A time-series ecological study protocol to analyze trends of incidence, mortality, lethality of COVID-19 in Brazil


  • Luiz Carlos de Abreu aProfessor Titular. Departamento de Educação Integrada em Saúde. Universidade Federal do Espírito Santo, Br; bAdjunct Professor. University of Limerick, Ireland; cBrazil and Ireland COVID-19 Observatory;
  • Khalifa Elmusharaf dDirector of Public Health Masters Programme Medical School, University of Limerick.
  • Carlos Eduardo Gomes Siqueira cBrazil and Ireland COVID-19 Observatory; dAssociate Professor of Environment and Public Health, School for the Environment. School for the Environment. University of Massachusetts, Boston, USA.




COVID-19, protocol, time-series, epidemiology, indicators


Introduction: Since the first case of COVID-19 was confirmed in February 2020, Brazil has reported more than 20 million cases and more than 600,000 deaths on October 31, 2021. The behavior of the pandemic was also different in the various regions of the country, from those with less economic development to those with greater economic development, such as the state of São Paulo.

Objective: to describe step-by-step time series for analyzing trends in mortality, lethality and incidence of COVID-19 in Brazil.

Methods: a protocol for an ecological study of time series, covering the 26 states and the federal district (Brasilia).

Results: The descriptions have the potential to provide information for the government and society in decision-making, about knowledge and conduct, clinical, epidemiological and research investments in health care for the Brazilian people. It is focused on fully understanding the spread of SARS-COV-2 infection in the Brazilian territory, and developing a database for public and universal access for comparative studies between countries and continents.

Conclusion: database built from ecological studies are essential for a full understanding of the virus behavior, its transmissibility, lethality and mortality, and a repository for data that’s been collected and integrated from multiple sources. It is a relevant tool for the search of information and decision-making in global health.


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