My journal by Thandeka Kurwakumire https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8 en-us 2024-10-20 11:26:29 UTC 2024-10-20 11:37:09 UTC hello@padlet.com https://padlet.net/icons/png/1f4d3.png Final thoughts kurwakumirethandeka004 https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177774812 From this article, I took away three main insights. Firstly, by analyzing how rainfall, temperature, and altitude affect malaria incidence, the study emphasized the significance of using mean, range, and time series plots to describe real-world data. Also, I saw how important data visualization is in effectively communicating trends. For example, the time series plots helped me know the relationship between malaria cases and changes in weather conditions. Lastly, poor presentation, such as clustered tables or limited color variation in graphs, can affect interpretation even if the figures are accurate.

]]> 2024-10-20 11:26:53 UTC https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177774812 Data Analysis kurwakumirethandeka004 https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177775417 The article clearly defined the qualitative data collected and its link to the study: the date (year and month) of diagnosis, address of the patients, age, sex, and the diagnosis results. The address helped to understand geographical variations at different altitudes, while age and sex showed the segments of the population that were more affected. The article shows the mean and range of metrological variables and the mean and mode of the cases(male). Percentages were also used to clarify the distribution of cases across different age groups. The time series plot for rainfall in Figure 1, showing temperature and malaria cases across the months of the year, effectively illustrated the trends in these variables over time. By placing graphs side by side, the article made it easy to observe the link between meteorological factors and malaria cases. Using tables to display different values was helpful, although some tables were clustered with big numbers, which made them difficult to interpret. Figures, such as time series plots of malaria incidence and rainfall, were well-labeled and straightforward to interpret, though more variation in color would have made them visually engaging.

]]> 2024-10-20 11:27:59 UTC https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177775417 Article summary kurwakumirethandeka004 https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177775682 In 2015, the World Health Organization (WHO) developed a global malaria elimination program to make a malaria-free world by 2030. The research focused on the population of Ethiopia, one of the most affected countries, and sampled Boricha district. It examines how climate change and geographical factors like elevation influence malaria transmission. Meteorological variables, such as rainfall, temperature, and humidity, were analyzed since they could impact the bionomics of malaria vectors, which could eventually determine malaria transmission intensity. Retrospective malaria morbidity data were collected from health facilities to determine the association between meteorological variables and topography with malaria incidence over the last eight years (2010–2017) in the Boricha district. Accordingly, the findings revealed that rainfall, temperature, and elevation were the major drivers of the disease.

]]> 2024-10-20 11:28:31 UTC https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177775682 Topic: Effects of Rainfall, temperature, and topography on malaria incidence in elimination-targeted district of Ethiopia kurwakumirethandeka004 https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177775955 The link to the article can be found here:

https://malariajournal.biomedcentral.com/articles/10.1186/s12936-021-03641-1

]]> 2024-10-20 11:29:04 UTC https://padlet.com/kurwakumirethandeka004/5tc7ykqydtny80b8/wish/3177775955