Airandes de Sousa Pinto, Carlos Alberto Rodrigues, C. L. Sobrinho, Edval Gomes dos Santos, Lívia Almeida da Cruz, Paulo Cesar Nunes, Matheus Gomes Reis Costa, M. O. da Costa Rocha
medRxiv, 2020
Introduction: Recently, 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. Methods: This 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. Results: The 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. Conclusion: Brazilian states showed heterogeneous data curves. Densitypopulation and socioeconomic inequality are associated with worse control of the epidemic.
Cited by 4 publications.
Field of study: Mathematics