What is it about?

The coronavirus disease 2019 (COVID-19) pandemic is spreading rapidly throughout Africa and threatening millions of lives. This paper explains the results of a method that untangles the flow of the pandemic between all of the African countries, and generates weekly predictions that are sufficiently accurate to be suitable to guide ongoing policy decisions.

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Why is it important?

It is difficult for any country to absorb and makes sense of the bewildering array of data on the virus cases each day. Beyond understanding the infection spread, a policy maker needs to be able to predict the next week or so ahead to see what needs to be done to help control the infection, such as transportation regulation and border closures. Furthermore, it is impossible to know for any given country or climate how meteorological factors, such as humidity and temperature, might be important in such predictions without testing these effects. Lastly, it is not possible to develop tools intended to help guide policy implementation unless scientists work closely with governmental authorities who have to make such decisions. In this new work, a team of scientists was assembled from Africa, the US and Europe, working in partnership with the National Planning Authority of Uganda, to develop a tool that monitors the flow of coronavirus cases throughout Africa, and generates weekly predictions for case numbers within each country. The team is making the method freely available to all countries and agencies that can make use of this tool at this very critical time.


These findings also demonstrate why inter-country cooperation for COVID-19 control is essential to get better control of a pandemic that no country can manage well on their own.

Dr Steven J Schiff
Pennsylvania State University

Read the Original

This page is a summary of: Pan-African evolution of within- and between-country COVID-19 dynamics, Proceedings of the National Academy of Sciences, June 2021, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2026664118.
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