Tracking the emergence of disparities in the subnational spread of COVID-19 in Brazil using an online application for real-time data visualisation.

Mee, P.; Alexander, N.; Mayaud, P.; Colon-Gonzalez, F. J.; Abbott, S.; de Souza Santos, A. A.; Acosta, A. L.; Parag, K. V.; Pereira, R.; Prete, C. A.; Sabino, E. C.; Faria, N. R.; Brady, O. J.

Brazil is one of the countries worst affected by the COVID-19 pandemic. We have developed CLIC-Brazil an online application for the real-time visualisation of COVID-19 data in Brazil at the municipality level. In the app, case and death data are standardised to allow comparisons to be made between places and over time. Estimates of Rt , a measure of the rate of propagation of the epidemic, over time are also made. Using data from the app, regression analyses identified factors associated with; the rate of initial spread, early epidemic intensity and predictions of the likelihood of occurrence of new incidence maxima. Municipalities with higher metrics of social development experienced earlier onset and faster growing epidemics, although space and time were the predominant predictive factors. Differences in the initial epidemic intensity (mean Rt ) were largely driven by geographic location and the date of local onset. This study demonstrates that by monitoring, standardising and analysing the development of an epidemic at a local level, insights can be gained into spatial and temporal heterogeneities.