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

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

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. Asymptomat...

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Veröffentlicht in:Infection control and hospital epidemiology 2022-11, Vol.43 (11), p.1715-1718
Hauptverfasser: Rivera, Frida, Ahn, Kwang Woo, Munoz-Price, L. Silvia
Format: Artikel
Sprache:eng
Schlagworte:
Asymptomatic
Concise Communication
Coronaviruses
COVID-19
COVID-19 - diagnosis
COVID-19 - epidemiology
COVID-19 Testing
Disease transmission
Hospitals
Humans
Infections
Inpatients
Pandemics
Patients
Regression analysis
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Software
Time series
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Beschreibung
Zusammenfassung: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.
ISSN:0899-823X
1559-6834
1559-6834
DOI:10.1017/ice.2021.282