<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Bouman JA</submitter><funding>ETH Zürich</funding><funding>Botnar Research Centre for Child Health</funding><pagination>e1008728</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7946301</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>17(2)</volume><pubmed_abstract>Large-scale serological testing in the population is essential to determine the true extent of the current SARS-CoV-2 pandemic. Serological tests measure antibody responses against pathogens and use predefined cutoff levels that dichotomize the quantitative test measures into sero-positives and negatives and use this as a proxy for past infection. With the imperfect assays that are currently available to test for past SARS-CoV-2 infection, the fraction of seropositive individuals in serosurveys is a biased estimator of the cumulative incidence and is usually corrected to account for the sensitivity and specificity. Here we use an inference method-referred to as mixture-model approach-for the estimation of the cumulative incidence that does not require to define cutoffs by integrating the q</pubmed_abstract><journal>PLoS computational biology</journal><pubmed_title>Estimating the cumulative incidence of SARS-CoV-2 with imperfect serological tests: Exploiting cutoff-free approaches.</pubmed_title><pmcid>PMC7946301</pmcid><funding_grant_id>2020-FS-354</funding_grant_id><pubmed_authors>Regoes RR</pubmed_authors><pubmed_authors>Bonhoeffer S</pubmed_authors><pubmed_authors>Bouman JA</pubmed_authors><pubmed_authors>Riou J</pubmed_authors></additional><is_claimable>false</is_claimable><name>Estimating the cumulative incidence of SARS-CoV-2 with imperfect serological tests: Exploiting cutoff-free approaches.</name><description>Large-scale serological testing in the population is essential to determine the true extent of the current SARS-CoV-2 pandemic. Serological tests measure antibody responses against pathogens and use predefined cutoff levels that dichotomize the quantitative test measures into sero-positives and negatives and use this as a proxy for past infection. With the imperfect assays that are currently available to test for past SARS-CoV-2 infection, the fraction of seropositive individuals in serosurveys is a biased estimator of the cumulative incidence and is usually corrected to account for the sensitivity and specificity. Here we use an inference method-referred to as mixture-model approach-for the estimation of the cumulative incidence that does not require to define cutoffs by integrating the q</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Feb</publication><modification>2025-04-06T09:48:47.402Z</modification><creation>2025-04-06T09:48:47.402Z</creation></dates><accession>S-EPMC7946301</accession><cross_references><pubmed>33635863</pubmed><doi>10.1371/journal.pcbi.1008728</doi></cross_references></HashMap>