Epidemiological and clinical characteristics of COVID-19 in Brazil using digital technology

  1. Faissal N. Hajar
  2. Miguel M. Fernandes-Silva
  3. Gustavo S. Pereira da Cunha
  4. Ali B. Hamud
  5. Geny H. Herrera
  6. Valderílio F. Azevedo

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Abstract

Background

Brazil has the third-highest number of Coronavirus disease 2019 (COVID-19) cases worldwide. Understanding the epidemiology of COVID-19 from reported cases is challenging due to heterogeneous testing rates. We estimated the number of COVID-19 cases in Brazil on a national and regional level using digital technology.

Methods

We used a web-based application to perform a population-based survey from March 21 st to August 29 th , 2020 in Brazil. We obtained responses from 243 461 individuals across all federative units, who answered questions on COVID-19-related symptoms, chronic diseases and address of residence. COVID-19 was defined as at least one of the following: fever, cough, dyspnea and nasal flaring, associated with a history of close contact with a suspect or confirmed COVID-19 case in the previous 14 days. A stratified two-stage weighted survey analysis was performed to estimate the population level prevalence of COVID-19 cases.

Results

After calibration weighing, we estimated that 10 339 461 cases of COVID-19 occurred, yielding a 2.75 estimated infection per officially reported case. Estimated/reported ratios varied across Brazilian states and were higher in states with lower human development indexes. Areas with lower income levels displayed higher rates of COVID-19 cases (66 vs 38 cases/1000 people in the lowest and highest income strata respectively, p<0.001), but presented lower rates of COVID-19 testing.

Conclusion

In this population-based survey using digital technology in Brazil, we estimated that the COVID-19 case rates were 2.75 times higher than officially reported. The estimated per reported case ratios were higher in areas with worse socioeconomic status.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.30.20204917: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has limitations that deserve attention. First, we used a web-based application that relies on spontaneous survey responses. Although access to the internet has been reported in 79% of households in Brazil, our sample was under-represented by elderly and low-income individuals.[30] Appropriate weighing and calibration helped mitigate this limitation, as estimated demographics became similar to census-based population data. Second, most COVID-19 cases were defined by self-reported symptoms and history of contact with a suspected/confirmed case, which may overestimate the number of symptomatic infections and does not account for asymptomatic infections. Nevertheless, this strategy is a feasible approach to evaluate large population-based surveys, particularly in settings with insufficient tests for screening every suspected case, such as most regions in the world during this pandemic. Finally, a noteworthy aspect of this initiative was its collaborative and non-profit nature. Over 30 professionals and over 10 companies from various fields gathered resources and expertise to help brazilians stay aware of their surroundings while also contributing to science. This study proves that it is possible to conduct nationwide high-level research in developing countries with limited resources. What is already known in this subject?: What this study adds?:

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.09.30.20204917v1 on medRxiv