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Challenges in hospital-acquired coronavirus disease 2019 (COVID-19) surveillance and attribution of infection source

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

Published online by Cambridge University Press:  02 August 2021

Sarah S. Lewis ,
Ibukunoluwa C. Kalu ,
Jessica Seidelman ,
Deverick J. Anderson ,
Rebekah W. Moehring ,
Becky A. Smith  and
for the Centers for Disease Control and Prevention Epicenters Program
Sarah S. Lewis*
Affiliation:
Division of Infectious Diseases, Department of Medicine, Durham, North Carolina Duke Center for Antimicrobial Stewardship and Infection Prevention, Duke University, Durham, North Carolina
Ibukunoluwa C. Kalu
Affiliation:
Duke Center for Antimicrobial Stewardship and Infection Prevention, Duke University, Durham, North Carolina Division of Infectious Diseases, Department of Pediatrics, Duke University, Durham, North Carolina
Jessica Seidelman
Affiliation:
Division of Infectious Diseases, Department of Medicine, Durham, North Carolina Duke Center for Antimicrobial Stewardship and Infection Prevention, Duke University, Durham, North Carolina
Deverick J. Anderson
Affiliation:
Division of Infectious Diseases, Department of Medicine, Durham, North Carolina Duke Center for Antimicrobial Stewardship and Infection Prevention, Duke University, Durham, North Carolina
Rebekah W. Moehring
Affiliation:
Division of Infectious Diseases, Department of Medicine, Durham, North Carolina Duke Center for Antimicrobial Stewardship and Infection Prevention, Duke University, Durham, North Carolina
Becky A. Smith
Affiliation:
Division of Infectious Diseases, Department of Medicine, Durham, North Carolina Duke Center for Antimicrobial Stewardship and Infection Prevention, Duke University, Durham, North Carolina
*
Author for correspondence: Sarah S. Lewis, E-mail: sarah.stamps@duke.edu
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Abstract

We performed surveillance for hospital-acquired COVID-19 (HA-COVID-19) and compared time-based, electronic definitions to real-time adjudication of the most likely source of acquisition. Without real-time adjudication, nearly 50% of HA-COVID-19 cases identified using electronic definitions were misclassified. Both electronic and traditional contact tracing methods likely underestimated the incidence of HA-COVID-19.

Type
Concise Communication
Information
Infection Control & Hospital Epidemiology , Volume 43 , Issue 12 , December 2022 , pp. 1914 - 1917
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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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