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      COVID-19 diagnostic multiplicity and its role in community surveillance and control

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            Abstract

            Diagnosis of persons exposed to/infected with severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) is central to controlling the global pandemic of COVID-19. Currently, several diagnostic modalities are available for COVID-19, each with its own pros and cons. Although there is a global consensus to increase the testing capacity, it is also essential to prudently utilize these tests to control the pandemic. In this paper, we have reviewed the current array of diagnostics for SARSCoV-2 highlighted the gaps in current diagnostic modalities and their role in community surveillance and control of the pandemic. The different modalities of COVID-19 diagnosis discussed are: clinical and radiological, molecular-based (laboratory-based and point-of-care), Immunoassay based (ELISA, rapid antigen and antibody detection tests) and digital diagnostics (artificial intelligence-based algorithms). The role of rapid antigen/antibody detection tests in community surveillance has also been described here. These tests can be used to identify asymptomatic persons exposed to the virus and in community-based seroprevalence surveys to assess the epidemiology of spread of the virus. However, there are few concerns about the accuracy of these tests which needs to evaluated beforehand.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            8 May 2020
            Affiliations
            [1 ] Assistant Professor, Anatomy
            [2 ] Assistant Professor, Biochemistry
            [3 ] Assistant Professor, Physiology
            [4 ] Assistant Professor, Community Medicine
            Author information
            https://orcid.org/0000-0002-6970-6699
            Article
            10.14293/S2199-1006.1.SOR-.PPA94RC.v1
            32532934
            ead0f75d-3a24-495e-8984-8aed83635165

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            : 8 May 2020

            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            General medicine,Immunology,Infectious disease & Microbiology
            Coronavirus,AI,Artificial intelligence,COVID-19,SARSCoV-2,Surveillance,RT-PCR

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