Covid-19 epidemic curve in Brazil: A sum of multiple epidemics, whose income inequality and population density in the states are correlated with growth rate and daily acceleration

Abstract

ABSTRACTIntroductionRecently, we demonstrated that the polynomial interpolation method can be used to accurately calculate the daily acceleration of cases and deaths by Covid-19. The acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this work is to measure the diversity of epidemic curves and understand the importance of socioeconomic variables in the acceleration, peak cases and deaths by Covid-19 in Brazilian states.MethodsThis is an ecological study with time series analysis of new cases and deaths by Covid-19 in Brazil and its 27 federation units. Using the polynomial interpolation method, we calculated the daily cases and deaths with the measurement of the respective acceleration. We calculated the correlation coefficient between the epidemic curve data and socioeconomic data.ResultsThe combination of daily data and acceleration determined that the states of Brazil are in different stages of the epidemic. Maximum acceleration of peak cases, peak of cases, maximum acceleration of deaths and peak of deaths are associated with the Gini index and population density, but did not correlate with HDI and per capita income.ConclusionBrazilian states showed heterogeneous data curves. Density population and socioeconomic inequality are associated with worse control of the epidemic.