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Predicting asymptomatic severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection rates of inpatients: A time-series analysis

Part of: SARS-CoV-2/COVID-19

Published online by Cambridge University Press:  24 June 2021

Frida Rivera ,
Kwang Woo Ahn  and
L. Silvia Munoz-Price
Frida Rivera
Affiliation:
Division of Infectious Diseases, Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
Kwang Woo Ahn
Affiliation:
Department of Biostatistics, Medical College of Wisconsin, Milwaukee, Wisconsin
L. Silvia Munoz-Price*
Affiliation:
Division of Infectious Diseases, Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
*
Author for correspondence: L. Silvia Munoz-Price, E-mail: smunozprice@mcw.edu
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Abstract

Asymptomatic SARS-CoV-2 infections are often difficult to identify because widespread surveillance has not been the norm. Using time-series analyses, we examined whether COVID-19 rates at the county level could predict positivity rates among asymptomatic patients in a large health system. Asymptomatic positivity rates at the system level and county-level COVID-19 rates were not associated.

Type
Concise Communication
Information
Infection Control & Hospital Epidemiology , Volume 43 , Issue 11 , November 2022 , pp. 1715 - 1718
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Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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