<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>2(2)</volume><submitter>Shoer S</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>The gold standard for COVID-19 diagnosis is detection of viral RNA through PCR. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential.&lt;h4>Methods&lt;/h4>We devised a model estimating the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions that have been associated with SARS-CoV-2 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel in its first 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive.&lt;h4>Findings&lt;/h4>Our model was validated on a held-out set of individuals f</pubmed_abstract><journal>Med (New York, N.Y.)</journal><pagination>196-208.e4</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7547576</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys.</pubmed_title><pmcid>PMC7547576</pmcid><pubmed_authors>Rossman H</pubmed_authors><pubmed_authors>Balicer R</pubmed_authors><pubmed_authors>Irony A</pubmed_authors><pubmed_authors>Kolobkov D</pubmed_authors><pubmed_authors>Castel N</pubmed_authors><pubmed_authors>Segal E</pubmed_authors><pubmed_authors>Shoer S</pubmed_authors><pubmed_authors>Lavon A</pubmed_authors><pubmed_authors>Godneva A</pubmed_authors><pubmed_authors>Hoch O</pubmed_authors><pubmed_authors>Shilo S</pubmed_authors><pubmed_authors>Zer-Aviv M</pubmed_authors><pubmed_authors>Spector T</pubmed_authors><pubmed_authors>Cohen O</pubmed_authors><pubmed_authors>Zohar AE</pubmed_authors><pubmed_authors>Kalka I</pubmed_authors><pubmed_authors>Hizi D</pubmed_authors><pubmed_authors>Keshet A</pubmed_authors><pubmed_authors>Karady T</pubmed_authors><pubmed_authors>Meir T</pubmed_authors><pubmed_authors>Shalev V</pubmed_authors><pubmed_authors>Sudre C</pubmed_authors><pubmed_authors>Kariv A</pubmed_authors><pubmed_authors>Geiger B</pubmed_authors><pubmed_authors>Gavrieli A</pubmed_authors></additional><is_claimable>false</is_claimable><name>A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys.</name><description>&lt;h4>Background&lt;/h4>The gold standard for COVID-19 diagnosis is detection of viral RNA through PCR. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential.&lt;h4>Methods&lt;/h4>We devised a model estimating the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions that have been associated with SARS-CoV-2 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel in its first 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive.&lt;h4>Findings&lt;/h4>Our model was validated on a held-out set of individuals f</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Feb</publication><modification>2025-05-29T22:30:52.252Z</modification><creation>2025-05-29T22:30:52.252Z</creation></dates><accession>S-EPMC7547576</accession><cross_references><pubmed>33073258</pubmed><doi>10.1016/j.medj.2020.10.002</doi></cross_references></HashMap>