{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["10"],"submitter":["Wass LM"],"pubmed_abstract":["<h4>Background</h4>Syndromic surveillance represents a potentially inexpensive supplement to test-based COVID-19 surveillance. By strengthening surveillance of COVID-19-like illness (CLI), targeted and rapid interventions can be facilitated that prevent COVID-19 outbreaks without primary reliance on testing.<h4>Objective</h4>This study aims to assess the temporal relationship between confirmed SARS-CoV-2 infections and self-reported and health care provider-reported CLI in university and county settings, respectively.<h4>Methods</h4>We collected aggregated COVID-19 testing and symptom reporting surveillance data from Cornell University (2020-2021) and Tompkins County Health Department (2020-2022). We used negative binomial and linear regression models to correlate confirmed COVID-19 case c"],"journal":["JMIR public health and surveillance"],"pagination":["e54551"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11220726"],"repository":["biostudies-literature"],"pubmed_title":["Syndromic Surveillance Tracks COVID-19 Cases in University and County Settings: Retrospective Observational Study."],"pmcid":["PMC11220726"],"pubmed_authors":["Klepack W","Busche JM","O'Keeffe Hoare D","Osman M","Basu S","Zhang N","Clarkberg ME","Wass LM","Parrilla L","Smits GE","Cazer CL"],"additional_accession":[]},"is_claimable":false,"name":"Syndromic Surveillance Tracks COVID-19 Cases in University and County Settings: Retrospective Observational Study.","description":"<h4>Background</h4>Syndromic surveillance represents a potentially inexpensive supplement to test-based COVID-19 surveillance. By strengthening surveillance of COVID-19-like illness (CLI), targeted and rapid interventions can be facilitated that prevent COVID-19 outbreaks without primary reliance on testing.<h4>Objective</h4>This study aims to assess the temporal relationship between confirmed SARS-CoV-2 infections and self-reported and health care provider-reported CLI in university and county settings, respectively.<h4>Methods</h4>We collected aggregated COVID-19 testing and symptom reporting surveillance data from Cornell University (2020-2021) and Tompkins County Health Department (2020-2022). We used negative binomial and linear regression models to correlate confirmed COVID-19 case c","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jun","modification":"2026-06-01T21:46:50.33Z","creation":"2025-04-04T23:54:08.987Z"},"accession":"S-EPMC11220726","cross_references":{"pubmed":["38952000"],"doi":["10.2196/54551"]}}