previous graph I showed countries with 50 cases or more. Now I'm showing countries with 1000 cases or more. There's 181 countries with coronavirus cases, or over 90% of the total.

Note that now I'm adding China, which tells you how bad the situation is. The vertical axis has gone from a maximum of 6,000 to 200,000. A factor of 33x in four weeks. We quickly forget these orders of magnitude, but it's worth remembering: three weeks ago, the US had fewer than 1,000 cases and there was still a debate of whether there would be an epidemic. This is what exponential growth looks like.

And you can see the trajectory.

It's not good.

Let's zoom in, looking at the state level.

New York used to dwarf everything else, but now New Jersey is joining it. Note that as of 3/31, only four countries have more cases than New York. And it's still adding thousands of cases a day.

Remember how we zoomed in to the bottom right corner to see the emerging coronavirus countries? Let's do that again, this time with states, taking New York and New Jersey out.

Oh, and just for context, this is the point at which Hubei shut down.

I use absolute numbers (total cases) instead of relative numbers (cases per capita) because here we're trying to assess whether there's an outbreak or not. Absolute numbers show if there's a cluster and how big it is. Per capita doesn't show this. Eg, if Liechtenstein had 5 cases, it would look like a national emergency in relative numbers, but it's nothing. When assessing outbreaks, absolute numbers are more relevant. When assessing how bad the situation was a posteriori, relative numbers will be more relevant. The other reason is that relative numbers are much harder to process.

From now on, I'm going to use "Hubeis" as a measure, because everybody has a good sense of what happened there. A "Hubei" is a region that has more cases than Hubei when it was shut down. Hubei shut down with 444 confirmed cases, and ended up with close to 70,000 cases and 3,200 deaths. As a rule of thumb, a region that has more cases than Hubei but hasn't taken the same measures as Hubei at least as early as them is very likely to end up with both more cases and more deaths than Hubei.

So now we have 33 states (34 including DC) with more cases than Hubei when it shut down (accounting for 92% of US GDP). I had to rebuild these charts 3 times in 5 days because they quickly became outdated. There were "only" 13 Hubeis in the US on Friday; now there are 33.

Here's a geographic visualization of all the counties where there are cases.

But that's not real cases. It's just official ones. How close are official cases from real cases? It depends on how much you test:

This chart shows the share of tests that are positive. In the case of Spain, with 50% of cases positive, it's very likely that they are missing a lot of cases. As a result, it's very likely that Spain has many more cases than the 100,000 it reports.

We can see that countries that are doing a good job at controlling the virus understand the situation because they identify most cases. Vietnam, Taiwan, Singapore, South Korea and Germany all have less than 4% positives. They are still probably undercounting, but probably not by much.

So what does this look like in the US?

There are a few states that have good enough testing to be close to the true number of cases: New Mexico, Hawaii, the Dakotas, and Minnesota have testing levels similar to South Korea's. But all of them also have few cases. As soon as a state has an outbreak, it gets overwhelmed, can't keep up with tests, and undercounts the true number of cases.

So how can states assess how many cases they truly have?

Assuming a fatality rate of 1% (one in 100 cases dies), you can back out one estimate of true cases:

This approximation would double the number of official cases, from ~200,000 officially today, to ~400,000. This is still likely to be an underestimate, because people take on average 3 weeks to die from the coronavirus.

This forgets time-to-death. If instead we use the back-of-the-envelope calculation from previous posts, where one death today means 100 cases three weeks ago (1% fatality rate, and it takes 3 weeks on average from contagion to death), and these double every week for three weeks, so they end up becoming 800 cases today, the situation becomes much more dire. Even if we assume cases doubled only two times in the last two weeks because of social distancing measures, this is what we see:

According to this, more than a million people are already infected in the US, and most states would have thousands of cases. Because I used two doublings instead of three, this is likely still an underestimate.

So let's summarize so far: we are in a situation where the US has 33 states with more cases than Hubei, and probably many more, but it has no way to know for sure because it's not testing enough.

You might have noted that, as a rule of thumb, the states that have more cases lean Democrat.

The Coronavirus Hit Urban Areas First

Big urban areas are usually more connected to the rest of the world via travel. That means they've imported more cases, faster.

They also have a higher urban density, which means a higher transmission rate of the virus. The more people are close by, the more you meet every day, and the faster the virus spreads.

Because the vote in urban areas tends to lean more Democrat, states controlled by Democratic governors today have been impacted by the virus earlier, so they have taken measures earlier. It's not a coincidence that New York is Ground Zero for the coronavirus in the U.S., and that the San Francisco Bay Area was initially among the worst impacted. Maybe that's why San Francisco ordered a shelter in place on 3/16, California on 3/19, and New York on 3/20 - well before other major cities and states.

The fact that democratic-leaning states have been hit earlier explains why Democrat voters have been worried about the coronavirus earlier. As more and more cases have appeared in different states, concerns about the virus have grown on both sides.

Source: Civiqs, via the New York Times

This chart was only updated two weeks ago. What does that polarization look like today?

Now, both parties are equally concerned. That's important, because the virus is about to hit Republican states hard.

The Coronavirus Will Hit Republicans Too

This is the growth of Coronavirus cases in states that have a Republican governor today:

There are 16 Hubeis among Republican states (states with more cases than Hubei when it shut down). With the current growth rates, by next week there will be 22. As a reminder, Hubei ended up with over 70,000 cases and 3,000 deaths.

Not surprisingly, both Democrat-leaning and Republican-leaning voters strongly advocate for measures to curb the virus:

Link to article

It is notable that a majority of voters from both parties support every single one of the measures above. Voters want tough measures against the coronavirus.

So what measures are Republican-controlled states taking?

Coronavirus Measures in Republican-Controlled States
Details of measures per state can also be found at the Kaiser Family Foundation site. Updated as of 3/29/2020
In a thoughtful decision, all fifty states have at least issued a State Emergency Declaration, and many are much stricter. For example, Alaska, despite a very low population density, has mandated strong measures, such as a shelter-in-place, travel bans, and wide business closures. West Virginia established a shelter in place with just 40 cases.These measures make sense given the unique challenges of delivering healthcare across Alaska and the fact that West Virginia has been ranked 44th in overall health and 48th in clinical care.

But most are still very short of the measures they need to take. For example, Florida still has no ban for large gatherings, no business closures, and no stay-at-home orders beyond quarantines for travelers. Yet it leads all other Republican-controlled states in terms of cases. Even worse, Florida has just exported back across the United States countless spring breakers who hung out together in mass gatherings, especially on beaches the state refused to close.

Georgia, another leading state in terms of cases, has taken similar measures to Florida, except that bars and restaurants are still open with limited service, and high-risk groups are asked to stay home.

Meanwhile, Mississippi, with nearly 1,000 cases, requires a fever of 100.4 AND severe cough or chest pain to receive testing, and on March 24th, the governor reversed non-essential shutdowns applied by local jurisdictions.

Countries like South Korea or Singapore can get away with light social distancing measures because they have extensive testing, contact tracing, quarantines, isolations and travel bans: thanks to these measures, they can quickly identify cases and prevent them from infecting others.

That is not the case for many of these states. As we saw, most have poor testing. Contact tracing is worse: no state in the US has a good process as of today. That's why most states need to apply The Hammer - a strategy of heavy social distancing for a few weeks - to control the virus and buy themselves time to set up these measures. But many states aren't doing that either, especially when governed by Republican governors:

Chart updated as of 3/29/2020

Republican-controlled states have had a huge advantage: They have seen what has happened to their Democratic-controlled brethren, but because they are on average more rural, the coronavirus took time to reach them. But it will reach them. Some rural states, like Alaska or Idaho, have taken advantage of this delay. Others, like Oklahoma, Mississippi or Missouri, are not taking enough measures to contain the virus: It will continue spreading invisibly, infecting the people of these states.
Update: the states of Mississippi, Nevada, Georgia and Florida mandated statewide directives for citizens to stay home the same day as this article was published.
State lawmakers consider many things when deciding what measures to take, primarily health and the economy. Another factor that is surely in their mind, but isn't discussed much, is political calculation.

The Coronavirus Kills Republican-Leaning Voters More

Most readers are acquainted with fatality rates per age group:

What I haven't seen much is the overlap of this graph with partisanship:

The older you are, the more likely you are to both vote Republican and die from the coronavirus. Voters aged 80+ are 80 times more likely to die from the coronavirus than those under 40 (16% fatality rate vs. ~0.2%).

This effect is strong enough that people who voted for Trump in the 2016 election are around 30% more likely to die from the coronavirus than Democrats. In some swing states from the 2016 election, such as Pennsylvania, if the coronavirus were to run wild, this effect alone could have wiped out up to 30% of the gap between Republicans and Democrats in the 2016 election.

This graph shows how flu epidemics impact 600 US cities based on their size. Bigger cities are more to the right and have bigger circles, so the small bubbles on the left show smaller cities. The vertical axis represents how concentrated the flu season is in particular weeks. We can see that big cities concentrate at the bottom right, which means their epidemics are spread over many weeks. Conversely, the smaller cities are, the more they tend to be at the top left, meaning their epidemics are concentrated in fewer weeks. This is believed to be caused partially by the fact that there is always some transmission, and hence ongoing herd immunity, in urban areas. This won't be the case with the coronavirus, since there's no herd immunity yet, but what this does illustrate is that smaller cities don't get spared because they're small. They do get hit, and when they do, the epidemic also hits hard.

This shows the loss of voters from coronavirus deaths. It doesn't account for other effects, such as the votes of the family members of the deceased who might be angry at politicians for the avoidable death of their loved ones, or collateral damage of people who might die due to a collapsed healthcare system, or the family members of those people, or other secondary effects.

Many other factors will hurt rural voters more than urban ones. For example, the healthcare system has much less capacity in rural areas. The rural population tends to have worse health, so a higher likelihood of comorbidities that increase the fatality rate of coronavirus. On top of that, they don't even get more spared by infections: the flu season tends to be delayed in rural areas compared to urban ones, but when it hits, it hits much harder.

1. Mitigation: Take some measures now but don't be too aggressive. Just flatten the curve, go through the epidemic, build herd immunity, and go back to business as usual. This has the benefit of avoiding an economic shock early on because the economy doesn't shut down for a few weeks or months. But during the epidemic, people will avoid going to work or consuming, for fear of getting infected. That ongoing panic can strain the economy for as long as people believe the epidemic is uncontrolled.

2. Suppression (The Hammer and the Dance): Apply a "Hammer" early on and shut down the economy for a few weeks or months. That will bring infections to nearly zero while giving time to organize everything, from testing to contact tracing. Once testing data indicates it's safe, move towards the "Dance," a period during which social distancing measures are reduced, but some measures might still be needed nevertheless, depending on the situation.

To the extent Republican governors are hesitating to declare strict containment measures for political reasons, it will eventually become clear that they got the politics exactly backwards: instituting stricter measures early-on would have helped keep their most loyal voters alive.

The main hesitance of some American policymakers to take strong, early action against the coronavirus comes from economic tradeoffs between two very different approaches.

Both approaches have ramifications and costs. For example, the heavy psychological toll of the fear of the virus or the loss of a job can depress consumers and their income, reducing their spending. The resulting demand shock could put companies out of business if they don't have enough cash and banks don't want to lend. If too many of these companies go out of business, the financial system itself could be imperiled. Consumers, particularly shocked by losses in their retirement accounts could significantly increase their savings rate - which means significantly reducing consumption for years.

So, on the balance, what's the economic impact of each?

The Big Picture of Pandemics

We can go back to normal. BCG and the Harvard Business Review call this "V-shape".

We can go back to growing like we used to, but having lost enough GDP that we never gain that growth back, and take some years to go back to the same level of the economy. We can call this "U-shape".

The slump is big and afterwards there's some lingering issues in the economy and we don't quite go back to the same level of GDP growth. We can call this "L-shape".

Before we jump into the comparison, it's useful to take a step back and put the entire pandemic thing into economic perspective: How bad is this going to be economically over the next few years? These are the potential scenarios:

There are 3 scenarios:

These can impact the level of the GDP as well as its growth.

Which scenario each country will go through depends on how we react, but in the grand scheme of things, after a year of pain, it is likely that we will go back to normal. Let me explain.

Link to source

A recent analysis showed that the 1918 pandemic reduced GDP per capita of the average country by 6%, and consumption by 8% for a year.

And yet, for most pandemics of the 20th century, the economy went back to normal afterwards.

This is important because it puts the entire discussion into perspective: What we decide today will impact lives and the economy in the short term. There are also risks in the economy today that are different from the past. However, what history teaches us is that, usually, after a pandemic, the economy goes back to normal. The decisions we take will have a tremendous impact this year and next, but economically, in a few years it's likely that the impact will be minimal.

So Which One Is Better, Mitigation or Suppression?

The complexity of mitigation and suppression economic outcomes is such that it's very hard to model. If only there had been a real-life test where we could compare the different strategies...

It turns out, there is.

In the 1918 pandemic, different US cities had different approaches to the pandemic. Some took it easy, like Philadelphia, with measures that came too late and for a short period of time. Other cities, like St Louis, took measures quickly and for a longer period of time.

I've already talked about these cities in the past, but only about fatality rates. A crucial paper that came out on Thursday, March 26th, now also compares their measures with their economic outcomes.

Before showing their results, it's important to ask ourselves: What should we expect to find?

It's crucial to understand this graph. On the horizontal axis, we have mortality. On the vertical one, as a proxy for economic growth, we have the growth in employment. This graph illustrates the hypothesis, not actual data: Red dots are hypothetical cities that impose few social distancing measures, while green dots are cities that take stronger social distancing measures.

This is one of the more complex graphs in this entire article, so let's explain it a bit. Red dots are cities that had weaker social distancing measures than the average city. Green dots are cities that had stronger social distancing measures than the average. The line shows the trend: more mortality meant less employment after the pandemic. The grey area shows the confidence interval: the true trend is likely to be within that area, meaning that it's extremely likely that it was a downward trend. Because the virus hit the East Coast first, cities in the West had time to learn from cities in the East and take stronger, faster measures. That, however, generates a bias. There are more biases, such as that wealthier cities could manage the healthcare crisis better, but might be hit worse by the virus, or cities with more density could be hit more. So researchers controlled for factors such as density, wealth, population... Their controls were the 1910 agriculture employment share, 1910 manufacturing employment share, 1910 urban population share, 1910 income per capita, and log 1910 population.

If indeed social distancing measures had been bad for the economy, what we should see is that cities with higher mortality rates (because they applied measures that were too little too late) had a bigger economic growth in the years after.

Is this what we actually found?

Researchers found the opposite of the hypothesis. "Mitigation", the strategy where the measures taken are weaker, was much worse for the economy than "suppression", heavier social distancing measures.

As you can see, most green dots are at the top left (fewer deaths, more economic growth) and the red dots are at the bottom right (more deaths, less economic growth). Together, they form a trend: the more people died (because there were weaker social distancing measures), the weaker the economy was afterwards.

Not only that, but this was true for both how long measures were taken and how fast they were enacted. And it wasn't just due to losing more workers: It remains true for other economic indicators, such as growth in manufacturing value and growth in national banking assets.

From the charts below, the quick takeaway is that more social distancing measures were better for the economy, no matter how you look at it.

Here are some quotes directly from the paper:

"Our findings suggest that pandemics can have substantial economic costs, and NPIs can have economic merits, beyond lowering mortality"

"Cities that intervened earlier and more aggressively experience a relative increase in real economic activity after the pandemic"

"More severely affected areas experience a relative decline in manufacturing employment, manufacturing output, bank assets, and consumer durables."

"The declines in all outcomes are persistent, and more affected areas remain depressed relative to less exposed areas from 1919 through 1923."

"Reacting 10 days earlier to the arrival of the pandemic in a given city increases manufacturing employment by around 5% in the post period. Likewise, implementing NPIs for an additional 50 days increases manufacturing employment by 6.5% after the pandemic."

Obviously, there are differences between the 1918 flu pandemic and the 2020 coronavirus pandemic: This one affects older people, it has a lower fatality rate, the healthcare system is stronger, people can work from home more, we're much more connected so the virus spreads more quickly everywhere... We don't know what would be true for this pandemic. But... the only economic evidence we have of social distancing measures is that they helped, rather than hurt, the economy.

What other data points can we look at to assess how bad suppression could be for the economy? What about the markets?

How the Chinese Equity Market Valued the Hubei Lockdown

China is the only good example to understand how the markets value a massive outbreak, because it's the only country that has had a huge one and that has (apparently) been able to control it.

When Hubei shut down, the markets panicked. But as soon as they were down, they started going back up again. By the beginning of March, they had gone back to nearly normal, their level before the lockdown, and a similar level as the year before. What that means is that investors believed a full shutdown of an area of 60 million people barely registered in the grand scheme of things.

Only when the coronavirus became a pandemic did investors start worrying again. But what matters here is how they valued the cost of the lockdown. The answer appears to be: Not much.

Incidentally, the day President Trump announced the National Emergency, markets went up.

This is not much information, but we need to realize that we're making decisions that might cost millions of lives with very little data. Any information we have needs to be part of our analysis. And so far, all the evidence we have suggests a suppression strategy would not be more expensive than mitigation, but rather the opposite.

Ok, let's take a step back. Now we have some evidence that:

21st century pandemics have tended to have a short-term effect on the economy

Quicker and longer social distancing measures probably benefit the economy

A lockdown that can control an outbreak was enough to increase the confidence of investors to bring the Chinese stock market back to the levels before the lockdown.

Based on the little we know today, it looks like Suppression is economically better than Mitigation once you have an outbreak.

The Price of a Life

One of the core challenges lawmakers have when comparing Suppression and Mitigation is that tradeoffs between life and money are hard. The major benefit of Suppression, the lives saved, can't be translated into money.

But it can.

We do that all the time. In insurance, pharmacology or healthcare, for example, society has to decide how much a life is worth.

This is a painful reality in healthcare: We don't have infinite resources. We can't, unfortunately, treat everybody for everything. Otherwise, we would go bankrupt. As a society, we are forced to make decisions: How should we spend the limited resources we have? What measures are worth paying for, and which ones are too expensive?

The way we calculate this is by asking ourselves: How much are we willing to pay to extend our life? In healthcare in the US, that number turns out to be between $50,000 and $150,000 per year.

If we assume the average age of death for coronavirus is 78, these people have on average 10 more years to live, which means the average coronavirus patient would pay up to $1.5 million to avoid death (10 years * $150,000 per year).

In my previous post, I explained how direct deaths from a mitigation strategy in the US could range between 500,000 and over 10 million. As a quick back-of-the-envelope reminder, it's the result of assuming the share of the US population that gets infected ranges between 40% and 75%, and the fatality rate ranges between 1% (currently 1.5% in South Korea, the country with some of the best testing and healthcare system) and 4% (Hubei region. Note the current fatality rate in Italy is ~10%, but they are probably undercounting cases). That does not account for collateral damage (other people who die because they don't have access to urgent healthcare), which could greatly increase the death rate.

If we account for how much we value life, the cost of the coronavirus in deaths for the US would be between $750 billion and $15 trillion. For context, that's between 4% and 75% of GDP. The cost in lives would be staggering.

Let's summarize all this information

Notes: some people have asked me how it is possible that the value of some people's lives is comparable to the size of GDP. GDP is broadly the value created in a year, not the total wealth we have. The total wealth we have in the US is approximately $1 million per person on average, which means the US's wealth is ~$320 trillion. That does not account for the wealth in terms of life, but puts the cost of $15 trillion in lives into perspective. Also I haven't talked about the costs to the economy of the Dance phase of the Suppression strategy, once heavy social distancing measures subside. That's because, if done well, countries can "dance" with only a small subset of measures that don't cost much: testing, contact tracing, quarantines, isolation, hygiene education, and travel bans. Note finally that a suppression strategy would cost all of society but would benefit older people more, as they are the ones most likely to be saved by these measures. As such, they are a transfer of wealth from all of society towards our seniors, who in the US tend to vote Republican.

Some societies are adopting a "survival of the fittest" approach, exposing their populations to the virus and letting the weak die. But it looks like that approach might weaken these societies more, making them, in turn, not be the fittest they could be in the face of this epidemic.

All these numbers, with the surprising conclusion that a Suppression strategy would likely be less costly than a Mitigation strategy. But these numbers obscure a larger truth:

We don't live to make money. We make money to live.

And the best way to illustrate that is through war.

This is War

President Trump put it very clearly on March 18th: This is war.

He compared the sacrifices we will need to make to those of World War II. This is exactly how we should be looking at the problem.

Imagine we had foreign agents. They have infiltrated the US. They are invisible. They are spreading across the country: slowly, silently. And then, they strike: rapidly, randomly. People start falling left and right. Over a matter of days, the death toll of 9/11 is passed, and then dwarfed. At some point, it becomes clear that the death toll will be worse than Iraq. Worse than Vietnam. Worse than World War II. Worse than all of America's wars combined.

If this was happening, the US would stop everything it's doing and single-mindedly focus all of its attention and money to beat this enemy.

That's why the US has the mightiest military in the world. That's why it spent $2.4 trillion on the wars against Iraq and Afghanistan. That's why, during World War II, two-thirds of the American economy had been integrated into the war effort: to beat the enemies that threaten America.

This is what should be happening now. The fact that our enemies are invisible viruses and not invisible agents doesn't change much. If anything, it only makes it easier, because we're smarter than them and we can beat them.

But only one entity can declare war and harness the resources we would need: the federal government.

Survival of the Fittest

China had a centralized response to the coronavirus. South Korea had a centralized response. Taiwan. Italy. Spain. France. UK. Poland. India. All centralized responses. Meanwhile, so far in the US, we have let states take the lead.

There are many situations where that approach is reasonable. But waging war against an exponentially growing threat that all countries face at the same time is not one of those situations.

We have a $2 trillion package to fight the coronavirus. It's a war-like budget, but without war-like measures. The government has invoked the Defense Production Act, for example, but hasn't actually used it yet. As a result, states and companies are struggling to face the challenge, but in some places, they're drowning.
Trade War over Supplies
One of the best examples is the purchase of personal protective equipment (PPE), such as masks, goggles, gowns or gloves.

Traditional medical distributors such as Cardinal Health or McKesson are doing what they can to get PPEs from the manufacturing center of the world, China. Except that China has been closed for business for nearly a month. Just as the supply plummeted, demand exploded around the world, with orders of magnitude more requests from all countries in the world for more of everything. Even if China wanted, it couldn't supply everything. That's assuming that China wants to. In the middle of a trade war with the US, and with a grey market that is much more profitable than the official one, the traditional channels don't work. Suppliers are selling to the highest bidder.

When there's will, we can overcome these challenges, such as the recent airlifting of medical supplies spearheaded by the White House. But this is piecemeal right now, not a systematic approach.
Homegrown Mess for Protective Equipment
The country is mobilized. Everybody wants to help, from tech to education. In healthcare, hundreds of initiatives have sprung up to produce the PPEs our healthcare workers need. Manufacturing plants across the country are trying to change their production towards masks, face screens or any other PPE. But they don't have the money, designs or logistics to start, and they don't know where to sell. Dozens of organizations have sprung up to help, such as the PPE Coalition. But we need one master effort to immediately coordinate all manufacturers, financiers, designers, lawyers, logistics experts, and customers in one place.

If we had months, the private sector could figure it out. But we have days. When you need speed, you need a single actor coordinating everything, and the obvious one is the federal government.

But the response so far has been for states to figure it out by themselves. The federal government has told state governors to find ventilators by themselves. That is tragic.
Fratricide for Ventilators
First, states are not experts on this. They don't have their own CDCs. They don't deal with ventilator markets. They don't know where the supply is. Every day counts, but instead of mandating what needs to happen, thousands of state employees are trying to become overnight experts in ventilator and PPE procurement.

But even if they were experts, they couldn't do it. Because now every state is fighting for itself. Every state needs ventilators, either because they need them today, or because they will need them tomorrow. This is a matter of life and death, so they're bidding against each other. Ventilator and PPE providers are looking at this and selling to the highest bidder. Survival of the fittest.

A coordinated federal response would eliminate all these problems: it would harness the experience of the best experts, it would determine the prices and quantities to be manufactured, and it would distribute assets based on needs, not on whoever is fast and rich enough to buy them first.
Unaffordable Testing Kits
Arguably, the single most important measure against the coronavirus is to test as many people as possible to identify all the infected, isolate them, trace their contacts, and quarantine them. This is the bread and butter of how all East Asia countries have controlled the virus. It's how we'll know how when, in a Suppression strategy, it's time to switch from the Hammer (total lockdown) to the Dance (relaxed social distancing measures).

But in the US, not only do we have a very hard time testing. It's unaffordable. If testing for the virus was as simple as getting a test covered by your insurance, that would be easy. But that's not how it works.

People who are symptomatic and seek care may be billed for a visit with a doctor, an influenza test, a chest x-ray, and bacterial, viral, or blood culture tests. These costs can add up very quickly, particularly for people with no insurance or who have high-deductible health plans. - Castlight Report

With all these, a simple coronavirus test can end up costing people over $4,000. That does not include the treatment. There is no way you can test everybody with that price tag.
Contact Tracing and Quarantine Enforcement
China had 1,800 teams of five people each figuring out every single person that a coronavirus patient might have infected while out and about. These techniques were extremely advanced, looking at mobile phone location or credit card data, cross-referencing with mass transport tickets, and using other tools to identify every single potential contagion.

Meanwhile, in the US, we're leaving all of that to the states.

Quarantine enforcement is equally technologically-advanced and time-consuming. Some countries use apps, while others track the movement of your phone to know if you're still at home and call you if they suspect you left your phone home.

None of this exists in the US. As we know, the NSA already has a lot of this data. The government is already using it, they're just not using it for this yet, and 50 states can't be expected to all figure it out on their own.

The government doesn't need to do all of this, but it needs to coordinate it. We will go much faster if we develop a single app for all states and we tell everybody to use that same app. We will also need software for contact tracing workers to do their job. States can employ these workers, but with the time we have available, the fastest way to get this done is through a the federal government, even if it's through a public-private partnership between with tech companies.

All of that can be done while maintaining privacy, like in Singapore. And if people don't want to use the app, they can opt out like in Poland and just expect random visits from state enforcement workers.

The Weakest Link

All of this puts US states in a very tough situation. The richest ones might be able to organize all of this and develop the technology required. But many will not. These states will suffer outbreaks they can't see or control. That will create difficult dynamics between them.

Imagine Alaska applies a costly Hammer and locks down the state for weeks. It manages to control the epidemic, and sets up great testing and contact tracing processes. Meanwhile, maybe Texas doesn't want to do the same, and there's an uncontrolled epidemic.

What will Alaska do? Will it let Texans come, at risk of seeding new outbreaks? No, it will want to ban them from traveling to Alaska. Clever Texans will just travel to another state and go from there to Alaska. So Alaska will be forced to seal its borders. And every state that takes the coronavirus seriously will have to seal its borders too. This is already happening.

If you think that's impossible, legal experts disagree: states can close their borders to other states.

When the federal government treats every state like an independent country, the states require the same tools as those of independent countries. Even though Spain is part of the European Union, as an independent country, it sealed its borders.

Individual states are only as strong as the weakest link. Either the US mandates measures at the federal level, or states will be forced to behave like countries and eventually seal their borders.

What Should the States and the Federal Government Do?

The takeaway is that both states and the federal government have their own roles to fulfill. So far, states are taking the lead, and many are doing what's needed. But some haven't. And even the best ones still need coordination in some areas.

Based on all of this, here are some key measures the federal government should contemplate:

Healthcare Supplies: Centralize the purchase of critical supplies (ventilators, PPEs, test kits...) and allocate them to states, allowing them to distribute within the state. Provide supplier guarantees so that they don't underproduce in fear of ending up with too much unsold inventory.

Homegrown Production: Support the homegrown production of critical supplies, including financing and supplier guarantees. Determine a clearinghouse so that supply, demand, and philanthropic help know where to meet. Either build one through a public-private partnership, or anoint one of the existing platforms to speed up market making (eg, Google for ventilators, PPE Coalition for PPEs).

Centralize Contact Tracing: Build with a public/private partnership the technology needed to trace contacts easily. Create a law that requires companies to hand over the data needed to make it work and allows its use by federal and state employees. Provides the tools for states to actually carry out the contact tracing. Create the tools in a way that privacy is optimized, and add an automatic expiration date to the law.

Either mandate country-wide social distancing measures, or provide very specific guidelines for states and clarify their ability to seal borders with each other. The application of social distancing measures should adapt to the reality on the ground: What works in infected cities with lots of work-from-home ability might not fit rural areas with low density, no coronavirus cases, and predominant farming activity. If a federal mandate is unworkable, use access to other resources and funding for compliance.

Speed up decision-making or get out of the way when states need agility. For example, testing kits could arguably be better off without the heavy oversight of the FDA, given all the international best practices and the speed of local laboratories. Use the FDA recommendations as guidance and best practices, rather than as a gate.

Lead an initiative to guarantee free coronavirus testing to citizens, all costs included.

Actively update travel bans: Right now, they are mostly from China, Iran and Europe, but that doesn't reflect the reality on the ground anymore. There are as of today 23 countries outside of these places with more than 1,000 cases, and many more quickly growing.

Support states with advice and money to educate the population on the importance and best practices of social distancing and hygiene.

The United States is the strongest country in the world. It has the most vibrant economy, the mightiest military. It has inspired democracies through history, and shines the values of freedom around the world.

All of this originated two and a half centuries ago, when a group of ragtag colonies, subservient to a remote king, decided to band together to overturn a tyranny.

That triumph emerged from the union of the original thirteen states. Independent, they couldn't beat the mighty United Kingdom. Together, they did.

This is why the US is called the United States. It was the union that brought the force. It's why the seal of the United States of America declares: E Pluribus Unum.

We are facing the biggest battle of our generation, and it all comes down to today. We have two options on our hands: Either we unite as a country, or we will crumble as individual states.

The margin of error is so small. A few days off, and thousands more die. Our healthcare workers are already dying on the lines. They're willing to give their lives for all of us. Because that's what living is about. We, too, need to fight for every life of our compatriots. Because we know, when we add up these lives, this will make the difference between winning and losing. Between living, or letting our loved ones die.

I want to be on the winning team. Do you?

If you believe this article, or any other similar article, can help your lawmakers make the right decisions, please share it. Millions have done it with the previous articles, and they might have saved countless lives. If you want to receive the next articles, If you agree with this approach, consider signing the German translation This has been a massive team effort with the help of dozens of people who have provided research, sources, arguments, feedback on wording, challenged my arguments and assumptions, and disagreed with me. Special thanks to Carl Juneau, John Hsu, Genevieve Gee, Matt Bell, Elena Baillie, Xianhang Zhang, Jorge Peñalva, Pierre Djian, Mike Kidd, Yasemin Denari, Eric Ries, Castlight, Berin Szoka, Andy Skrzypacz, Shishir Mehrotra, Dan Hess, Mudit Garg, David Walker, Max Henderson, Jonathan Kreiss-Tomkins, Misha David Chellam, Michael Ovadia, Peter Schwartz, Mick Costigan, Alex Whitehead, Mike LeVasseur, and many more. This would have been impossible without all of you. Portuguese translation (outside of Medium) White House petition. sign up here.

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What the US Federal Government and the States Should Do to Fight the Coronavirus My two previous articles, Summary: It makes political and economic sense for the US to suppress the coronavirus. For that, states and the federal government each have their own roles that they need to adjust.

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Covid Projections

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And here are the 14 day projections for active cases (PROJECTIONS, not PREDICTIONS). Simply based on simple extrapolation of maximum of 2-day, 3-day and 7-day growth rate. 

Confirms that apart from Kerala and Karnataka, Telangana and Tamil Nadu have started flattening

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And here are the 14 day projections for active cases (PROJECTIONS, not PREDICTIONS). Simply based on simple extrapolation of maximum of 2-day, 3-day and 7-day growth rate. 

Confirms that apart from Kerala and Karnataka, Telangana and Tamil Nadu have started flattening https://t.co/GN3AfDtont

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Don’t miss what’s happening

People on Twitter are the first to know.

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And here are the 14 day projections for active cases (PROJECTIONS, not PREDICTIONS). Simply based on simple extrapolation of maximum of 2-day, 3-day and 7-day growth rate.

Confirms that apart from Kerala and Karnataka, Telangana and Tamil Nadu have started flattening pic.twitter.com/GN3AfDtont
— Karthik S (@karthiks) April 12, 2020

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And here are the 14 day projections for active cases (PROJECTIONS, not PREDICTIONS). Simply based on simple extrapolation of maximum of 2-day, 3-day and 7-day growth rate. 

Confirms that apart from Kerala and Karnataka, Telangana and Tamil Nadu have started flattening https://t.co/GN3AfDtont

# data[].attributes.attachment_link.metadata.attachment_props.original_text
And here are the 14 day projections for active cases (PROJECTIONS, not PREDICTIONS). Simply based on simple extrapolation of maximum of 2-day, 3-day and 7-day growth rate. 

Confirms that apart from Kerala and Karnataka, Telangana and Tamil Nadu have started flattening https://t.co/GN3AfDtont

# data[].attributes.attachment_link.metadata.attachment_props.text
And here are the 14 day projections for active cases (PROJECTIONS, not PREDICTIONS). Simply based on simple extrapolation of maximum of 2-day, 3-day and 7-day growth rate. 

Confirms that apart from Kerala and Karnataka, Telangana and Tamil Nadu have started flattening

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If you follow me on Twitter, you'll know I'm constantly going on about how the number of COVID-19 cases is not a very useful indicator of anything - unless you also know something about how tests are being conducted.

If you're a regular reader of FiveThirtyEight, you're probably used to looking at data in sports - where basically everything that happens on a basketball court or a baseball diamond is recorded - or in electoral politics, when polls ( in theory, anyway) survey a random sample of the population. COVID-19 statistics, especially the number of reported cases, are not at all like that. The data, at best, is highly incomplete, and often the tip of the iceberg for much larger problems. And data on tests and the number of reported cases is highly nonrandom. In many parts of the world today, health authorities are still trying to triage the situation with a limited number of tests available. Their goal in testing is often to allocate scarce medical care to the patients who most need it - rather than to create a comprehensive dataset for epidemiologists and statisticians to study.

But if you're not accounting for testing patterns, it can throw your conclusions entirely out of whack. You don't just run the risk of being a little bit wrong: Your analysis could be off by an order of magnitude. Or even worse, you might be led in the opposite direction of what is actually happening. A country where the case count is increasing because it's doing more testing, for instance, might actually be getting its epidemic under control. Alternatively, in a country where the reported number of new cases is declining, the situation could actually be getting worse, either because its system is too overwhelmed to do adequate testing or because it's ramping down on testing for PR reasons.

Failure to account for testing strategies can also render comparisons between states and countries meaningless. According to two recent epidemiological studies, which tried to infer the true number of infected people from the reported number of deaths, there is roughly a 20-fold difference in case detection rates between the countries that are doing the best job of it, such as Norway and the worst job, such as the United Kingdom. (The United States is probably somewhere in the middle of the pack by this standard.) That means, for example, that in one country that reports 1,000 COVID-19 cases, there could actually be 5,000 infected people, and in another country that reports 1,000 cases, there might be 100,000!

There is also a lot of uncertainty about the true numbers of infections within a given country. According to an expert survey published by FiveThirtyEight, the number of detected cases in the United States could underestimate the true number of infected people by anywhere from a multiple of two times to 100 times. The same holds in other countries. A recent paper published by Imperial College London estimated that the true number of people who had been infected with the coronavirus in the U.K. as of March 30 was somewhere between 800,000 and 3.7 million - as compared to a reported case count through that date of just 22,141.

So in this article, I'm going to work through four examples of how various testing strategies can skew case counts, in the hopes of giving you a more hands-on sense for how the mechanics behind the numbers work. These scenarios are definitely not meant as predictions of what will happen in any given country, state or region. They work with hypothetical data, because we don't know all the parameters we'd need to properly estimate a model anyway. The goal is just to illustrate, given relatively simple assumptions, how reported case counts for a disease can differ from the actual number of infections.

At the same time, the parameters in each scenario reflect what I hope are semi-realistic assumptions that at least loosely approximate the coronavirus situation in different groups of countries. Some countries have relatively robust testing. Some started out with strong testing but then stalled out. Some were way behind on testing but soon caught up. Each of these can have different effects on the pattern of reported cases.

You can even download an Excel spreadsheet and input your own assumptions - though I'm going to wait until the end of the story to give you the link, in the hopes that you'll continue reading about how this all works before trying to brew up your own scenario.

The not-so-simple math behind coronavirus testing

The core purpose of this exercise is to help you think through how many people might test positive for a disease based on how many people are actually infected with it, given various assumptions about testing. That does require us to make some simple assumptions about the underlying number of infected people in the population. So the scenarios are partly based on what should be a fairly simple, standard epidemiological model.

The most important number in any epidemiological model is R, or the reproduction ratio, which is how many people that a person in one generation passes the disease along to in the next generation. For example, if a disease has an R of 3, that means each infected person transmits it to three more people. So one initial case becomes three newly infected people in the next generation, which becomes nine people, which becomes 27 people, which becomes 81 people, and so forth - the very nature of exponential growth is that it gets out of hand quickly!

Assumptions about the R of COVID-19 vary, and to some extent that's inevitable given that there isn't necessarily one intrinsic number for how the disease spreads from one infected person to the next. In fact, epidemiologists make a distinction between R 0 (pronounced R-zero or R-naught), which is called the basic reproduction ratio, or how fast the disease spreads in the absence of any interventions or any immunity whatsoever, and the effective reproduction ratio, called R-effective or simply R. R-effective is likely to be much higher on a cruise ship or in a college dormitory than in the middle of a remote town in Alaska where people rarely encounter one another, for example. Moreover, interventions such as social distancing are being undertaken to bring down R, although actions can vary from location to location. The goal, though, is to get R below 1, which means that a disease begins to die out in a population. (It will die out gradually if R is close to 1 and quickly if it's close to zero, say, 0.2.) Finally, if a disease has spread very widely throughout the population, R may eventually fall because of herd immunity. In other words, enough people are immune to a disease because they've already had it, it will not continue to spread as fast.

So in these scenarios, I assume that R goes through three different stages that reflect various efforts at containment:

First, there's an uncontrolled stage where the disease is spreading unchecked throughout the population. I assume this stage has an R of 2.6. The WHO initially estimated R to be between 2.0 and 2.5, but other researchers such as those from Imperial College London have since revised their numbers upward to around 3.0; thus, 2.6 reflects something of a middle ground.

Next, there's an intermediate stage where some measures are being undertaken - businesses are having their employees work from home, large events are cancelled, and people are avoiding some unnecessary contacts and generally being more careful. But, there are no lockdown or quarantine measures in place. I assume that R falls to 1.4 during this stage.

Finally, there's a lockdown stage where R falls to 0.7 - or below zero, meaning that the disease begins to die out.

There's a lot of disagreement about these values - both how fast COVID-19 was spreading initially and how effective various interventions have been at lowering R. So you are welcome to download the spreadsheet at the end of this article and tweak those assumptions. (Note that the scenarios also account for R gradually reducing over time because of herd immunity, so the actual values of R in the scenarios may be slightly lower than the ones stated above.)

Next: How long does a generation last? By a generation, I don't mean the Baby Boomers or something like that - I mean one round of infections. The number that determines the length of a generation is the serial interval, which is how long it takes, on average, for a person to transmit the disease to the people he infects. For COVID-19, estimates of the serial interval hover between four to five days. So I assume that a generation lasts five days in the scenarios.

I also assume that the disease has varying levels of severity, and that this affects whether people are tested. In particular, I assume that:

10 percent of cases are severe.

60 percent of cases are mild.

And 30 percent of cases are asymptomatic.

Again, this seems to match the consensus of the medical literature on COVID-19 ... but there is a lot of disagreement about these parameters - and especially on the number of asymptomatic cases. So I'd welcome you to input different values and see how they affect the results.

However, in considering who gets tested, we also need to think about people who have symptoms similar to those of COVID-19 but who don't actually have the coronavirus. I haven't seen much research on this question, but thermometer data seems to find that around 3 percent of the U.S. population typically feels sick at this point in the year. So the scenarios assume that at any given time, 0.1 percent of the population has symptoms that resemble severe COVID-19 symptoms for reasons other than coronavirus (say, a bad flu or bronchitis or pneumonia), and that 2.5 percent have symptoms that resemble mild COVID-19 symptoms for other reasons than coronavirus (say, a mild flu or a bad cold). Furthermore, I assume that all people with severe symptoms seek testing (that is, they would get tested if they could), that half of people with mild symptoms do and that 2 percent of asymptomatic people do. All of these assumptions can also be changed in the spreadsheet.

But wait, there's more! I don't really consider the scenarios a "model" in the way FiveThirtyEight usually uses that term because we're not trying to predict anything, we're just trying to show how different testing strategies can impact the number of reported cases. But, as in the case of real coronavirus models, there are an awful lot of messy, real-world problems we need to consider, too.

One of them is that there's a long lag between when someone is infected, when they develop symptoms, when they get tested and when those test results are reported. In Wuhan, China, the lag between the development of symptoms and test results being reported was around 10 to 12 days. And considering it usually takes at least a few days for symptoms to develop, the lag between infection and a case showing up in the test statistics is going to be longer still. In these scenarios, I therefore assume that there's a delay of 15 days (or three generations) between infection and the test results showing up in the data - though if anything I suspect this is too generous, given the huge testing bottlenecks in places such as California.

Another real-world problem is that the tests aren't perfect. In fact, according to reporting by The Wall Street Journal on Thursday, around 30 percent of people who actually have COVID-19 test negative for it - which is what we'd call a false negative. Other estimates of false negatives aren't quite so high, so I assume a 20 percent false negative rate in the scenarios.

Then, of course, there's also the question of false positives, i.e., when a test reports that someone has COVID-19 but they actually don't. This number is harder to pin down, but we can infer that tests rarely produce false positives. Why? In Iceland, where large numbers of asymptomatic people are being tested, the overall rate of positive tests among this group is slightly under 1 percent. Given that includes people who probably do have the coronavirus (since asymptomatic cases are fairly common), we can assume the rate of false positives is even lower - for the purpose of the scenarios, we'll guess that it's 0.2 percent.

However, there's a bit of a mathematical twist in calculating false positives. Even if false positives are rare, false positives may swamp true positives if the underlying incidence of a disease is low. Say, for instance, that in the early stages of an outbreak in a town of 100,000 people, 100 people or 0.1 percent of the population actually has the disease. If everyone gets tested, then there will be roughly 200 false positives (0.2 percent of the population) - larger than the number of people who are actually sick! This is why some of the discourse around false positive tests is confusing. It can both be true that the rate of false positives is fairly low and that a high share of positive tests are false. For better or worse, this becomes less of an issue as new infections multiply; there are lots of real positives, so they no longer drown out the false positives.

Finally, there are a further set of assumptions we have to make about how many tests are conducted and who gets tested. But those vary from scenario to scenario. So let's work through the scenarios now:

Scenario 1: Robust growth in testing

To emphasize that these are hypothetical scenarios and to get you in an appropriately abstract mindset, I'm going to ask you to imagine that these scenarios occur in a country called Covidia, which has 10 million people and where the first infected person entered the country on Jan. 1 (although his case wasn't detected until later).

In this first scenario, Covidia - like most real-world countries - is a little slow to undertake social distancing measures. They take some intermediate steps on March 1, by which time 183,000 people there have already been infected, though far fewer positive tests (just 439!) have been reported. On March 16, with the number of cases still rapidly increasing, Covidia implements a full stay-at-home order (what I'm informally calling a "lockdown"), which reduces R to less than one.

In better news, the testing situation is comparatively good in this version of Covidia. In this scenario, I assume that Covidia starts out with the capacity to do 1,000 tests per generation, and beginning in early February, it improves testing volume by 50 percent per generation until all testing demand is satisfied. I further assume that Covidia rations 75 percent of tests, meaning that tests go to people with severe symptoms before people with mild symptoms, and to people with mild symptoms before people with no symptoms. The remaining 25 percent of tests are available on an on-demand basis.

So, what does this look like? Here is how the actual number of infections compares to the number of reported cases in Covidia, first in table form...

...and then in chart form:

There are quite a few things to look at here. The most obvious and probably the most important one is simply that a 15-day delay between when someone gets infected and when their case shows up in the data as a positive test makes a huge difference. Even if everything else was going perfectly - 100 percent of the population was being tested and the tests are 100 percent accurate - with an R of 2.6, a 15-day delay would result in there being about 18 times more newly infected people in the population than the number of newly reported positive tests at any given time.

The delay matters less as R declines because if the disease isn't growing as fast, there aren't as many new people who get infected in the 15-day period between infection and test results. But it still means we're always looking two weeks into the past whenever "new" data is reported. And remember, social distancing measures that are effective in flattening the curve may take two or three weeks to show up in the data. This is especially so when the demand for testing is near its peak and there are likely to be longer lags in processing test results.

Next, even with relatively good testing, you're still likely to miss many cases. By the end of the scenario on June 29, 1.2 million people have been infected at some point in Covidia, but there are only 186,000 detected cases, for a detection rate of about 16 percent (and some of those are false positives so the actual situation is a bit worse than that). What accounts for the missing cases?

First, we assume that many people with mild symptoms or no symptoms do not want to get tested (and nobody forces them to get tested) so they get infected at some point without ever realizing it.

Next, the 20 percent false negative rate means that some cases are missed.

Finally, even where testing ramps up quickly, it may not ramp up quite as fast as the disease itself. The actual peak in new infections in this scenario comes on March 16 - and at that point, testing is not fully scaled up and a lot of people who would like a test still cannot get one.

There's also a third issue: If testing is increasing, the rate of growth of a disease can be overestimated. Alternatively, if testing is stagnant or decreasing, the rate of growth can be underestimated. Note that in Scenario 1, the R you'd infer from the number of reported cases peaks at 3.5, when the actual R based on infections was not quite as high (2.6 before Covidia began implementing social distancing measures).

In other words, the rapid rates of growth in new cases you can see in a country (say, Germany) when it first gets serious about testing are both a function of the number of tests increasing and the number of infections increasing - and it's hard to tell what's what. You can also have problems if there's a sudden, one-off increase in tests, as we'll see in the next scenario.

A final issue - I'm not going to boldface it because it's less important than the others - is that in the late stages of the scenario when there is little disease transmission following a prolonged lockdown, many of the newly detected "cases" are false positives. As I mentioned, false positives can be an issue to contend with when the overall incidence of disease in a population is low. They are not the greatest concern in the U.S. or Europe right now, when we're still in the peak of the pandemic.

Scenario 2: Sudden, one-time increase in testing

What would a more rapid increase in testing look like? In Scenario 2, I'm leaving all the settings from Scenario 1 unchanged - except for the number of tests. In this new scenario, I assume that Covidia starts out with the capacity to conduct only 100 tests per generation, but then goes on a crash program in February and rapidly increases that number at a rate of 200 percent per generation until it maxes out at 100,000 tests about a month later. This is similar to the situation in the United States, where testing started out slow, improved rapidly and has now stalled out again.

In this scenario, the distortions between the number of infections and the number of people who test positive are more profound. Even though the actual R is "only" 2.6 in the early stages - still a very scary, high number by the way - it will briefly appear to be as high as 7.8 if you're looking at the number of newly detected cases because test capacity is scaling up so rapidly.

And on a graph, the slope will look extremely steep for a few weeks. You might be tempted to look at a graph like this and say that Covidia is on a much worse trajectory than other countries:

But that isn't getting the story right. What really happened was: Covidia was way behind on testing and it's playing catch-up, which means that the number of reported cases will increase at very fast rates until it does catch up. But the actual number of infections at any given time is the same as in Scenario 1. That doesn't mean the news in Scenario 2 is good, exactly. It means Covidia had a very big COVID-19 problem all along that wasn't being detected until very recently, but it is now finally starting to get its arms around it.

Next, let's look at the opposite case: Where testing starts out reasonably strong, but doesn't scale up very much.

Scenario 3: High test floor, low test ceiling

In this scenario, I assume that Covidia starts out with up to 10,000 tests available per generation. However, it scales up tests very slowly (by just 3 percent per generation) before eventually capping out at 20,000 tests per generation. Furthermore, 100 percent of tests are reserved for symptomatic individuals and there are no on-demand tests available. This situation is broadly analogous to some European countries with centralized, socialized health care systems. For instance, the U.K. has tested only about 160,000 people total as of Apr. 2, or an average of only about 7,000 tests per day since March 19.

In this case, the number of cases is substantially underestimated because there aren't enough tests at the peak of the epidemic. Only about 5 percent of infections are eventually detected.

But not only is the number of cases underestimated - the rate of increase will also be underestimated. For instance, in this scenario, R appears to peak in the low-to-mid 2's when it's actually 2.6. This is because the rate of new cases is increasing faster than the country's ability to detect them, even if the country rations as many of the tests as it can so it can test the sickest individuals, as we assume that it does. During the peak of the epidemic in Scenario 3, as many as 58 percent of newly reported tests will produce positive results, which resembles the extremely high rate of reported positives for periods of time in places such as Lombardy, Italy.

So while the slope of reported new cases in Scenario 3 might look more gentle than in Scenario 1 or Scenario 2...

...the country's situation is actually just as bad. And in some respects it might be worse. Having conducted so few tests, Covidia will miss some extremely ill people in Scenario 3 and they may die as a result of not being able to get medical care soon enough.

That's not the worst-case scenario, though. Imagine if a country, recognizing that the media tends to fixate on case counts, decides that it can make things look superficially better by decreasing the number of tests that it does.

Scenario 4: A testing decrease

Let's say that, as in Scenario 3, Covidia starts out with the capacity to conduct 10,000 tests per generation. However, as the case count begins to accelerate, the government panics that the outbreak will make it look bad, so it subtly starts scaling down testing capacity by 20 percent per generation in early March. Meanwhile, being in denial about the scale of the problem, it doesn't implement a full lockdown until April 10, or more than three weeks later than under the other scenarios.

I should note that this is more of a "thought experiment" than the other three scenarios. Countries from China to Russia to Iran have been accused of publishing unreliable official statistics - but I don't know whether any countries are deliberately limiting testing to keep case counts down.

Nonetheless, a situation like this obviously turns out quite badly. Almost 30 percent of the country eventually gets infected:

Would the country really wait so long to implement a lockdown? Well, if it wasn't doing enough testing, it might. Because Covidia is reducing the number of tests in this scenario, the number of reported new cases will appear to peak on March 16, even though the actual peak of new infections won't come until April 5. It will appear that the partial measures it undertook worked, when really they weren't working well enough:

In an instance like this, having information on the number of tests would be quite useful, as a high rate of positive tests could be a sign that you're only seeing the tip of the iceberg. During the peak of the outbreak in April, as many as 64 percent of tests would return positive results in Scenario 4, the number would be as high as 80 percent if not for false negatives.

I already gave away the conclusion at the top of the story, so I'm just going to repeat it once more, hoping that this article has helped to convince you of it: The number of reported COVID-19 cases is not a very useful indicator of anything unless you also know something about how tests are being conducted.

In fact, in some cases, places with lower nominal case counts may actually be worse off. In general, a high number of tests is associated with a more robust medical infrastructure and a more adept government response to the coronavirus. The countries that are doing a lot of testing also tend to have low fatality rates - not just low case fatality rates (how many people die as a fraction of known cases) but also lower rates of death as a share of the overall population. Germany, for example, which is conducting about 50,000 tests per day - seven times more than the U.K. - has more than twice as many reported cases as the U.K., but they've also had only about one-third as many deaths.

Put another way: Doing more tests is good, and likely leads to better long-run outcomes, even if it also results in higher case counts that people will freak out about in the short run. I don't usually like to be so didactic, but I hope you'll be a more educated consumer of COVID-19 data instead of just looking at case counts ticking upward on cable news screens without context. That context includes not only reporting about the amount of testing, but also indications such as hospital strain, which are more robust since they aren't subject to as many vagaries about how tests are conducted. Even if you're not from New York, Gov. Andrew Cuomo's daily briefings are worth watching because they do the best job I've seen of providing this context.

And if you do want to play with your own scenarios to see how all of this works... here's the link to that Excel sheet. Have fun, but keep in mind that even though there are a lot of parameters you can tweak, the scenarios are still a fairly crude simplification of the complex situation on the ground in any given state or country.

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Coronavirus Case Counts Are Meaningless*

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If you follow me on Twitter, you'll know I'm constantly going on about how the number of COVID-19 cases is not a very useful indicator of anything - unless you also know something about how tests are being conducted.

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Humankind is now facing a global crisis. Perhaps the biggest crisis of our generation. The decisions people and governments take in the next few weeks will probably shape the world for years to come. They will shape not just our healthcare systems but also our economy, politics and culture. We must act quickly and decisively. We should also take into account the long-term consequences of our actions. When choosing between alternatives, we should ask ourselves not only how to overcome the immediate threat, but also what kind of world we will inhabit once the storm passes. Yes, the storm will pass, humankind will survive, most of us will still be alive - but we will inhabit a different world.

Many short-term emergency measures will become a fixture of life. That is the nature of emergencies. They fast-forward historical processes. Decisions that in normal times could take years of deliberation are passed in a matter of hours. Immature and even dangerous technologies are pressed into service, because the risks of doing nothing are bigger. Entire countries serve as guinea-pigs in large-scale social experiments. What happens when everybody works from home and communicates only at a distance? What happens when entire schools and universities go online? In normal times, governments, businesses and educational boards would never agree to conduct such experiments. But these aren't normal times.

In this time of crisis, we face two particularly important choices. The first is between totalitarian surveillance and citizen empowerment. The second is between nationalist isolation and global solidarity.

Under-the-skin surveillance

In order to stop the epidemic, entire populations need to comply with certain guidelines. There are two main ways of achieving this. One method is for the government to monitor people, and punish those who break the rules. Today, for the first time in human history, technology makes it possible to monitor everyone all the time. Fifty years ago, the KGB couldn't follow 240m Soviet citizens 24 hours a day, nor could the KGB hope to effectively process all the information gathered. The KGB relied on human agents and analysts, and it just couldn't place a human agent to follow every citizen. But now governments can rely on ubiquitous sensors and powerful algorithms instead of flesh-and-blood spooks.

In their battle against the coronavirus epidemic several governments have already deployed the new surveillance tools. The most notable case is China. By closely monitoring people's smartphones, making use of hundreds of millions of face-recognising cameras, and obliging people to check and report their body temperature and medical condition, the Chinese authorities can not only quickly identify suspected coronavirus carriers, but also track their movements and identify anyone they came into contact with. A range of mobile apps warn citizens about their proximity to infected patients.

This kind of technology is not limited to east Asia. Prime Minister Benjamin Netanyahu of Israel recently authorised the Israel Security Agency to deploy surveillance technology normally reserved for battling terrorists to track coronavirus patients. When the relevant parliamentary subcommittee refused to authorise the measure, Netanyahu rammed it through with an "emergency decree".

You might argue that there is nothing new about all this. In recent years both governments and corporations have been using ever more sophisticated technologies to track, monitor and manipulate people. Yet if we are not careful, the epidemic might nevertheless mark an important watershed in the history of surveillance. Not only because it might normalise the deployment of mass surveillance tools in countries that have so far rejected them, but even more so because it signifies a dramatic transition from "over the skin" to "under the skin" surveillance.

Hitherto, when your finger touched the screen of your smartphone and clicked on a link, the government wanted to know what exactly your finger was clicking on. But with coronavirus, the focus of interest shifts. Now the government wants to know the temperature of your finger and the blood-pressure under its skin.

The emergency pudding

One of the problems we face in working out where we stand on surveillance is that none of us know exactly how we are being surveilled, and what the coming years might bring. Surveillance technology is developing at breakneck speed, and what seemed science-fiction 10 years ago is today old news. As a thought experiment, consider a hypothetical government that demands that every citizen wears a biometric bracelet that monitors body temperature and heart-rate 24 hours a day. The resulting data is hoarded and analysed by government algorithms. The algorithms will know that you are sick even before you know it, and they will also know where you have been, and who you have met. The chains of infection could be drastically shortened, and even cut altogether. Such a system could arguably stop the epidemic in its tracks within days. Sounds wonderful, right?

The downside is, of course, that this would give legitimacy to a terrifying new surveillance system. If you know, for example, that I clicked on a Fox News link rather than a CNN link, that can teach you something about my political views and perhaps even my personality. But if you can monitor what happens to my body temperature, blood pressure and heart-rate as I watch the video clip, you can learn what makes me laugh, what makes me cry, and what makes me really, really angry.

It is crucial to remember that anger, joy, boredom and love are biological phenomena just like fever and a cough. The same technology that identifies coughs could also identify laughs. If corporations and governments start harvesting our biometric data en masse, they can get to know us far better than we know ourselves, and they can then not just predict our feelings but also manipulate our feelings and sell us anything they want - be it a product or a politician. Biometric monitoring would make Cambridge Analytica's data hacking tactics look like something from the Stone Age. Imagine North Korea in 2030, when every citizen has to wear a biometric bracelet 24 hours a day. If you listen to a speech by the Great Leader and the bracelet picks up the tell-tale signs of anger, you are done for.

You could, of course, make the case for biometric surveillance as a temporary measure taken during a state of emergency. It would go away once the emergency is over. But temporary measures have a nasty habit of outlasting emergencies, especially as there is always a new emergency lurking on the horizon. My home country of Israel, for example, declared a state of emergency during its 1948 War of Independence, which justified a range of temporary measures from press censorship and land confiscation to special regulations for making pudding (I kid you not). The War of Independence has long been won, but Israel never declared the emergency over, and has failed to abolish many of the "temporary" measures of 1948 (the emergency pudding decree was mercifully abolished in 2011).

Even when infections from coronavirus are down to zero, some data-hungry governments could argue they needed to keep the biometric surveillance systems in place because they fear a second wave of coronavirus, or because there is a new Ebola strain evolving in central Africa, or because . . . you get the idea. A big battle has been raging in recent years over our privacy. The coronavirus crisis could be the battle's tipping point. For when people are given a choice between privacy and health, they will usually choose health.

The soap police

Asking people to choose between privacy and health is, in fact, the very root of the problem. Because this is a false choice. We can and should enjoy both privacy and health. We can choose to protect our health and stop the coronavirus epidemic not by instituting totalitarian surveillance regimes, but rather by empowering citizens. In recent weeks, some of the most successful efforts to contain the coronavirus epidemic were orchestrated by South Korea, Taiwan and Singapore. While these countries have made some use of tracking applications, they have relied far more on extensive testing, on honest reporting, and on the willing co-operation of a well-informed public.

Centralised monitoring and harsh punishments aren't the only way to make people comply with beneficial guidelines. When people are told the scientific facts, and when people trust public authorities to tell them these facts, citizens can do the right thing even without a Big Brother watching over their shoulders. A self-motivated and well-informed population is usually far more powerful and effective than a policed, ignorant population.

Consider, for example, washing your hands with soap. This has been one of the greatest advances ever in human hygiene. This simple action saves millions of lives every year. While we take it for granted, it was only in the 19th century that scientists discovered the importance of washing hands with soap. Previously, even doctors and nurses proceeded from one surgical operation to the next without washing their hands. Today billions of people daily wash their hands, not because they are afraid of the soap police, but rather because they understand the facts. I wash my hands with soap because I have heard of viruses and bacteria, I understand that these tiny organisms cause diseases, and I know that soap can remove them.

But to achieve such a level of compliance and co-operation, you need trust. People need to trust science, to trust public authorities, and to trust the media. Over the past few years, irresponsible politicians have deliberately undermined trust in science, in public authorities and in the media. Now these same irresponsible politicians might be tempted to take the high road to authoritarianism, arguing that you just cannot trust the public to do the right thing.

Normally, trust that has been eroded for years cannot be rebuilt overnight. But these are not normal times. In a moment of crisis, minds too can change quickly. You can have bitter arguments with your siblings for years, but when some emergency occurs, you suddenly discover a hidden reservoir of trust and amity, and you rush to help one another. Instead of building a surveillance regime, it is not too late to rebuild people's trust in science, in public authorities and in the media. We should definitely make use of new technologies too, but these technologies should empower citizens. I am all in favour of monitoring my body temperature and blood pressure, but that data should not be used to create an all-powerful government. Rather, that data should enable me to make more informed personal choices, and also to hold government accountable for its decisions.

If I could track my own medical condition 24 hours a day, I would learn not only whether I have become a health hazard to other people, but also which habits contribute to my health. And if I could access and analyse reliable statistics on the spread of coronavirus, I would be able to judge whether the government is telling me the truth and whether it is adopting the right policies to combat the epidemic. Whenever people talk about surveillance, remember that the same surveillance technology can usually be used not only by governments to monitor individuals - but also by individuals to monitor governments.

The coronavirus epidemic is thus a major test of citizenship. In the days ahead, each one of us should choose to trust scientific data and healthcare experts over unfounded conspiracy theories and self-serving politicians. If we fail to make the right choice, we might find ourselves signing away our most precious freedoms, thinking that this is the only way to safeguard our health.

We need a global plan

The second important choice we confront is between nationalist isolation and global solidarity. Both the epidemic itself and the resulting economic crisis are global problems. They can be solved effectively only by global co-operation.

First and foremost, in order to defeat the virus we need to share information globally. That's the big advantage of humans over viruses. A coronavirus in China and a coronavirus in the US cannot swap tips about how to infect humans. But China can teach the US many valuable lessons about coronavirus and how to deal with it. What an Italian doctor discovers in Milan in the early morning might well save lives in Tehran by evening. When the UK government hesitates between several policies, it can get advice from the Koreans who have already faced a similar dilemma a month ago. But for this to happen, we need a spirit of global co-operation and trust.

In the days ahead, each one of us should choose to trust scientific data and healthcare experts over unfounded conspiracy theories and self-serving politicians

Countries should be willing to share information openly and humbly seek advice, and should be able to trust the data and the insights they receive. We also need a global effort to produce and distribute medical equipment, most notably testing kits and respiratory machines. Instead of every country trying to do it locally and hoarding whatever equipment it can get, a co-ordinated global effort could greatly accelerate production and make sure life-saving equipment is distributed more fairly. Just as countries nationalise key industries during a war, the human war against coronavirus may require us to "humanise" the crucial production lines. A rich country with few coronavirus cases should be willing to send precious equipment to a poorer country with many cases, trusting that if and when it subsequently needs help, other countries will come to its assistance.

We might consider a similar global effort to pool medical personnel. Countries currently less affected could send medical staff to the worst-hit regions of the world, both in order to help them in their hour of need, and in order to gain valuable experience. If later on the focus of the epidemic shifts, help could start flowing in the opposite direction.

Global co-operation is vitally needed on the economic front too. Given the global nature of the economy and of supply chains, if each government does its own thing in complete disregard of the others, the result will be chaos and a deepening crisis. We need a global plan of action, and we need it fast.

Another requirement is reaching a global agreement on travel. Suspending all international travel for months will cause tremendous hardships, and hamper the war against coronavirus. Countries need to co-operate in order to allow at least a trickle of essential travellers to continue crossing borders: scientists, doctors, journalists, politicians, businesspeople. This can be done by reaching a global agreement on the pre-screening of travellers by their home country. If you know that only carefully screened travellers were allowed on a plane, you would be more willing to accept them into your country.

Unfortunately, at present countries hardly do any of these things. A collective paralysis has gripped the international community. There seem to be no adults in the room. One would have expected to see already weeks ago an emergency meeting of global leaders to come up with a common plan of action. The G7 leaders managed to organise a videoconference only this week, and it did not result in any such plan.

In previous global crises - such as the 2008 financial crisis and the 2014 Ebola epidemic - the US assumed the role of global leader. But the current US administration has abdicated the job of leader. It has made it very clear that it cares about the greatness of America far more than about the future of humanity.

This administration has abandoned even its closest allies. When it banned all travel from the EU, it didn't bother to give the EU so much as an advance notice - let alone consult with the EU about that drastic measure. It has scandalised Germany by allegedly offering $1bn to a German pharmaceutical company to buy monopoly rights to a new Covid-19 vaccine. Even if the current administration eventually changes tack and comes up with a global plan of action, few would follow a leader who never takes responsibility, who never admits mistakes, and who routinely takes all the credit for himself while leaving all the blame to others.

If the void left by the US isn't filled by other countries, not only will it be much harder to stop the current epidemic, but its legacy will continue to poison international relations for years to come. Yet every crisis is also an opportunity. We must hope that the current epidemic will help humankind realise the acute danger posed by global disunity.

Humanity needs to make a choice. Will we travel down the route of disunity, or will we adopt the path of global solidarity? If we choose disunity, this will not only prolong the crisis, but will probably result in even worse catastrophes in the future. If we choose global solidarity, it will be a victory not only against the coronavirus, but against all future epidemics and crises that might assail humankind in the 21st century.
Yuval Noah Harari is author of 'Sapiens', 'Homo Deus' and '21 Lessons for the 21st Century' Copyright © Yuval Noah Harari 2020 Follow @FTLifeArts on Twitter to find out about our latest stories first. Listen to our culture podcast, Culture Call, where editors Gris and Lilah dig into the trends shaping life in the 2020s, interview the people breaking new ground and bring you behind the scenes of FT Life & Arts journalism. Subscribe on Apple, Spotify, or wherever you listen.
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Yuval Noah Harari: the world after coronavirus | Free to read

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Humankind is now facing a global crisis. Perhaps the biggest crisis of our generation. The decisions people and governments take in the next few weeks will probably shape the world for years to come. They will shape not just our healthcare systems but also our economy, politics and culture.