Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States

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Science Translational Medicine  29 Jul 2020:
Vol. 12, Issue 554, eabc1126
DOI: 10.1126/scitranslmed.abc1126

Inferring infections

The prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in many countries is likely underestimated because of limited or inaccurate testing and undetected asymptomatic cases. Silverman et al. used data collected through an existing infrastructure for reporting influenza-like illness to estimate the actual prevalence of SARS-CoV-2 infections in US states. They used a statistical model to estimate the proportion of observed influenza-like illness during the early pandemic that was in excess of the seasonal variation seen in prior years, then adjusted this estimate to take into account subclinical infections. Their model estimated that more than 80% of individuals with SARS-CoV-2 infections in the US went undetected in March 2020.

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