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Estimating the efficacy of symptom-based screening for COVID-19.
Callahan, Alison; Steinberg, Ethan; Fries, Jason A; Gombar, Saurabh; Patel, Birju; Corbin, Conor K; Shah, Nigam H.
  • Callahan A; Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA.
  • Steinberg E; Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA.
  • Fries JA; Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA.
  • Gombar S; Department of Pathology, School of Medicine, Stanford University, Stanford, CA USA.
  • Patel B; Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA.
  • Corbin CK; Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA.
  • Shah NH; Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA.
NPJ Digit Med ; 3: 95, 2020.
Article in English | MEDLINE | ID: covidwho-641380
ABSTRACT
There is substantial interest in using presenting symptoms to prioritize testing for COVID-19 and establish symptom-based surveillance. However, little is currently known about the specificity of COVID-19 symptoms. To assess the feasibility of symptom-based screening for COVID-19, we used data from tests for common respiratory viruses and SARS-CoV-2 in our health system to measure the ability to correctly classify virus test results based on presenting symptoms. Based on these results, symptom-based screening may not be an effective strategy to identify individuals who should be tested for SARS-CoV-2 infection or to obtain a leading indicator of new COVID-19 cases.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: NPJ Digit Med Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: NPJ Digit Med Year: 2020 Document Type: Article