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                <text>Dominio científico: Coronavirus</text>
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              <text>Hyperlocal Postcode Based Crowdsourced Surveillance Systems in the COVID-19 Pandemic Response</text>
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              <text>Ajay Hegde, Darshan Krishnappa, Ramesh Masthi</text>
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              <text>The SARS-CoV-2 pandemic has rapidly saturated healthcare resources across the globe and has led to a restricted screening process, hindering efforts at comprehensive case detection. This has not only facilitated community spread but has also resulted in an underestimation of the true incidence of disease, a statistic which is useful for policy making aimed at controlling the current pandemic and in preparing for future outbreaks. In this perspective, we present a crowdsourced platform developed by us for the true estimation of all SARS-CoV-2 infections in the community, through active self-reporting and layering other authentic datasets. The granularity of data captured by this system could prove to be useful in assisting governments to identify SARS-CoV-2 hotspots in the community facilitating lifting of restrictions in a controlled fashion.</text>
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              <text>DOI: 10.3389/fpubh.2020.00286</text>
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              <text>Frontiers in Public Health</text>
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              <text>Frontiers Media S.A.</text>
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              <text>Public aspects of medicine</text>
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