Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples.

infectious diseases phylogenetics power sample size study design

Journal

American journal of epidemiology
ISSN: 1476-6256
Titre abrégé: Am J Epidemiol
Pays: United States
ID NLM: 7910653

Informations de publication

Date de publication:
10 Oct 2024
Historique:
medline: 11 10 2024
pubmed: 11 10 2024
entrez: 10 10 2024
Statut: aheadofprint

Résumé

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.

Identifiants

pubmed: 39390641
pii: 7817940
doi: 10.1093/aje/kwae378
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

Auteurs

Lucy D'Agostino McGowan (L)

Department of Statistical Sciences, Wake Forest University, Winston-Salem, NC.

Shirlee Wohl (S)

Department of Immunology and Microbiology, The Scripps Research Institute; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Justin Lessler (J)

Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC; Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Classifications MeSH