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Predictive Model of COVID-19 Incidence and Socioeconomic Description of Municipalities in Brazil

Author(s): Isadora CR Carneiro, Eloiza KGD Ferreira, Janaina C da Silva, Guilherme Soares, Daisy M. Strottmann, Guilherme F. Silveira


A new highly contagious coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China, in December 2019. The virus has spread rapidly, reaching all continents around the world, causing a potentially lethal human respiratory infection, COVID-19. Despite being the best alternative in the current pandemic context, social distancing measures alone may not be sufficient to prevent SARS-CoV-2 spread, and the overall impact of the virus is of great concern.


Herein, we describe the demographic and socioe-conomic characteristics of 672 cities with at least 1 reported case of COVID-19 until June 26, 2020, and thus, determine a predictive model for the number of cases using data from patients tested for SARS-CoV-2 and the autoregressive integrated moving average (ARIMA) approach.


Predict model and epidemiological study based on aggregated data from the recent COVID-19. The SARS-CoV-2 has spread around the world wider than any previous human viral disease over a century and to predict the dynamic risk of the disease into subnational regions we used a thorough exploratory data analysis of COVID-19 cases according to the sociodemographic Brazilian municipalities indicators and an autoregressive integrated moving average (ARIMA) model.


Following the first case of COVID-19 in the country to the reporting period confirmed cases of the disease were present in cities of all Brazilian states, affecting 36.5% of the municipalities in Rio de Janeiro State. The inhabitants in cities with reported cases of COVID-19 represent more than 73.1% of the Brazilian population. Stratifying by age or gender groups of the inhabitants does not affect COVID-19 incidence (confirmed cases/100,000 inhabitants). The demographic density, the Municipal Human Development Index (MHDI) and the per

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