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The Seattle Flu Study, a multi-institutional influenza study aiming to assess and map the prevalence of symptomatic influenza throughout the Seattle metropolitan area for the purpose of informing public health response, has been active since 2018.

In the context of the COVID-19 pandemic, it has recently diverted most of its resources to addressing questions about COVID-19 through a new partnership with Public Health — Seattle & King County is called the Seattle Coronavirus Assessment Network, or SCAN.

SCAN uses a non-representative online self-selecting study design and private couriers to deliver and return at-home test kits to a limited number of King County residents per day, with over-enrollment of those reporting "COVID-19-like illness" (CLI). The SCAN study is model-based rather than design-based.

Moving forward, SCAN would like to improve its study design in order to capture more precise information about under-represented groups so far, including children, essential workers, non-English speakers, older adults, and those from zip codes with low enrollment.

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Study Objective: Estimate the number of grocery store employees with COVID-19

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Study Objective: Estimate the number of grocery store employees with COVID-19

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These essential workers represent only one population of interest, but this strategy may be applied to other groups of essential workers, for example hospital employees, bus drivers, or agricultural workers.

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Target Population: Grocery store employees in King County

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Target Population: Grocery store employees in King County

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Approach: a stratified, multi-stage cluster design

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Approach: a stratified, multi-stage cluster design

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The primary sampling units are zip codes in King County. These will be selected with probability proportionate to the percent of the population in each zip code who are part of COVID-19 Vulnerable Communities as defined by Communities Count King County. Because this criterion is related to our outcome of interest, we expect it to result in a gain in precision.

A sampling frame enumerating our clusters, grocery stores, within each zip code will have to be drawn up through online research. Stores will be randomly selected from each zip code, and employees randomly selected from each store. This would require the stores to provide a list of employees to sample from, or we could get creative.

SCAN's typical courier data collection and sample processing will then be performed for each consenting participant.

A weighted Horvitz-Thompson estimate of the proportion of grocery store employees with COVID-19 can then be calculated.

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Sample Size Considerations and Limitations

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Sample Size Considerations and Limitations

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COVID-19 infection is a binary outcome and a rare event, with well under 10% of King County's population estimated to be currently infected. According to the literature, if the prevalence is about 1%, an SRS sample size of 1521 is appropriate (Naing et al. 2006).

Current estimates by SCAN place the prevalence somewhere between .05% and .75%, meaning that a larger sample size will be required. The design effect for a study like this one is likely to be higher than one- potentially 2, based on public health studies of more common diseases. This would place our required sample size somewhere higher than 1521*2=3042.

SCAN's resources are currently limited, such that it quickly reaches its cap for enrollment each day, typically testing 200-300 people. Given this restriction, further investigation into optimal sample allocation for the ~300 tests available per day will need to be performed.