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Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil

Our take —

This was a population-based study that aimed to highlight epidemiological and clinical features of the COVID-19 epidemic in Brazil. Investigators found that the estimated basic reproductive number in Brazil was 3.1, and that areas with higher income per capita were more likely to have cases versus higher numbers of acute respiratory infections of unknown causes in lower income areas. The finding that higher income areas were more likely to have cases differs from other reports of COVID-19 being more prevalent in lower income communities; however, this could be due to greater access to testing in these areas. Overall, the study can be a useful tool for those wanting to improve surveillance and reporting of COVID-19 in Brazil.

Study design

Cross-Sectional

Study population and setting

This article presents epidemiologic and clinical features of the COVID-19 epidemic in Brazil up to May 31, 2020. This included estimating the basic reproductive number (R0) for Brazil and key municipalities, comparing these estimates with European countries, and identifying demographic factors associated with infection. Investigators also explored the association between socioeconomic status and COVID-19 geographic distribution.

Summary of Main Findings

Investigators analyzed 514,200 COVID-19 cases that were reported by 75% of municipalities across Brazil’s five regions. The most common symptoms among cases were cough, fever, and shortness of breath. The R0 for Brazil was 3.1 (95% Bayesian credible interval (BCI) 2.4-5.5). Investigators found this was higher, yet had overlapping 95% BCI intervals with European countries (Spain: 2.6, France: 2.5, United Kingdom: 2.6, and Italy: 2.5). Investigators found that census tracts with a higher per capita income were more likely to have cases of COVID-19, whereas census tracts with a lower per capita income were more likely to have cases of severe acute respiratory infections of unknown causes.

Study Strengths

The study used multiple surveillance reporting systems and has a large population-based sample.

Limitations

There was only individual level data for two of their surveillance reporting systems (i.e. REDCap and SIVEP-Gripe). Thus, investigators could not make individual level inferences concerning the association between socioeconomic status and COVID-19 diagnosis.

Value added

This is a detailed documentation of the nature of the COVID-19 epidemic in Brazil and can be useful in future efforts to improve surveillance and reporting in Brazil.

This review was posted on: 28 August 2020