Remarkable variability in SARS-CoV-2 antibodies across Brazilian regions: nationwide serological household survey in 27 states

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Abstract

Population based data on COVID-19 are essential for guiding public policies. We report on the first of a series of planned seroprevalence surveys relying upon on household probabilistic samples of 133 large sentinel cities in Brazil, including 25,025 participants from all 26 states and the Federal District. Seroprevalence of antibodies to SARS-CoV-2, assessed using a lateral flow rapid test, varied markedly across the country’s cities and regions, from below 1% in most cities in the South and Center-West regions to up to 25% in the city of Breves in the Amazon (North) region. Eleven of the 15 cities with the highest seroprevalence were located in the North, including the six cities with highest prevalence which were located along a 2,000 km stretch of the Amazon river. Overall seroprevalence for the 90 cities with sample size of 200 or greater was 1.4% (95% CI 1.3–1.6). Extrapolating this figure to the population of these cities, which represent 25% of the country’s population, led to an estimate of 760,000 cases, as compared to the 104,782 cases reported in official statistics. Seroprevalence did not vary significantly between infancy and age 79 years, but fell by approximately two-thirds after age 80 years. Prevalence was highest among indigenous people (3.7%) and lowest among whites (0.6%), a difference which was maintained when analyses were restricted to the North region, where most indigenous people live. Our results suggest that pandemic is highly heterogenous, with rapid escalation in Brazil’s North and Northeast, and slow progression in the South and Center-West regions.

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  1. SciScore for 10.1101/2020.05.30.20117531: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval was obtained from the Brazilian’s National Ethics Committee (process number CAAE 30721520.7.1001.5313), with written informed consent from all participants.
    Consent: Ethical approval was obtained from the Brazilian’s National Ethics Committee (process number CAAE 30721520.7.1001.5313), with written informed consent from all participants.
    RandomizationUsing the data collection app, one individual was randomly selected from a listing of all household members completed at the beginning of the visit.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Following the introduction of the blood sample, reactive antibody:antigen:colloidal gold complexes, if present, are captured by antibodies against human IgM and IgG present on the on the “test” (T) line in the kit’s window, leading to the appearance of a dark-colored line.
    human IgM
    suggested: None
    Software and Algorithms
    SentencesResources
    ” The five response options are “white”, “brown” (“pardo” in Portuguese), “black”, “yellow” and “indigenous”.
    Portuguese
    suggested: None

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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. SciScore for 10.1101/2020.05.30.20117531: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.RandomizationOver an 8-day period ( from to May 14 to 21) , our field team visited a systematic sample of households in randomly selected census tracts .Blindingnot detected.Power Analysisnot detected.Sex as a biological variablePrevalence was similar among men and women .

    Table 2: Resources

    Antibodies
    SentencesResources
    Seroprevalence of antibodies to SARS-CoV2 , assessed using a lateral flow rapid test , varied markedly across the country’s cities and regions , from below 1 % in most cities in the South and Center-West regions to up to 25 % in the city of Breves in the Amazon ( North ) region .
    SARS-CoV2
    suggested: (Abcam Cat# ab273074, AB_2847846)

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


    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.