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What Can We Learn about SARS-CoV-2 Prevalence from Testing and Hospital Data?

Author

Listed:
  • Daniel W. Sacks

    (Indiana University)

  • Nir Menachemi

    (Indiana University and Regenstrief Institute, Inc.)

  • Peter Embí

    (Vanderbilt University Medical Center and Vanderbilt University)

  • Coady Wing

    (Indiana University)

Abstract

Measuring the prevalence of active SARS-CoV-2 infections in the general population is difficult because tests are conducted on a small and nonrandom segment of the population. However, hospitalized patients are tested at very high rates, even those admitted for non-COVID reasons. We show how to use information on testing of non-COVID hospitalized patients to obtain tight bounds on population prevalence, under conditions weaker than those usually used. We apply our approach to the population of test and hospitalization data for Indiana, and we validate our approach. Our bounds could be constructed at relatively low cost, and for other heavily tested populations.

Suggested Citation

  • Daniel W. Sacks & Nir Menachemi & Peter Embí & Coady Wing, 2024. "What Can We Learn about SARS-CoV-2 Prevalence from Testing and Hospital Data?," The Review of Economics and Statistics, MIT Press, vol. 106(3), pages 848-858, May.
    • Handle: RePEc:tpr:restat:v:106:y:2024:i:3:p:848-858
    DOI: 10.1162/rest_a_01179
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