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Sentinel Surveillance System Implementation and Evaluation for SARS-CoV-2 Genomic Data, Washington, USA, 2020–2021

Authors :
Hanna N. Oltean
Krisandra J. Allen
Lauren Frisbie
Stephanie M. Lunn
Laura Marcela Torres
Lillian Manahan
Ian Painter
Denny Russell
Avi Singh
JohnAric MoonDance Peterson
Kristin Grant
Cara Peter
Rebecca Cao
Katelynn Garcia
Drew Mackellar
Lisa Jones
Holly Halstead
Hannah Gray
Geoff Melly
Deborah Nickerson
Lea Starita
Chris Frazar
Alexander L. Greninger
Pavitra Roychoudhury
Patrick C. Mathias
Michael H. Kalnoski
Chao-Nan Ting
Marisa Lykken
Tana Rice
Daniel Gonzalez-Robles
David Bina
Kelly Johnson
Carmen L. Wiley
Shaun C. Magnuson
Christopher M. Parsons
Eugene D. Chapman
C. Alexander Valencia
Ryan R. Fortna
Gregory Wolgamot
James P. Hughes
Janet G. Baseman
Trevor Bedford
Scott Lindquist
Source :
Emerging Infectious Diseases, Vol 29, Iss 2, Pp 242-251 (2023)
Publication Year :
2023
Publisher :
Centers for Disease Control and Prevention, 2023.

Abstract

Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility–affiliated status, and geographic coverage; timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.

Details

Language :
English
ISSN :
10806040 and 10806059
Volume :
29
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Emerging Infectious Diseases
Publication Type :
Academic Journal
Accession number :
edsdoj.95b55d4c64f24049ac6459de163901ca
Document Type :
article
Full Text :
https://doi.org/10.3201/eid2902.221482