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Income inequality and risk of infection and death by COVID-19 in Brazil


  • Lauro Miranda Demenech Universidade Federal do Rio Grande
  • Samuel C. Dumith Universidade Federal do Rio Grande (FURG)
  • Maria Eduarda Centena Duarte Vieira Universidade Católica de Pelotas (UCPel)
  • Lucas Neiva-Silva Universidade Federal do Rio Grande (FURG)



COVID-19, pandemic, health inequality, social determinants of health, Gini coefficient


Objective: To assess, through space-time analyses, whether the economic inequality of the Federative Units (FU) in Brazil can be associated with the risk of infection and death by COVID-19. Methods: This was an ecological study, based on secondary data on incidence and mortality rates for COVID-19. Data were analyzed at the state level, having the Gini coefficient as the main independent variable. Records of twelve days were used, spaced one week each, between April 21 and June 07, 2020. The weekly rate variation was calculated through Prais-Winsten regression, aiming measuring evolution of the pandemic in each FU. Spearman correlation test was used to assess correlation between the rates and their weekly evolution and the independent variables. Lastly, a spatial dependence diagnosis was conducted, and a Spatial Regression lag model was used when applicable. Results: Incidence and mortality rates of COVID-19 increased in all Brazilian FUs, being more pronounced among those with greater economic inequality. Association between Gini coefficient and COVID-19 incidence and mortality  rates remained even when demographic and spatial aspects were taken into account. Conclusions: Economic inequality can play an important role in the impact of COVID-19 in Brazilian territory, through absolute and contextual effects. Structural policies to reduce inequality are essential to face this and future health crises in Brazil.


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How to Cite

Demenech, L. M. ., Dumith, S. C. ., Vieira, M. E. C. D. ., & Neiva-Silva, L. . (2020). Income inequality and risk of infection and death by COVID-19 in Brazil. In SciELO Preprints.


Health Sciences