Efficient Sampling in Disease Surveillance through Subpopulations: Sampling Canaries in the Coal Mine

Fuente: arXiv
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Auteur principal: Stoepker, Ivo V.
Format: Preprint
Publié: 2024
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author Stoepker, Ivo V.
author_facet Stoepker, Ivo V.
contents We consider outbreak detection settings of endemic diseases where the population under study consists of various subpopulations available for stratified surveillance. These subpopulations can for example be based on age cohorts, but may also correspond to other subgroups of the population under study such as international travellers. Rather than sampling uniformly across the population, one may elevate the effectiveness of the detection methodology by optimally choosing a sampling subpopulation. We show (under some assumptions) the relative sampling efficiency between two subpopulations is inversely proportional to the ratio of their respective baseline disease risks. This implies one can increase sampling efficiency by sampling from the subpopulation with higher baseline disease risk. Our results require careful treatment of the power curves of exact binomial tests as a function of their sample size, which are non-monotonic due to the underlying discreteness. A case study of COVID-19 cases in the Netherlands illustrates our theoretical findings.
format Preprint
id arxiv_https___arxiv_org_abs_2405_10742
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Efficient Sampling in Disease Surveillance through Subpopulations: Sampling Canaries in the Coal Mine
Stoepker, Ivo V.
Methodology
Applications
62D05, 62F03, 62P10
We consider outbreak detection settings of endemic diseases where the population under study consists of various subpopulations available for stratified surveillance. These subpopulations can for example be based on age cohorts, but may also correspond to other subgroups of the population under study such as international travellers. Rather than sampling uniformly across the population, one may elevate the effectiveness of the detection methodology by optimally choosing a sampling subpopulation. We show (under some assumptions) the relative sampling efficiency between two subpopulations is inversely proportional to the ratio of their respective baseline disease risks. This implies one can increase sampling efficiency by sampling from the subpopulation with higher baseline disease risk. Our results require careful treatment of the power curves of exact binomial tests as a function of their sample size, which are non-monotonic due to the underlying discreteness. A case study of COVID-19 cases in the Netherlands illustrates our theoretical findings.
title Efficient Sampling in Disease Surveillance through Subpopulations: Sampling Canaries in the Coal Mine
topic Methodology
Applications
62D05, 62F03, 62P10
url https://arxiv.org/abs/2405.10742