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Leveraging genomic sequencing data to evaluate disease surveillance strategies

Authors :
Benjamin Anderson
Derek Ouyang
Alexis D’Agostino
Brandon Bonin
Emily Smith
Vit Kraushaar
Sarah L. Rudman
Daniel E. Ho
Source :
iScience, Vol 26, Iss 12, Pp 108488- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: In the face of scarce public health resources, it is critical to understand which disease surveillance strategies are effective, yet such validation has historically been difficult. From May 1 to December 31, 2021, a cohort study was carried out in Santa Clara County, California, in which 10,131 high-quality genomic sequences from COVID-19 polymerase chain reaction tests were merged with disease surveillance data. We measured the informational value, the fraction of sequenced links surfaced that are biologically plausible according to genomic sequence data, of different disease surveillance strategies. Contact tracing appeared more effective than spatiotemporal methods at uncovering nonresidential spread settings, school reporting appeared more fruitful than workplace reporting, and passively retrieved links through survey information presented some promise. Given the rapidly dwindling cost of sequencing, the informational value metric may enable near real-time, readily available evaluation of strategies by public health authorities to fight viral diseases beyond COVID-19.

Subjects

Subjects :
Public health
Virology
Science

Details

Language :
English
ISSN :
25890042
Volume :
26
Issue :
12
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.044f11d88110437b9ee2d89a064d4d6c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2023.108488