Subnational analysis of the COVID-19 epidemic in Brazil
Mellan, T. A.; Hoeltgebaum, H. H.; Mishra, S.; Whittaker, C.; Schnekenberg, R. P.; Gandy, A.; Unwin, H. J. T.; Vollmer, M. A. C.; Coupland, H.; Hawryluk, I.; Faria, N. R.; Vesga, J.; Zhu, H.; Hutchinson, M.; Ratmann, O.; Monod, M.; Ainslie, K.; Baguelin, M.; Bhatia, S.; Boonyasiri, A.; Brazeau, N.; Charles, G.; Cooper, L. V.; Cucunuba, Z.; Cuomo-Dannenburg, G.; Dighe, A.; Djaafara, B.; Eaton, J.; van Elsland, S. L.; FitzJohn, R.; Fraser, K.; Gaythorpe, K.; Green, W.; Hayes, S.; Imai, N.; Jeffrey, B.; Knock, E.; Laydon, D.; Lees, J.; Mangal, T.; Mousa, A.; Nedjati-Gilani, G.; Nouvellet, P.; Oli
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1Brazil is currently reporting the second highest number of COVID-19 deaths in the world. Here we characterise the initial dynamics of COVID-19 across the country and assess the impact of non-pharmaceutical interventions (NPIs) that were implemented using a semi-mechanistic Bayesian hierarchical modelling approach. Our results highlight the significant impact these NPIs had across states, reducing an average Rt > 3 to an average of 1.5 by 9-May-2020, but that these interventions failed to reduce Rt < 1, congruent with the worsening epidemic Brazil has experienced since. We identify extensive heterogeneity in the epidemic trajectory across Brazil, with the estimated number of days to reach 0.1% of the state population infected since the first nationally recorded case ranging from 20 days in Sao Paulo compared to 60 days in Goias, underscoring the importance of sub-national analyses in understanding asynchronous state-level epidemics underlying the national spread and burden of COVID-19.
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