Routine Assessment of Infections, Prevention, and Control of SARS-CoV-2 on Unequal Populations

Juliane Foseca de Oliveira and colleagues at Fiocruz in Brazil will develop mathematical and statistical methods to model COVID-19 infection transmission, prevention and control across populations in Brazil to better inform local intervention efforts. Social and economic inequalities are known to shape the spread of diseases, therefore the team will integrate existing health data together with social and economic determinants for 5,570 Brazilian cities, as well as assessing data on the effects of the mitigation strategies and social mobility patterns. These data will be used to develop and apply statistical analyses and nonlinear mathematical modelling to forecast disease evolution and outcomes that consider the specific socio-economic conditions, which influence transmission rates. The results will be presented on a user-friendly surveillance platform that can be used by local governments and communities to identify the most effective control methods for their region.