<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="other" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">Gates Open Res</journal-id>
            <journal-title-group>
                <journal-title>Gates Open Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2572-4754</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/gatesopenres.14035.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Study Protocol</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Mar&#x00e9; cohort-profile: a prospective cohort study based in a socially vulnerable community during the COVID-19 pandemic in Rio de Janeiro, Brazil</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>A Batista-da-Silva</surname>
                        <given-names>Amanda</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-8256-2178</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>T Ranzani</surname>
                        <given-names>Olivia</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>M de Paulo</surname>
                        <given-names>Daniela</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>L Braunstein</surname>
                        <given-names>Mariana</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4878-0256</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>R Bozza</surname>
                        <given-names>Helena</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Fischer</surname>
                        <given-names>Ronald</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-3055-3955</uri>
                    <xref ref-type="aff" rid="a4">4</xref>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>V Ramos</surname>
                        <given-names>Grazielle</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>M C Dias</surname>
                        <given-names>Carolina</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-6878-3468</uri>
                    <xref ref-type="aff" rid="a6">6</xref>
                    <xref ref-type="aff" rid="a7">7</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>P da Silva</surname>
                        <given-names>Everton</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4878-0256</uri>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>E Arouca</surname>
                        <given-names>Luna</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>L S Bastos</surname>
                        <given-names>Leonardo</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>T Ranzani</surname>
                        <given-names>Otavio</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a8">8</xref>
                    <xref ref-type="aff" rid="a9">9</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Hamacher</surname>
                        <given-names>Silvio</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>A Bozza</surname>
                        <given-names>Fernando</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4878-0256</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a4">4</xref>
                    <xref ref-type="aff" rid="a10">10</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil</aff>
                <aff id="a2">
                    <label>2</label>Tecgraf Institute, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil</aff>
                <aff id="a3">
                    <label>3</label>Institute of Economics, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil</aff>
                <aff id="a4">
                    <label>4</label>D&#x2019;Or Institute for Research and Education, Rio de Janeiro, Brazil</aff>
                <aff id="a5">
                    <label>5</label>School of Psychology, Victoria University of Wellington, Wellington, New Zealand</aff>
                <aff id="a6">
                    <label>6</label>Associa&#x00e7;&#x00e3;o Redes de Desenvolvimento da Mar&#x00e9;, Rio de Janeiro, Brazil</aff>
                <aff id="a7">
                    <label>7</label>Graduate Program on Sociology and Anthropology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil</aff>
                <aff id="a8">
                    <label>8</label>Barcelona Institute for Global Health, ISGlobal, Universitat Pompeu Fabra, CIBER Epidemiolog&#x00ed;a y Salud P&#x00fa;blica, Barcelona, Spain</aff>
                <aff id="a9">
                    <label>9</label>Pulmonary Division, Heart Institute (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, S&#x00e3;o Paulo, Brazil</aff>
                <aff id="a10">
                    <label>10</label>National Institute of Infectious Disease Evandro Chagas, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:bozza.fernando@gmail.com">bozza.fernando@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>1</day>
                <month>2</month>
                <year>2023</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>7</volume>
            <elocation-id>22</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>24</day>
                    <month>1</month>
                    <year>2023</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 A Batista-da-Silva A et al.</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://gatesopenresearch.org/articles/7-22/pdf"/>
            <abstract>
                <p>
                    <bold>Background:</bold> Socially vulnerable populations were vastly affected by the COVID-19 pandemic. The pandemic significantly impacted Brazil, pressuring its healthcare system for several months, with high mortality rates, even among the youngest population. Cohort studies combining disease surveillance are essential for understanding virus circulation in the community, surrogates of protection, vaccine effectiveness, and demand for health resources.</p>
                <p>
                    <bold>Methods:</bold> Here, we present the protocol for a community-based prospective cohort study in the largest complex of 
                    <italic toggle="yes">favelas</italic>(slums) in Rio de Janeiro, Brazil (Complexo da Mar&#x00e9;). The study participants are residents initially recruited during a massive vaccination campaign in the community. Five waves of data collection at approximately six-month intervals were planned. The first two waves have been completed at the time of writing this study protocol, and the third is underway. The protocol comprises interviews, blood sampling,and records linkage with secondary data to enrich the profiles of cohort participants and community information. We will describe COVID-19 seroprevalence, socio-demographic characteristics, and the burden of COVID-19, followed by estimating the association of socioeconomic factors and the burden of disease with seroprevalence.</p>
                <p>
                    <bold>Discussion:</bold> The primary aims of the study are to assess COVID-19 clinical, epidemiological and genomic profiles and outcomes in residents from Mar&#x00e9;,including vaccine effectiveness, surrogates of immune protection, virus transmission in households, and the overall burden of the pandemic.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>cohort</kwd>
                <kwd>COVID-19</kwd>
                <kwd>serosurvey</kwd>
                <kwd>LMIC</kwd>
                <kwd>community</kwd>
                <kwd>vaccine</kwd>
                <kwd>household</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Instituto Todos pela Sa&#x00fa;de</funding-source>
                </award-group>
                <funding-statement>This work was supported by the Gates Foundation [INV-017293]. This work is part of the Grand Challenges ICODA pilot initiative, delivered by Health Data Research UK and funded by the Gates Foundation and the Minderoo Foundation. &#13;
This research received a grant from Instituto Todos pela Sa&#x00fa;de (ITpS) [Chamada P&#x00fa;blica 01_2021 &#x2013; Coortes]. </funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec sec-type="intro">
            <title>Introduction</title>
            <p>Since December 2019, the world population, health workers, and governments have been dealing with the challenges imposed by the COVID-19 pandemic. The burden across the globe was not only perceived through high morbidity and mortality rates but also by its effects on economic and social dimensions. Vulnerable populations, defined as groups of individuals susceptible to physical, biological, psychological, and socioeconomic stressors while lacking adequate resources to cope with these stressors
                <sup>
                    <xref ref-type="bibr" rid="ref-1">1</xref>
                </sup>, were vastly affected by the COVID-19 pandemic, both in high-income and low-and-middle-income countries (LMICs)
                <sup>
                    <xref ref-type="bibr" rid="ref-2">2</xref>
                </sup>.</p>
            <p>One of the countries most affected by the pandemic was Brazil, where the health system was under increased demand and pressure for several months, and the mortality rate was high, even among the young population
                <sup>
                    <xref ref-type="bibr" rid="ref-3">3</xref>
                </sup>. During the pandemic, initiatives articulated between social organisations and academia were essential to provide health and socioeconomic support to vulnerable populations, such as those living in 
                <italic toggle="yes">favelas</italic> or &#x201c;slums&#x201d; (a Brazilian urban community, sharing some features with slums in other countries, comprising highly populated areas, with different levels of urbanisation and informal settlements, historically neglected from govern) - usually crowded areas with several basic needs
                <sup>
                    <xref ref-type="bibr" rid="ref-4">4</xref>
                </sup>.</p>
            <p>Cohort studies associated with disease surveillance are essential for understanding pathogens' circulation, surrogates of protection, disease burden, and demand for health services, especially in poor communities in LMIC. By following individuals over time, cohorts provide granular data for monitoring disease trends
                <sup>
                    <xref ref-type="bibr" rid="ref-5">5</xref>,
                    <xref ref-type="bibr" rid="ref-6">6</xref>
                </sup> and the long-term impacts of the pandemic. Prospective studies may fill knowledge gaps regarding the burden of disease and risk factors in a vulnerable population
                <sup>
                    <xref ref-type="bibr" rid="ref-7">7</xref>
                </sup>.</p>
            <p>Here, we describe the protocol and the baseline demographic profile of a cohort design, which started recruiting during the COVID-19 pandemic in Complexo da Mar&#x00e9;, a neighborhood of Rio de Janeiro and one of the largest groups of 
                <italic toggle="yes">favelas</italic> in Brazil. The Mar&#x00e9; Cohort is embedded in several initiatives recently implemented in Mar&#x00e9;, such as socioeconomic support, health care, and surveillance, managed by an innovative organisational arrangement involving non-governmental organisations (NGOs), research institutions, private funders, and local government
                <sup>
                    <xref ref-type="bibr" rid="ref-8">8</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref-10">10</xref>
                </sup>.</p>
            <sec>
                <title>Objectives</title>
                <p>We aim to assess clinical, epidemiological and genomic profiles, outcomes and the impact of the COVID-19 pandemic in the residents from Mar&#x00e9;. The specific objectives of the Mar&#x00e9; Cohort are:</p>
                <list list-type="bullet">
                    <list-item>
                        <label>1.</label>
                        <p>To evaluate the effectiveness of the COVID-19 vaccines and the temporal course of seroprevalence of SARS-CoV-2 antibodies</p>
                    </list-item>
                    <list-item>
                        <label>2.</label>
                        <p>To perform genomic surveillance and identify the transmission chains of SARS-Cov-2 in the community</p>
                    </list-item>
                    <list-item>
                        <label>3.</label>
                        <p>To estimate long-term health impacts of COVID-19 (long COVID-19 and mental health)</p>
                    </list-item>
                    <list-item>
                        <label>4.</label>
                        <p>To evaluate the association of socioeconomic aspects, access to primary care services and the burden COVID-19 pandemic</p>
                    </list-item>
                </list>
            </sec>
        </sec>
        <sec>
            <title>Protocol</title>
            <sec>
                <title>Study Design</title>
                <p>The study is a community-based prospective cohort study in Mar&#x00e9;, Rio de Janeiro, Brazil. Ethical approval was obtained from the National Research Ethics Committee (IRB/CONEP) (CAEE: 49726921.6.0000.5248 and 44180821.1.0000.5249).</p>
            </sec>
            <sec>
                <title>Study Status</title>
                <p>We planned five waves at approximately six-month intervals. The study is planned to finish by the beginning of 2024. Data collection is ongoing; the first and second waves have been completed, and the third was initiated in December 2022.</p>
            </sec>
            <sec>
                <title>Setting</title>
                <p>This prospective cohort study was designed to be conducted among the residents of Mar&#x00e9; in Rio de Janeiro municipality, an area composed of 16 
                    <italic toggle="yes">favelas,</italic> one of the largest set of 
                    <italic toggle="yes">favelas</italic> in Brazil. Mar&#x00e9; is the city&#x2019; sninth most populous neighbourhood with more than 140,000 inhabitants
                    <sup>
                        <xref ref-type="bibr" rid="ref-11">11</xref>
                    </sup> spread over 4.3 km&#x00b2;
                    <sup>
                        <xref ref-type="bibr" rid="ref-12">12</xref>
                    </sup>. Its population is mainly young (51.9% under 30 years old)
                    <sup>
                        <xref ref-type="bibr" rid="ref-13">13</xref>
                    </sup> and almost twice the size of Rio's second largest 
                    <italic toggle="yes">favela</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref-12">12</xref>
                    </sup>.</p>
                <p>Mar&#x00e9; is located near the city centre and is surrounded by major highways. Although the region presents informal settlements with substandard housing, most residences have running water, access to a sewage network and public lighting
                    <sup>
                        <xref ref-type="bibr" rid="ref-13">13</xref>
                    </sup>. The chaotic urbanisation of 
                    <italic toggle="yes">favelas</italic> has resulted in a heterogeneous population spread within the limited area, generating a high population density and vulnerable regions. With respective educational and healthcare facilities, 44 public schools are attending the territory in 2013
                    <sup>
                        <xref ref-type="bibr" rid="ref-13">13</xref>
                    </sup>, and the public health system provides seven primary healthcare units, three psychosocial centres, a mobile outreach clinic, an emergency unit, and a reference public hospital to the area (
                    <xref ref-type="fig" rid="f1">Figure 1</xref>).</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>Figure 1. </label>
                    <caption>
                        <title>Complexo da Mar&#x00e9; territory.</title>
                        <p>Each coloured circle illustrates a different health institution in Mar&#x00e9;. Primary healthcare units are represented in orange, psychosocial centres in yellow, mobile outreach clinics in white, emergency unit in blue and public hospital in red. The subtitles on the left attribute a number to each of the 16 
                            <italic toggle="yes">favelas</italic> which constitute the community, while the yellow line delimits their territory. The map illustrates how Mar&#x00e9; is not entirely continuous since the area zoomed ("Marc&#x00ed;lio Dias&#x201d;,16) is located on the far left of &#x201c;Praia de Ramos&#x201d; (15). The Federal University of Rio de Janeiro (UFRJ) and Fiocruz, written in light blue, are significant scientific institutions near to community. The other coloured lines (red, yellow and blue) illustrate the main roads that cross Mar&#x00e9; and its vicinity. In addition, the tree token symbolises green space.This figure is an original figure produced by the author(s) for this review article.</p>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://gatesopenresearch-files.f1000.com/manuscripts/15333/233350ff-fbf3-488c-be0c-4fd04a5940f6_figure1.gif"/>
                </fig>
                <p>The community is among the most vulnerable neighbourhoods in the municipality (
                    <xref ref-type="table" rid="T1">Table 1</xref>), evidenced by its low Human Development Index (HDI: 0.686), ranked 123rd out of 126 in Rio de Janeiro. The GINI index of 0.39 may suggest a more homogenous and less unequal community
                    <sup>
                        <xref ref-type="bibr" rid="ref-12">12</xref>
                    </sup>. Mar&#x00e9; has nearly three times as many illiterate residents and a one-third monthly per capita income of USD 294 compared with the municipality estimates. In terms of health indicators, Mar&#x00e9; has higher incidences of tuberculosis (155.7 per 100,000 population), higher infant mortality rates (16.7 per 100,000 live births), and higher mortality rates due to external causes (105.8 standardised deaths per 100,000 population) than the municipality (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <table-wrap id="T1" orientation="portrait" position="anchor">
                    <label>Table 1. </label>
                    <caption>
                        <title>Territorial, socioeconomic and health indicators of Mar&#x00e9; neighbourhood and Rio de Janeiro municipality based on the 2010 National Census.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="center" colspan="1" rowspan="1"/>
                                <th align="center" colspan="1" rowspan="1" valign="top">Complexo da Mar&#x00e9;</th>
                                <th align="center" colspan="1" rowspan="1" valign="top">Rio de Janeiro
                                    <break/>Municipality</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Territorial dimension</bold>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Area - 2020 
                                        <xref ref-type="other" rid="TFN3">(a)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">4.3 km&#x00b2;</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,204 km&#x00b2;</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Population - 2010 
                                        <xref ref-type="other" rid="TFN2">(b)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">129,770</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">6,320,446</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Population density - 2010 
                                        <xref ref-type="other" rid="TFN2">(b)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">30,179/km&#x00b2;</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">5,266/km&#x00b2;</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Number of households - 2010 
                                        <xref ref-type="other" rid="TFN2">(b)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">41,731</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">2,144,445</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Socio-economic indicators</bold>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Human Development Index (HDI) - 2010 
                                        <xref ref-type="other" rid="TFN3">(c)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">0.674</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">0.799</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">GINI index - 2010
                                        <xref ref-type="other" rid="TFN3">(c)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">0.39</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">0.62</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Ageing index - 2010 
                                        <xref ref-type="other" rid="TFN2">(b)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">27</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">77</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Monthly Per capita income
                                        <xref ref-type="other" rid="TFN5">*</xref> - 2010 
                                        <xref ref-type="other" rid="TFN3">(c)</xref>
                                    </italic> </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">USD 294.0</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">USD 895.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Workers with an income of up to 2 minimum wages - 2010
                                        <xref ref-type="other" rid="TFN3">(c)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">79%</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">54%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Illiteracy (15 years of age or older) - 2010 
                                        <xref ref-type="other" rid="TFN2">(b)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">7.7%</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">2.9%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Household sewage disposal - 2010 
                                        <xref ref-type="other" rid="TFN3">(c)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">99%</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">99%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Health indicators-</bold> 
                                    <italic toggle="yes"> 2019</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Tuberculosis incidence per 100,000 
                                        <xref ref-type="other" rid="TFN4">(d)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">155.7</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">140.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Infant mortality per 1,000 live births 
                                        <xref ref-type="other" rid="TFN4">(d)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">16.7</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">12.1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Mortality rate for infectious disease (Chapter I ICD-10) 
                                        <xref ref-type="other" rid="TFN4">(d)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">59.4
                                    <xref ref-type="other" rid="TFN6">**</xref>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">59.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Mortality rate for neoplasms (tumours) (Chapter II ICD-10) 
                                        <xref ref-type="other" rid="TFN4">(d)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">26.4
                                    <xref ref-type="other" rid="TFN6">**</xref>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">158.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Mortality rate for circulatory system (Chapter IX ICD-10) 
                                        <xref ref-type="other" rid="TFN4">(d)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">277.6
                                    <xref ref-type="other" rid="TFN6">**</xref>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">269.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Mortality rate for external causes (Chapter XX ICD-10) 
                                        <xref ref-type="other" rid="TFN4">(d)</xref>
                                    </italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">105.8
                                    <xref ref-type="other" rid="TFN6">**</xref>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">79.3</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn>
                            <p id="TFN1">(a) 2020 carried out by the Pereira Passos Municipal Urbanism Institute (IPP)</p>
                            <p id="TFN2">(b)2010 census carried out by the Brazilian Institute of Geography and Statistics (IBGE), published on the Pereira Passos Municipal Urbanism Institute (IPP)</p>
                            <p id="TFN3">(c) 2010 census carried out by the Brazilian Institute of Geography and Statistics (IBGE), published on Atlas do Desenvolvimento Humano no Brasil</p>
                            <p id="TFN4">(d) Health systems' databases provided by the Municipal Health Department</p>
                            <p id="TFN5">(*) Average nominal monthly household income per capita. The minimum wage in 2010 was $306.1</p>
                            <p id="TFN6">(**) The rate in Mare standardised for Rio de Janeiro municipality - per 100,000</p>
                        </fn>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec>
                <title>Governance and Management</title>
                <p>This cohort study is part of a platform composed of  several initiatives developed in the territory to assist residents during the COVID-19 pandemic
                    <sup>
                        <xref ref-type="bibr" rid="ref-8">8</xref>&#x2013;
                        <xref ref-type="bibr" rid="ref-10">10</xref>
                    </sup>, with diverse actions and partnerships (
                    <xref ref-type="fig" rid="f2">Figure 2</xref>). A steering committee (SC) composed of the principal investigator and one member of four institutions was assembled to manage the cohort. The SC has held weekly meetings to plan and decide on support action in the territory. Furthermore, two coordination units report directly to the SC, one for field-related actions and the other for data-related activities. A communication team was constituted to perform direct engagement and targeted communication activities, composed of different professionals: coordinator, designer, illustrator, social media manager and content producer, web designer, photographer, video maker, and image editor. The field team consists of 17 community mobilisers, seven of them with technical training in nursing, and 14 community health workers (CHWs) responsible for direct contact with the cohort participants, interviewing, laboratory testing and clarifying questions about the project, and reporting directly to the field coordination. The CHWs were recruited specifically for the project on a part-time basis.Firstly, five candidates were selected by the manager of each primary healthcare unit. Then, after an interviewing process with the field coordinator, two were recruited/selected. The recruitment process was based on nursing technical training and the largest work experience in the unit.</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>Figure 2. </label>
                    <caption>
                        <title>Cohort organisational chart.</title>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://gatesopenresearch-files.f1000.com/manuscripts/15333/233350ff-fbf3-488c-be0c-4fd04a5940f6_figure2.gif"/>
                </fig>
                <p>In addition, the data working group is divided into management and analytics teams, who reports to the data coordination team. The former is responsible for curating and integrating the data and the latter consists of epidemiologists, data scientists and vaccinologists performing research and data analysis.</p>
                <p>The corresponding author is the study principal investigator (PI) and part of the steering committee, along with three co-authors. Two authors are part of the field coordination team, and eight compose the data working group.</p>
                <p>The laboratory testing structure has two major components to support the surveillance actions in Mar&#x00e9;. "
                    <italic toggle="yes">Dados do Bem</italic>", the Brazilian symptom tracking app
                    <sup>
                        <xref ref-type="bibr" rid="ref-14">14</xref>
                    </sup>, was designed by the PI of this project with a team of developers (Zoox Smart Data) to detect symptomatic cases, track contacts, and identify areas at increased risk of SARS-CoV-2 infection. The app was free of charge and available in iOS and Android systems. The app manages the user registration and SARS-CoV-2 testing process, working as a platform for hosting the data of serological and RT-qPCR test results for cohort participants. The COVID-19 diagnosis unit (
                    <italic toggle="yes">Unidade de Apoio ao Diagn&#x00f3;stico da COVID-19,</italic> UNADIG-FIOCRUZ) provides laboratory support with the distribution and analysis of serological and RT-qPCR results from participants and Mar&#x00e9; residents. Tests were free of charge to participants.</p>
            </sec>
            <sec>
                <title>Population selection and participants</title>
                <p>The cohort comprises participants that reside in Mar&#x00e9;. The inclusion criteria considered all applicants must be permanent residents of Mar&#x00e9; and complete an Informed Consent (IC) form before enrolment. We excluded residents with incomplete identification data, such as invalid unique identifier numbers or incomplete addresses and telephone numbers.</p>
                <p>We calculated there quired number of responders using the formula for prevalence studies
                    <sup>
                        <xref ref-type="bibr" rid="ref-15">15</xref>
                    </sup>. The appropriate sample size required for different prevalence and precision levels is shown in 
                    <xref ref-type="fig" rid="f3">Figure 3</xref>. We estimated that an overall minimum sample size of approximately 2,400 participants, with an alpha of 0.05 and precision of 2%, is sufficient to ensure the outcome is significant and provides meaningful results.</p>
                <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                    <label>Figure 3. </label>
                    <caption>
                        <title>Estimated total sample size for prevalence studies.</title>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://gatesopenresearch-files.f1000.com/manuscripts/15333/233350ff-fbf3-488c-be0c-4fd04a5940f6_figure3.gif"/>
                </fig>
            </sec>
            <sec>
                <title>Participant recruitment and consent</title>
                <p>The initial round of recruitment occurred during the large-scale COVID-19 vaccination campaign from July 29
                    <sup>th</sup>, 2021 to August 1
                    <sup>st</sup>, 2021, when approximately 36,000 first doses of ChAdOx1 were administered
                    <sup>
                        <xref ref-type="bibr" rid="ref-16">16</xref>
                    </sup>. Since then, study participants have been monitored via household follow-up.</p>
                <p>The enrolment strategy has three stages. In the first stage, a trained interviewer invites participants, explains the research purpose and testing procedures, clarifies questions, and obtains informed consent - in the case of participants who are illiterate, the researcher reads the consent inform supervised by a family member of the participant, and a thumbprint is taken. In the second stage, the participant answers a questionnaire filled out by a trained mobiliser. In the third stage, they register at the app - in the case of illiterate participants, the mobiliser completes the registration - and takes a serological test - a specialised technician collects the material (dry blood spot). For children, parental consent is obtained, and the guardian answers a simplified and adapted questionnaire. Participants can withdraw from the study anytime, even after providing written, informed consent. This enrolment strategy will be used in all waves of data collection.</p>
                <p>The Mar&#x00e9; cohort is based on household units. Following the enrolment of an index adult, the mobilisers and CHWs conducted home visits to map and recruit new family members, following the same steps executed during the recruitment of the first adult (i.e., applying an informed consent form to the new family member and collecting information as a new entry).</p>
            </sec>
            <sec>
                <title>Representativeness</title>
                <p>Participants were pragmatically included in the cohort since recruitment occurred during the pandemic. Our efforts at mitigating selection bias and achieving representativeness combined social, spatial, and demographic characteristics, recruiting participants at different times and days of the week and spatial locations within Mar&#x00e9;. We plan to adjust cohort estimates using sampling weights derived from characteristics reported in the 2013 Mar&#x00e9; survey, where we have a complete demographic cross-sectional evaluation of the entire community
                    <sup>
                        <xref ref-type="bibr" rid="ref-13">13</xref>
                    </sup>.</p>
            </sec>
            <sec>
                <title>Follow-up</title>
                <p>This cohort study will be divided into waves, each corresponding to different stages of analyses and data collection (
                    <xref ref-type="fig" rid="f4">Figure 4</xref>). The study was initially planned to hold five waves at approximately six-month intervals and is expected to end at the beginning of the first half of 2024. The first wave occurred from August 2021 to January 2022, and we evaluated infection by COVID-19 and the socio-demographic characteristics of the target population. The second wave ran from February to July 2022, and the analyses focused on socioeconomic factors and COVID-19 response to the vaccine.</p>
                <fig fig-type="figure" id="f4" orientation="portrait" position="float">
                    <label>Figure 4. </label>
                    <caption>
                        <title>Cohort follow-up.</title>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://gatesopenresearch-files.f1000.com/manuscripts/15333/233350ff-fbf3-488c-be0c-4fd04a5940f6_figure4.gif"/>
                </fig>
                <p>The first two waves have been completed at the time of writing this study protocol, and the third is underway. Following a similar enrolment and data collection strategy from the first and second waves, the third wave focuses on understanding the residents&#x00b4; perspective about vaccination, primary care services, and socioeconomic aspects during the pandemic. Future (fourth and fifth) waves are planned to address  the conduct of  COVID-19 surveillance and other health problems prevalent in vulnerable communities in low-and-middle-income countries. These new waves will follow the same strategy of recruitment, data collection, communication, and engagement used in waves one-three. The questionnaire will be adapted to incorporate the dimensions of other diseases and the follow-up questions from previous waves, using the same teams and structure already in place in the territory.</p>
            </sec>
            <sec>
                <title>Data Collection</title>
                <p>The protocol includes interviews, blood sampling and record linkage to secondary data associated with cohort participants.</p>
            </sec>
            <sec>
                <title>Data access</title>
                <p>Once the data has been collected, access to individual data will require a formal request to the authors and the cohort&#x2019;s Steering Committee. This route of access follows the guidelines and practices according to the Brazilian General Data Protection Regulation (Lei Geral da Prote&#x00e7;&#x00e3;o de Dados 13.709/2018) for data integrity and security.</p>
            </sec>
            <sec>
                <title>Questionnaires Development</title>
                <p>A group of 11 specialists, consisting of clinical researchers, epidemiologists, phycologists, social workers, and vaccinologists, developed the standardised questionnaires to collect data from the cohort participants. They were responsible for creating the protocol, and eight form this paper authorship. The questionnaires were validated with local community members, followed by interviewers' training. Questionnaire data was collected directly on a standardised form at each contact via an electronic data capture system (REDCap &#x2013; Research Electronic Data Capture)
                    <sup>
                        <xref ref-type="bibr" rid="ref-17">17</xref>
                    </sup>. The data was collected using a mobile device (tablet) during the interview, uploaded into REDCap at the end of the day, and then deleted from the device to preserve the integrity of the participants.</p>
                <p>Questionnaires applied to adults included variables of socio-demographic characteristics, socioeconomic levels, general health, vaccines (including adverse events), well-being, search for medical assistance, the self-reported status of COVID-19 infection, and risk factors for exposure to COVID-19. Well-being questions addressed generalised anxiety and depression using the Patient Health Questionnaire-4 (PHQ-4)
                    <sup>
                        <xref ref-type="bibr" rid="ref-18">18</xref>
                    </sup>, a standardised screening instrument. We also included an item measuring happiness
                    <sup>
                        <xref ref-type="bibr" rid="ref-19">19</xref>
                    </sup> and two items from the Life Orientation Test
                    <sup>
                        <xref ref-type="bibr" rid="ref-20">20</xref>
                    </sup>, indicating overall optimism levels. A specific questionnaire for those under 18 years contains variables of socio-demographic characteristics, education level status, general health and medical assistance.</p>
                <p>Data from different sources were linked directly using a unique identifier or probabilistic linkage when applicable. After data preparation and integration, participants were de-identified and anonymised for analysis. Data governance and curation activities were described in a Data Protection Assessment document that followed the Brazilian General Data Protection Regulation (
                    <italic toggle="yes">Lei Geral de Prote&#x00e7;&#x00e3;o de Dados</italic>)
                    <sup>
                        <xref ref-type="bibr" rid="ref-21">21</xref>
                    </sup>.</p>
            </sec>
            <sec>
                <title>Testing Strategy</title>
                <p>We collected five blood spots on filter paper with a lancet for finger-prick in each wave of data collection. The primary data analysed were the serological tests for anti-SARS-CoV-2 IgG antibodies. We used the Perkin-Elmer (Rio de Janeiro, RJ, Brazil) kitto identify IgG immunoglobulin class antibodies to SARS-CoV-2, a fully automated system dried blood spot based able to test a large population efficiently
                    <sup>
                        <xref ref-type="bibr" rid="ref-23">22</xref>,
                        <xref ref-type="bibr" rid="ref-23">23</xref>
                    </sup>.</p>
            </sec>
            <sec>
                <title>Vaccination campaign</title>
                <p>On January 17
                    <sup>th</sup> 2021, the Brazilian government launched a nationwide vaccination campaign against COVID&#x2013;19 following an age-based priority
                    <sup>
                        <xref ref-type="bibr" rid="ref-24">24</xref>
                    </sup>. The Brazilian National Immunisation Programme (PNI) is responsible for the vaccination schedule and the administration of free doses of the following vaccines: Sinovac-CoronaVac, ChAdOx1-S/nCoV-19 (Oxford-AstraZeneca), BNT162b2 (Pfizer/BioNTech) and Ad26.COV2.S (Janssen). Six months after the vaccination roll-out started in the country (July 2021), a mass vaccination campaign (Vacina Mar&#x00e9;) was carried out in Complexo da Mar&#x00e9;, which increased the first dose coverage from 38% of to 93% in four days. Along with this campaign, the cohort study started the recruitment phase in the territory.</p>
                <p>The COVID-19 immunisation data from cohort participants were made available for research and analysis purposes through the PNI Information System (
                    <italic toggle="yes">Sistema de Informa&#x00e7;&#x00e3;o do Programa Nacional de Imuniza&#x00e7;&#x00e3;o</italic>, [SI-PNI]), a secondary data made available by the city health department. SI-PNI is Brazil's central data archive for vaccine doses administered. It contains information on demographics (age, sex and place of residence), vaccine platform, the number of doses received, date of administration and location.</p>
            </sec>
            <sec>
                <title>Secondary data</title>
                <p>We plan to perform a deterministic followed by probabilistic record linkage between cohort participants and administrative data collected from the Brazilian health systems, such as COVID-19-related surveillance systems for mild and severe cases.</p>
            </sec>
            <sec>
                <title>Preliminary data</title>
                <p>Overall, 6,429 residents in Mar&#x00e9; answered the questionnaire during the first wave, 5,923 (92%) were adults, and 506 (8%) were under 18 (
                    <xref ref-type="table" rid="T2">Table 2</xref>). The sample is adherent to the size predicted, considering an alpha of 0.05 and precision of 2%.</p>
                <table-wrap id="T2" orientation="portrait" position="anchor">
                    <label>Table 2. </label>
                    <caption>
                        <title>Demographic characteristics (
                            <italic toggle="yes">n</italic>): cohort baseline, Mar&#x00e9; and Rio de Janeiro municipality</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                                <th align="center" colspan="1" rowspan="1" valign="top">Cohort
                                    <xref ref-type="other" rid="TFN7">&#x00b9;</xref>
                                    <break/>N = 6,429</th>
                                <th align="center" colspan="1" rowspan="1" valign="top">Mar&#x00e9;
                                    <xref ref-type="other" rid="TFN8">&#x00b2;</xref>
                                    <break/>N = 129,770</th>
                                <th align="center" colspan="1" rowspan="1" valign="top">Rio de Janeiro
                                    <xref ref-type="other" rid="TFN8">&#x00b2;</xref>
                                    <break/>N = 6,320,446</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Age group, years</bold>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">0&#x2013;9</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">211 (3%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">21,260 (16%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">759,791 (12%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">10&#x2013;19</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">646 (11%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">23,473 (18%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">930,717 (14%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">20&#x2013;29</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,697 (26%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">25,746 (20%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1059,810 (17%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">30&#x2013;39</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,175 (18%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">22,951 (18%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">992,986 (16%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">40&#x2013;49</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">862 (13%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">16,514 (13%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">876,487 (14%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">50&#x2013;59</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">822 (13%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">10,800 (8%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">759,804 (12%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">60+</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,016 (16%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">9,026 (7%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">940,851 (15%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Sex</bold>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Female</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">4,456 (69%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">66,027 (51%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">3360,629 (53%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Male</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,973 (31%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">63,743 (49%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">2959,817 (47%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Self-reported skin colour
                                        <xref ref-type="other" rid="TFN9">&#x00b3;</xref>
                                    </bold>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                                <td align="center" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Brown</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">3,108 (48%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">62,156 (48%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">2318,675 (37%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">White</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,777 (28%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">51,580 (40%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">3239,888 (51%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Black</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,215 (19%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">14,341 (11%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">708,148 (11%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Asian</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">  154 (2%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,445 (1%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">45,913 (1%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Indigenous</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">30 (1%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">178 (0%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">5,981 (0%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x00a0;&#x00a0;&#x00a0;&#x00a0;
                                    <italic toggle="yes">Missing</italic>
                                </td>
                                <td align="center" colspan="1" rowspan="1" valign="top">  145 (2%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">69 (0%)</td>
                                <td align="center" colspan="1" rowspan="1" valign="top">1,842 (0%)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn>
                            <p id="TFN7">&#x00b9;Data collected from August 2021 to January 2022.</p>
                            <p id="TFN8">&#x00b2; 2010 census carried out by the Brazilian Institute of Geography and Statistics (IBGE)</p>
                            <p id="TFN9">&#x00b3;Skin colour was recorded as self-reported race or skin colour, classified as Branco (White), Preto (Black), Pardo (Brown), Amarelo (Asian), or Ind&#x00ed;gena (Indigenous).</p>
                        </fn>
                    </table-wrap-foot>
                </table-wrap>
                <p>A brief description of the baseline characteristics of the cohort, Mar&#x00e9; neighbourhood Census 2019 and Rio de Janeiro municipality Census 2010, is shown in 
                    <xref ref-type="table" rid="T2">Table 2</xref>. The majority of participants are up to 39 years old. The cohort has a lower proportion of children (newborn-nine years) and a higher proportion of the elderly than Mar&#x00e9;. Females are the majority of the three samples; almost half of the cohort and Mar&#x00e9; are self-declared 
                    <italic toggle="yes">Pardo</italic>.</p>
                <p>Evaluating anti-SARS-CoV-2 antibody prevalence is part of the next step of this cohort analysis, and at the time of writing this study protocol, we have results from 6,272 (97.6% of 6,429) tests for IgG. A total of 157 (2.4%) individuals not tested or with inconclusive results were excluded at this stage (
                    <xref ref-type="fig" rid="f5">Figure 5</xref>).</p>
                <fig fig-type="figure" id="f5" orientation="portrait" position="float">
                    <label>Figure 5. </label>
                    <caption>
                        <title>Participant flow chart.</title>
                    </caption>
                    <graphic orientation="portrait" position="float" xlink:href="https://gatesopenresearch-files.f1000.com/manuscripts/15333/233350ff-fbf3-488c-be0c-4fd04a5940f6_figure5.gif"/>
                </fig>
                <p>Immunisation information was obtained for 5,780 participants. We excluded 92 adults based on system registry inconsistencies data (5,688 with complete immunisation status).</p>
                <p>Full baseline data will be included in the final dataset.</p>
            </sec>
            <sec>
                <title>Outcomes</title>
                <p>The primary outcome of this study will be the seroprevalence of SARS-CoV-2 antibodies in the population. Secondary outcomes will include symptomatic and asymptomatic COVID-19 infections and severe cases with hospitalisations and deaths related to COVID-19, and long-term impacts, such as the prevalence of long COVID-19 symptoms and mental health conditions.</p>
            </sec>
            <sec>
                <title>Data analysis</title>
                <p>We will describe seroprevalence, socio-demographic characteristics, and the burden of the disease for the baseline and each wave using descriptive statistics. Categorical variables will be displayed in absolute and relative frequencies, and continuous variables will be described as means and standard deviation (SD) or medians and interquartile range (p25-p75). When applicable, missing values will be imputed using multiple imputations with chained equations (MICE)
                    <sup>
                        <xref ref-type="bibr" rid="ref-25">25</xref>
                    </sup>.</p>
                <p>Direct comparisons between baseline and waves characteristics will be performed using statistical hypothesis testing, such as Pearson&#x00b4;s chi-square test, Fisher&#x00b4;s exact test, Student&#x00b4;s t-test or Wilcoxon-Mann-Whitney test. Correlation between variables will be calculated using Spearman&#x2019;s rho correlation.</p>
                <p>We will use regression modelling approaches to estimate the association of socioeconomic characteristics and seroprevalence of SARS-CoV-2 infection. The response variable will be the seroprevalence outcome; therefore, we will apply generalised linear models accounting for repeated measures when necessary. We have considered study and work status, number of healthcare workers, the density of residents in households, use of public transport, and number of vaccinated residents as exposure variables. Numerical variables will be modelled using cubic splines. All statistical analyses are to be performed in R
                    <sup>
                        <xref ref-type="bibr" rid="ref-26">26</xref>
                    </sup>. A significance level of 0.05 will be considered. We will follow STROBE recommendations. Dictionaries data from the first and the second waves are available on the extended data.</p>
            </sec>
            <sec>
                <title>Dissemination of study results</title>
                <p>Monthly meetings with local leaders, agents from the NGO Redes Mar&#x00e9; and the primary healthcare units&#x2019; workers are to be held throughout the study to notify and discuss, for example, the main self-reported comorbidities, vaccine status, number of tests and data collection at each phase. The meeting's objectives are to show the scientific results from the cohort to stakeholders and create a space for scientific discussions about how this study can improve healthcare in a vulnerable population. Newsletters addressing the pandemic context and initiatives which happened in the community were regularly disclosed on print and digital platforms, targeting the cohort participants, healthcare workers and the Mar&#x00e9; population.</p>
            </sec>
        </sec>
        <sec sec-type="conclusions | discussion">
            <title>Conclusions/discussion</title>
            <p>Cohort studies conducted in urban poor communities are essential to understand the spread of pathogens, protective strategies, disease burden and health resource needs in areas where epidemiological information is usually limited.</p>
            <p>This study aims to contribute a new source of data on infectious and poverty-related diseases for researchers, policymakers and programme implementers who wish to improve health services for a vulnerable population in an urban area of a LMIC. The results will be used to support the establishment of a public health data repository and communication and mobilisation activities that can promote data-driven decision-making and public health action in other vulnerable communities, especially in LMICs.</p>
            <p>Data and results will be limited to the follow-up of participants during wave collections. To mitigate potential dropout, engagement and communication activities will be performed with Mar&#x00e9; residents. The communication team will be in charge of the dissemination and information in different platforms, with weekly actions in social media, newsletters posters and cards. In parallel, the field team will be in direct contact with the participants during waves. We also plan to conduct events such as seminars to disseminate the insights from the study. Moreover, records linkage with secondary data to enrich the cohort participants and community information may present inconsistencies since external databases offer different input patterns and data quality. It should be emphasised that participants enrolled in the cohort will be mostly vaccinated, as enrolment started after the vaccination campaign.</p>
            <p>The engagement process is challenging in a vulnerable population due to difficulties in maintaining contact with participants, as they frequently change their mobile phone numbers and addresses. This is combined with low adherence to other COVID-19 vaccine doses and the potential refusal to participate in the subsequent waves of data collection.</p>
        </sec>
    </body>
    <back>
        <sec sec-type="data-availability">
            <title>Data availability</title>
            <sec>
                <title>Underlying data</title>
                <p>No underlying data are associated with this article.</p>
            </sec>
            <sec>
                <title>Extended data</title>
                <p>Open Science Framework: Cohort profile: Mar&#x00e9; Cohort, COVID-19 pandemic in a vulnerable community in Brazil, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.17605/OSF.IO/QX5HK">https://doi.org/10.17605/OSF.IO/QX5HK</ext-link>
                    <sup>
                        <xref ref-type="bibr" rid="ref-27">27</xref>
                    </sup>.</p>
                <p>This project contains the following extended data:</p>
                <list list-type="bullet">
                    <list-item>
                        <p>Interview questions:</p>
                        <list list-type="bullet">
                            <list-item>
                                <p>W1_adults_questionnaire_EN.pdf (Questionnaire to adult residents used in the first wave - English);</p>
                            </list-item>
                            <list-item>
                                <p>W1_minors_questionnaire_EN.pdf (Questionnaire to residents aged under 18 years used in the first wave - English);</p>
                            </list-item>
                            <list-item>
                                <p>W2_adults_questionnaire_EN.pdf (Questionnaire to adult residents used in the second wave - English);</p>
                            </list-item>
                            <list-item>
                                <p>W2_minors_questionnaire_EN.pdf (Questionnaire to residents aged under 18 years used in the second wave - English)</p>
                            </list-item>
                        </list>
                    </list-item>
                    <list-item>
                        <p>Data dictionaries:</p>
                        <list list-type="bullet">
                            <list-item>
                                <p>Wave1_dictionary_data.xlsx (Data dictionary from the first wave);</p>
                            </list-item>
                            <list-item>
                                <p>Wave2_dictionary_data.xlsx (Data dictionary from the second wave)</p>
                            </list-item>
                        </list>
                    </list-item>
                    <list-item>
                        <p>Informed Consent forms:</p>
                        <list list-type="bullet">
                            <list-item>
                                <p>Adult_Consent_Form_PTBR.pdf (Informed consent form for adult residents - Portuguese);</p>
                            </list-item>
                            <list-item>
                                <p>Legal_Responsible_Consent_Form_PTBR.pdf (Legal responsibility consent form for adults - Portuguese);</p>
                            </list-item>
                            <list-item>
                                <p>Minor_Assent_Form_7_11_years_PTBR (Informed agreement form for residents aged 7 to 11 years - Portuguese);</p>
                            </list-item>
                            <list-item>
                                <p>Minor_Assent_Form_12_17_years_PTBR.pdf (Informed agreement form for residents aged 12 to 17 years - Portuguese)</p>
                            </list-item>
                        </list>
                    </list-item>
                    <list-item>
                        <p>Newsletter on vaccine studies carried out in the Mar&#x00e9;:</p>
                        <list list-type="bullet">
                            <list-item>
                                <p>Newsletter_Mare_Covid_studies_EN.pdf (Newsletter &#x2013; COVID-19 cohort studies in Mar&#x00e9; - English)</p>
                            </list-item>
                        </list>
                    </list-item>
                </list>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>We acknowledge support from the National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES) - Finance Code 001, Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ), and the Pontifical Catholic University of Rio de Janeiro.</p>
            <p>Otavio T Ranzani acknowledges indirect support from the Instituto de Salud Carlos III (CD19/00110) by a Sara Borrell grant, from the Spanish Ministry of Science and Innovation and State Research Agency through the &#x201c;Centro de Excelencia Severo Ochoa 2019&#x2212;2023&#x201d; Program (CEX2018-000806-S), and the Generalitat de Catalunya through the CERCA Program received a research grant from the Health Effects Institute for research unrelated to this manuscript.</p>
            <p>We would like to thank the 
                <italic toggle="yes">Unidade de Apoio ao Diagn&#x00f3;stico da Covid-19</italic> (UNADIG-FIOCRUZ) for their support in the test diagnosis.</p>
            <p>The authors also would like to thank Mar&#x00e9; residents and all the professionals who engaged in the project. Without them, this work would not have been possible. Thank you for all the hard work!</p>
        </ack>
        <ref-list>
            <ref id="ref-1">
                <label>1</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>de Groot</surname>
                            <given-names>N</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Bonsel</surname>
                            <given-names>GJ</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Birnie</surname>
                            <given-names>E</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Towards a universal concept of vulnerability: Broadening the evidence from the elderly to perinatal health using a Delphi approach.</article-title>
                    <source>

                        <italic toggle="yes">PLoS One.</italic>
</source>
                    <year>2019</year>;<volume>14</volume>(<issue>2</issue>):<fpage>e0212633</fpage>.
                    <pub-id pub-id-type="pmid">30785926</pub-id>
                    <pub-id pub-id-type="doi">10.1371/journal.pone.0212633</pub-id>
                    <pub-id pub-id-type="pmcid">6382270</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-2">
                <label>2</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Brotherhood</surname>
                            <given-names>L</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Cavalcanti</surname>
                            <given-names>T</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Da Mata</surname>
                            <given-names>D</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Slums and pandemics.</article-title>
                    <source>

                        <italic toggle="yes">J Dev Econ.</italic>
</source>
                    <year>2022</year>;<volume>157</volume>:<fpage>102882</fpage>.
                    <pub-id pub-id-type="pmid">35463050</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.jdeveco.2022.102882</pub-id>
                    <pub-id pub-id-type="pmcid">9017060</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-3">
                <label>3</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>de Souza</surname>
                            <given-names>CDF</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Machado</surname>
                            <given-names>MF</given-names>
                        </name>

                        <name name-style="western">
                            <surname>do Carmo</surname>
                            <given-names>RF</given-names>
                        </name>
</person-group>:
                    <article-title>Human development, social vulnerability and COVID-19 in Brazil: a study of the social determinants of health.</article-title>
                    <source>

                        <italic toggle="yes">Infect Dis Poverty.</italic>
</source>
                    <year>2020</year>;<volume>9</volume>(<issue>1</issue>):<fpage>124</fpage>.
                    <pub-id pub-id-type="pmid">32867851</pub-id>
                    <pub-id pub-id-type="doi">10.1186/s40249-020-00743-x</pub-id>
                    <pub-id pub-id-type="pmcid">7456757</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-4">
                <label>4</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Raju</surname>
                            <given-names>E</given-names>
                        </name>

                        <name name-style="western">
                            <surname> Ayeb-Karlsson</surname>
                            <given-names>S</given-names>
                        </name>
</person-group>:
                    <article-title>COVID-19: How do you self-isolate in a refugee camp?</article-title>
                    <source>

                        <italic toggle="yes">Int J Public Health.</italic>
</source>
                    <year>2020</year>;<volume>65</volume>(<issue>5</issue>):<fpage>515</fpage>&#x2013;<lpage>517</lpage>.
                    <pub-id pub-id-type="pmid">32385541</pub-id>
                    <pub-id pub-id-type="doi">10.1007/s00038-020-01381-8</pub-id>
                    <pub-id pub-id-type="pmcid">7206218</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-5">
                <label>5</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Metcalf</surname>
                            <given-names>CJE</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Farrar</surname>
                            <given-names>J</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Cutts</surname>
                            <given-names>FT</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Use of serological surveys to generate key insights into the changing global landscape of infectious disease.</article-title>
                    <source>

                        <italic toggle="yes">Lancet.</italic>
</source>
                    <year>2016</year>;<volume>388</volume>(<issue>10045</issue>):<fpage>728</fpage>&#x2013;<lpage>730</lpage>.
                    <pub-id pub-id-type="pmid">27059886</pub-id>
                    <pub-id pub-id-type="doi">10.1016/S0140-6736(16)30164-7</pub-id>
                    <pub-id pub-id-type="pmcid">5678936</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-6">
                <label>6</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Peeling</surname>
                            <given-names>RW</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Wedderburn</surname>
                            <given-names>CJ</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Garcia</surname>
                            <given-names>PJ</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Serology testing in the COVID-19 pandemic response.</article-title>
                    <source>

                        <italic toggle="yes">Lancet Infect Dis.</italic>
</source>
                    <year>2020</year>;<volume>20</volume>(<issue>9</issue>):<fpage>e245</fpage>&#x2013;<lpage>e249</lpage>.
                    <pub-id pub-id-type="pmid">32687805</pub-id>
                    <pub-id pub-id-type="doi">10.1016/S1473-3099(20)30517-X</pub-id>
                    <pub-id pub-id-type="pmcid">7367660</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-7">
                <label>7</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Mugunga</surname>
                            <given-names>JC</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Tyagi</surname>
                            <given-names>K</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Bernal-Serrano</surname>
                            <given-names>D</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>SARS-CoV-2 serosurveys in low-income and middle-income countries.</article-title>
                    <source>

                        <italic toggle="yes">Lancet.</italic>
</source>
                    <year>2021</year>;<volume>397</volume>(<issue>10272</issue>):<fpage>353</fpage>&#x2013;<lpage>355</lpage>.
                    <pub-id pub-id-type="pmid">33516323</pub-id>
                    <pub-id pub-id-type="doi">10.1016/S0140-6736(21)00188-4</pub-id>
                    <pub-id pub-id-type="pmcid">7906745</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-8">
                <label>8</label>
                <mixed-citation publication-type="journal">
                    <collab>Redes da Mar&#x00e9;</collab>:
                    <article-title>Campanha mar&#x00e9; diz n&#x00e3;o ao coronavirus</article-title>.<year>2020</year>.
                    <ext-link ext-link-type="uri" xlink:href="https://www.google.com/url?sa=t&amp;rct=j&amp;q=&amp;esrc=s&amp;source=web&amp;cd=&amp;cad=rja&amp;uact=8&amp;ved=2ahUKEwi9z6WaxeT8AhU1A7cAHXXkA8MQFnoECA4QAQ&amp;url=https%3A%2F%2Fwww.redesdamare.org.br%2Fmedia%2Fdownloads%2Farquivos%2FMareCoronavirus_livro-min.pdf&amp;usg=AOvVaw1mbMNBkluVLJey67voFC1G">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-9">
                <label>9</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Cerqueira</surname>
                            <given-names>E</given-names>
                        </name>
</person-group>:
                    <article-title>Conex&#x00e3;o Sa&#x00fa;de no enfrentamento da pandemia de Covid-19.</article-title>
                    <source>

                        <italic toggle="yes">Os impactos sociais da Covid-19 no Bras. Popul. vulnerabilizadas e respostas a pandemia.</italic>
</source>
                    <year>2021</year>;<fpage>209</fpage>&#x2013;<lpage>219</lpage>.
                    <pub-id pub-id-type="doi">10.7476/9786557080320.0017</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-10">
                <label>10</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Arouca</surname>
                            <given-names>LE</given-names>
                        </name>

                        <name name-style="western">
                            <surname> Bozza</surname>
                            <given-names>FA</given-names>
                        </name>
</person-group>:
                    <article-title>Covid-19: desafios para a organiza&#x00e7;&#x00e3;o e repercuss&#x00f5;es nos sistemas e servi&#x00e7;os de sa&#x00fa;de.</article-title>(S&#x00e9;rie Informa&#x00e7;&#x00e3;o para a&#x00e7;&#x00e3;o na Covid-19 | Fiocruz), 2022.
                    <pub-id pub-id-type="doi">10.7476/9786557081587</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-11">
                <label>11</label>
                <mixed-citation publication-type="journal">
                    <collab>Data.Rio</collab>.
                    <article-title>Popula&#x00e7;&#x00e3;o Residente e Estimada - Brasil, Estado do Rio de Janeiro e Munic&#x00ed;pio do Rio de Janeiro e Regi&#x00f5;es Administrativas (RA) - 2000/2010/2013-2016/2020.</article-title>
                    <year>2021</year>.
                    <ext-link ext-link-type="uri" xlink:href="https://www.data.rio/documents/ba877d53302346eca990a47c99e15f74/about">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-12">
                <label>12</label>
                <mixed-citation publication-type="journal">
                    <collab>Atlas Brasil</collab>:
                    <article-title>Bases do Censo e das UDHs por Regi&#x00f5;es Metropolitanas</article-title>.<year>2010</year>.
                    <ext-link ext-link-type="uri" xlink:href="http://www.atlasbrasil.org.br/acervo/biblioteca">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-13">
                <label>13</label>
                <mixed-citation publication-type="journal">
                    <collab>Redes da Mar&#x00e9;</collab>:
                    <article-title>Censo populacional da Mar&#x00e9;</article-title>.<year>2019</year>.
                    <ext-link ext-link-type="uri" xlink:href="https://www.google.com/url?sa=t&amp;rct=j&amp;q=&amp;esrc=s&amp;source=web&amp;cd=&amp;cad=rja&amp;uact=8&amp;ved=2ahUKEwis9sPZx-T8AhXfgWMGHWoQAecQFnoECAkQAQ&amp;url=https%3A%2F%2Fapublica.org%2Fwp-content%2Fuploads%2F2020%2F07%2Fcensomare-web-04mai.pdf&amp;usg=AOvVaw3SxlxjirqQdf0x4wvUKKPm">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-14">
                <label>14</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Dantas</surname>
                            <given-names>LF</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Peres</surname>
                            <given-names>LT</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Bastos</surname>
                            <given-names>LSL</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning.</article-title>
                    <source>

                        <italic toggle="yes">PLoS One.</italic>
</source>
                    <year>2021</year>;<volume>16</volume>(<issue>3</issue>):<fpage>e0248920</fpage>.
                    <pub-id pub-id-type="pmid">33765050</pub-id>
                    <pub-id pub-id-type="doi">10.1371/journal.pone.0248920</pub-id>
                    <pub-id pub-id-type="pmcid">7993758</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-15">
                <label>15</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Pourhoseingholi</surname>
                            <given-names>MA</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Vahedi</surname>
                            <given-names>M</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Rahimzadeh</surname>
                            <given-names>M</given-names>
                        </name>
</person-group>:
                    <article-title>Sample size calculation in medical studies.</article-title>
                    <source>

                        <italic toggle="yes">Gastroenterol Hepatol Bed Bench.</italic>
</source>
                    <year>2013</year>;<volume>6</volume>(<issue>1</issue>):<fpage>14</fpage>&#x2013;<lpage>7</lpage>.
                    <pub-id pub-id-type="pmid">24834239</pub-id>
                    <pub-id pub-id-type="pmcid">4017493</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-16">
                <label>16</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Ranzani</surname>
                            <given-names>OT</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Silva</surname>
                            <given-names>AAB</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Peres</surname>
                            <given-names>IT</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Vaccine effectiveness of ChAdOx1 nCoV-19 against COVID-19 in a socially vulnerable community in Rio de Janeiro, Brazil: a test-negative design study.</article-title>
                    <source>

                        <italic toggle="yes">Clin Microbiol Infect.</italic>
</source>
                    <year>2022</year>;<volume>28</volume>(<issue>5</issue>):<fpage>736.e1</fpage>&#x2013;<lpage>736.e4</lpage>.
                    <pub-id pub-id-type="pmid">35150884</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.cmi.2022.01.032</pub-id>
                    <pub-id pub-id-type="pmcid">8828302</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-17">
                <label>17</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Harris</surname>
                            <given-names>PA</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Taylor</surname>
                            <given-names>R</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Thielke</surname>
                            <given-names>R</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Research electronic data capture (REDCap)--A metadata-driven methodology and workflow process for providing translational research informatics support.</article-title>
                    <source>

                        <italic toggle="yes">J Biomed Inform.</italic>
</source>
                    <year>2009</year>;<volume>42</volume>(<issue>2</issue>):<fpage>377</fpage>&#x2013;<lpage>381</lpage>.
                    <pub-id pub-id-type="pmid">18929686</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.jbi.2008.08.010</pub-id>
                    <pub-id pub-id-type="pmcid">2700030</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-18">
                <label>18</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>L&#x00f6;we</surname>
                            <given-names>B</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Wahl</surname>
                            <given-names>I</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Rose</surname>
                            <given-names>M</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>A 4-item measure of depression and anxiety: Validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population.</article-title>
                    <source>

                        <italic toggle="yes">J Affect Disord.</italic>
</source>
                    <year>2010</year>;<volume>122</volume>(<issue>1&#x2013;2</issue>):<fpage>86</fpage>&#x2013;<lpage>95</lpage>.
                    <pub-id pub-id-type="pmid">19616305</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.jad.2009.06.019</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-19">
                <label>19</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Helliwell</surname>
                            <given-names>J</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Layard</surname>
                            <given-names>R</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Sachs</surname>
                            <given-names>J</given-names>
                        </name>
</person-group>:
                    <article-title>World Happiness Report 2017.</article-title>WellBeing International,<year>2017</year>.
                    <ext-link ext-link-type="uri" xlink:href="https://www.wellbeingintlstudiesrepository.org/hw_happiness/6/">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-20">
                <label>20</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Scheier</surname>
                            <given-names>MF</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Carver</surname>
                            <given-names>CS</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Bridges</surname>
                            <given-names>MW</given-names>
                        </name>
</person-group>:
                    <article-title>Distinguishing Optimism From Neuroticism (and Trait Anxiety, Self-Mastery, and Self-Esteem): A Reevaluation of the Life Orientation Test.</article-title>
                    <source>

                        <italic toggle="yes"> J Pers Soc Psychol.</italic>
</source>
                    <year>1994</year>;<volume>67</volume>(<issue>6</issue>):<fpage>1063</fpage>&#x2013;<lpage>1078</lpage>.
                    <pub-id pub-id-type="pmid">7815302</pub-id>
                    <pub-id pub-id-type="doi"> 10.1037//0022-3514.67.6.1063</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-21">
                <label>21</label>
                <mixed-citation publication-type="journal">
                    <article-title>Lei Geral de Prote&#x00e7;&#x00e3;o de Dados Pessoais (LGPD).</article-title>
                    <ext-link ext-link-type="uri" xlink:href="https://www.planalto.gov.br/ccivil_03/_ato2015-2018/2018/lei/l13709.htm">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-22">
                <label>22</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Wire</surname>
                            <given-names>B</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Authorization</surname>
                            <given-names>EU</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Dbs</surname>
                            <given-names>T</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>PerkinElmer Releases New Dried Blood Spot Based COVID-19 Serology Test</article-title>.<year>2020</year>.
                    <ext-link ext-link-type="uri" xlink:href="https://www.businesswire.com/news/home/20200721005223/en/PerkinElmer-Releases-New-Dried-Blood-Spot-Based-COVID-19-Serology-Test">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-23">
                <label>23</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Amendola</surname>
                            <given-names>A</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Bianchi</surname>
                            <given-names>S</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Gori</surname>
                            <given-names>M</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Dried Blood Spot as an Alternative to Plasma/Serum for SARS-CoV-2 IgG Detection, an Opportunity to Be Sized to Facilitate COVID-19 Surveillance among Schoolchildren.</article-title>
                    <source>

                        <italic toggle="yes"> Pediatr Infect Dis J.</italic>
</source>
                    <year>2021</year>;<volume>40</volume>(<issue>1</issue>):<fpage>e46</fpage>&#x2013;<lpage>e47</lpage>.
                    <pub-id pub-id-type="pmid">33181785</pub-id>
                    <pub-id pub-id-type="doi">10.1097/INF.0000000000002955</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-24">
                <label>24</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Bastos</surname>
                            <given-names>LSL</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Aguilar</surname>
                            <given-names>S</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Rache</surname>
                            <given-names>B</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Primary healthcare protects vulnerable populations from inequity in COVID-19 vaccination: An ecological analysis of nationwide data from Brazil.</article-title>
                    <source>

                        <italic toggle="yes"> Lancet Reg Health Am.</italic>
</source>
                    <year>2022</year>;<volume>14</volume>:<fpage>100335</fpage>.
                    <pub-id pub-id-type="pmid">35991675</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.lana.2022.100335</pub-id>
                    <pub-id pub-id-type="pmcid">9381845</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-25">
                <label>25</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Sterne</surname>
                            <given-names>JAC</given-names>
                        </name>

                        <name name-style="western">
                            <surname>White</surname>
                            <given-names>IR</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Carlin</surname>
                            <given-names>JB</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.</article-title>
                    <source>

                        <italic toggle="yes">BMJ.</italic>
</source>
                    <year>2009</year>;<volume>338</volume>:<fpage>b2393</fpage>.
                    <pub-id pub-id-type="pmid">19564179</pub-id>
                    <pub-id pub-id-type="doi">10.1136/bmj.b2393</pub-id>
                    <pub-id pub-id-type="pmcid">2714692</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref-26">
                <label>26</label>
                <mixed-citation publication-type="data">
                    <collab>R Core Team</collab>:
                    <article-title>R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria</article-title>.<year>2022</year>.
                    <ext-link ext-link-type="uri" xlink:href="https://www.r-project.org/">Reference Source</ext-link>
                </mixed-citation>
            </ref>
            <ref id="ref-27">
                <label>27</label>
                <mixed-citation publication-type="data">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Batista-da-Silva</surname>
                            <given-names>A</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Ranzani</surname>
                            <given-names>OT</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Bozza</surname>
                            <given-names>HR</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <data-title>Mare Cohort profile: COVID-19 pandemic in a vulnerable community in Brazil.</data-title>[Dataset].<year>2022</year>.
                    <ext-link ext-link-type="uri" xlink:href="http://www.doi.org/10.17605/OSF.IO/QX5HK">http://www.doi.org/10.17605/OSF.IO/QX5HK</ext-link>
                </mixed-citation>
            </ref>
        </ref-list>
    </back>
    <sub-article article-type="reviewer-report" id="report33959">
        <front-stub>
            <article-id pub-id-type="doi">10.21956/gatesopenres.15333.r33959</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Umakanthan</surname>
                        <given-names>Srikanth</given-names>
                    </name>
                    <xref ref-type="aff" rid="r33959a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-6713-2265</uri>
                </contrib>
                <aff id="r33959a1">
                    <label>1</label>Paraclinical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>24</day>
                <month>7</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Umakanthan S</copyright-statement>
                <copyright-year>2023</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport33959" related-article-type="peer-reviewed-article" xlink:href="10.12688/gatesopenres.14035.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Abstract: The methodology explanation should be curtailed, and more emphasis should be given to the results. Results and conclusion should be added.</p>
            <p> </p>
            <p> Keywords: should be different from the title.</p>
            <p> </p>
            <p> Introduction and discussion can be strengthened by incorporating the following points:</p>
            <p> </p>
            <p> 1. Include a sentence on origin, transmission of COVID-19 (refer and cite: Umakanthan 
                <italic>et al.</italic>, 2019
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-33959-1">1</xref>
                </sup>).</p>
            <p> 2. In brief about Post acute(long) COVID-19 (refer and cite: Umakanthan 
                <italic>et al.</italic>, 2023
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-33959-2">2</xref>
                </sup>)</p>
            <p> 3. COVID-19 awareness among medical professionals (refer and cite: Umakanthan 
                <italic>et al.</italic>, 2022
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-33959-3">3</xref>
                </sup>).</p>
            <p> 4. The role of social environmental predictors of COVID-19 in general (refer and cite: Umakanthan 
                <italic>et al.</italic>, 2022
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-33959-4">4</xref>
                </sup>).</p>
            <p> 5. The effect of vaccine hesitancy in COVID-19 and its effects in trust in science (refer and cite: Umakanthan 
                <italic>et al.</italic>, 2021
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-33959-5">5</xref>
                </sup>).</p>
            <p> 6. The calibre of predictors in COVID-19 (refer and cite: doi: Umakanthan 
                <italic>et al.</italic>, 2022
                <sup>
                    <xref ref-type="bibr" rid="rep-ref-33959-6">6</xref>
                </sup>). 
                <list list-type="bullet">
                    <list-item>
                        <p>List the inclusion and exclusion criteria.</p>
                    </list-item>
                    <list-item>
                        <p>Were the factors classified based on variables?</p>
                    </list-item>
                    <list-item>
                        <p>How efficient was the survey tool in eliminating/minimizing the bias?</p>
                    </list-item>
                    <list-item>
                        <p>Was ethical clearance obtained before data extraction?</p>
                    </list-item>
                    <list-item>
                        <p>Was the online survey tested using a pilot study before the inception to the survey population?</p>
                    </list-item>
                    <list-item>
                        <p>Indicate the strengths and limitations of your study.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the study design appropriate for the research question?</p>
            <p>Yes</p>
            <p>Is the rationale for, and objectives of, the study clearly described?</p>
            <p>Yes</p>
            <p>Are sufficient details of the methods provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Are the datasets clearly presented in a useable and accessible format?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Covid-19, Lung cancer, molecular genetics, breast cancer,</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-33959-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Origin, transmission, diagnosis and management of coronavirus disease 2019 (COVID-19).</article-title>
                        <source>
                            <italic>Postgrad Med J</italic>
                        </source>.<year>2020</year>;<volume>96</volume>(<issue>1142</issue>) :
                        <elocation-id>10.1136/postgradmedj-2020-138234</elocation-id>
                        <fpage>753</fpage>-<lpage>758</lpage>
                        <pub-id pub-id-type="pmid">32563999</pub-id>
                        <pub-id pub-id-type="doi">10.1136/postgradmedj-2020-138234</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-33959-2">
                    <label>2</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Post-acute (long) COVID-19 quality of life: validation of the German version of (PAC19QoL) instrument.</article-title>
                        <source>
                            <italic>Front Public Health</italic>
                        </source>.<year>2023</year>;<volume>11</volume>:
                        <elocation-id>10.3389/fpubh.2023.1163360</elocation-id>
                        <fpage>1163360</fpage>
                        <pub-id pub-id-type="pmid">37457286</pub-id>
                        <pub-id pub-id-type="doi">10.3389/fpubh.2023.1163360</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-33959-3">
                    <label>3</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>COVID-19 Awareness among Undergraduate Medical Students in Trinidad: A Cross-Sectional Study</article-title>.
                        <source>
                            <italic>International Medical Education</italic>
                        </source>.<year>2022</year>;<volume>1</volume>(<issue>2</issue>) :
                        <elocation-id>10.3390/ime1020006</elocation-id>
                        <fpage>22</fpage>-<lpage>32</lpage>
                        <pub-id pub-id-type="doi">10.3390/ime1020006</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-33959-4">
                    <label>4</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Social Environmental Predictors of COVID-19 Vaccine Hesitancy in India: A Population-Based Survey.</article-title>
                        <source>
                            <italic>Vaccines (Basel)</italic>
                        </source>.<year>2022</year>;<volume>10</volume>(<issue>10</issue>) :
                        <elocation-id>10.3390/vaccines10101749</elocation-id>
                        <pub-id pub-id-type="pmid">36298614</pub-id>
                        <pub-id pub-id-type="doi">10.3390/vaccines10101749</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-33959-5">
                    <label>5</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>COVID-19 Vaccine Hesitancy and Resistance in India Explored through a Population-Based Longitudinal Survey.</article-title>
                        <source>
                            <italic>Vaccines (Basel)</italic>
                        </source>.<year>2021</year>;<volume>9</volume>(<issue>10</issue>) :
                        <elocation-id>10.3390/vaccines9101064</elocation-id>
                        <pub-id pub-id-type="pmid">34696172</pub-id>
                        <pub-id pub-id-type="doi">10.3390/vaccines9101064</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-33959-6">
                    <label>6</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Predictors of COVID-19 vaccine hesitancy in Germany: a cross-sectional, population-based study.</article-title>
                        <source>
                            <italic>Postgrad Med J</italic>
                        </source>.<year>2022</year>;<volume>98</volume>(<issue>1164</issue>) :
                        <elocation-id>10.1136/postgradmedj-2021-141365</elocation-id>
                        <fpage>756</fpage>-<lpage>764</lpage>
                        <pub-id pub-id-type="pmid">37062994</pub-id>
                        <pub-id pub-id-type="doi">10.1136/postgradmedj-2021-141365</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
    </sub-article>
</article>
