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Universal PCR and antibody testing demonstrate little to no transmission of SARS-CoV-2 in a rural community (preprint)
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.08.15.20175786
ABSTRACT
BackgroundThe absence of systematic surveillance for SARS-CoV-2 has curtailed accurate appraisal of transmission intensity. Our objective was to perform case detection of an entire rural community to quantify SARS-CoV-2 transmission using PCR and antibody testing. MethodsWe conducted a cross-sectional survey of the prevalence and cumulative incidence of SARSCoV-2 infection in the rural town of Bolinas, California (population 1,620), four weeks following shelter-in-place orders. Residents and county essential workers were tested between April 20th - 24th, 2020. Prevalence by PCR and seroprevalence combining data from two forms of antibody testing were performed in parallel (Abbott ARCHITECT IgG to nucleocapsid protein and in-house IgG ELISA to the receptor binding domain). ResultsOf 1,891 participants, 1,312 were confirmed Bolinas residents (>80% community ascertainment). Zero participants were PCR positive. Assuming 80% sensitivity, it would have been unlikely to observe these results (p< 0.05) if there were > 3 active infections in the community. Based on antibody results, estimated prevalence of prior infection was 0.16% (95% CrI 0.02%, 0.46%). Seroprevalence estimates using only one of the two tests would have been higher, with greater uncertainty. The positive predictive value (PPV) of a positive result on both tests was 99.11% (95% CrI 95.75%, 99.94%), compared to PPV 44.19%-63.32% (95% CrI range 3.25%-98.64%) if only one test was utilized. ConclusionsFour weeks following shelter-in-place, active and prior SARS-CoV-2 infection in a rural Northern California community was extremely rare. In this low prevalence setting, use of two antibody tests increased the PPV and precision of seroprevalence estimates.
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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint