Sample size calculations for pathogen variant surveillance in the presence of biological and systematic biases.
SARS-CoV-2
infectious disease
pathogen genomics
pathogen variants
sample size calculations
variant surveillance
variants of concern
Journal
Cell reports. Medicine
ISSN: 2666-3791
Titre abrégé: Cell Rep Med
Pays: United States
ID NLM: 101766894
Informations de publication
Date de publication:
16 05 2023
16 05 2023
Historique:
received:
05
09
2022
revised:
08
02
2023
accepted:
05
04
2023
medline:
19
5
2023
pubmed:
28
4
2023
entrez:
27
4
2023
Statut:
ppublish
Résumé
Tracking the emergence and spread of pathogen variants is an important component of monitoring infectious disease outbreaks. To that end, accurately estimating the number and prevalence of pathogen variants in a population requires carefully designed surveillance programs. However, current approaches to calculating the number of pathogen samples needed for effective surveillance often do not account for the various processes that can bias which infections are detected and which samples are ultimately characterized as a specific variant. In this article, we introduce a framework that accounts for the logistical and epidemiological processes that may bias variant characterization, and we demonstrate how to use this framework (implemented in a publicly available tool) to calculate the number of sequences needed for surveillance. Our framework is designed to be easy to use while also flexible enough to be adapted to various pathogens and surveillance scenarios.
Identifiants
pubmed: 37105175
pii: S2666-3791(23)00132-5
doi: 10.1016/j.xcrm.2023.101022
pmc: PMC10213798
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
101022Informations de copyright
Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors declare no competing interests.
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