title: Inferring epidemiological parameters on the basis of allele frequencies.
abstract: In this article, I develop a methodology for inferring the transmission rate and reproductive value of an epidemic on the basis of genotype data from a sample of infected hosts. The epidemic is modeled by a birth-death process describing the transmission dynamics in combination with an infinite-allele model describing the evolution of alleles. I provide a recursive formulation for the probability of the allele frequencies in a sample of hosts and a Bayesian framework for estimating transmission rates and reproductive values on the basis of observed allele frequencies. Using the Bayesian method, I reanalyze tuberculosis data from the United States. I estimate a net transmission rate of 0.19/year [0.13, 0.24] and a reproductive value of 1.02 [1.01, 1.04]. I demonstrate that the allele frequency probability under the birth-death model does not follow the well-known Ewens' sampling formula that holds under Kingman's coalescent.
authors.affiliation: Institut für Integrative Biologie, ETH Zürich, 8092 Zürich, Switzerland.
authors.forename: Tanja
authors.initials: T
authors.lastname: Stadler
mesh_terms: D000465:Algorithms; D000483:Alleles; D001499:Bayes Theorem; D001723:Birth Rate; D058872:Epidemics; D005787:Gene Frequency; D005828:Genetics, Population / Q000379:methods* / Q000706:statistics & numerical data; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D008962:Models, Theoretical; D009154:Mutation; D009169:Mycobacterium tuberculosis / Q000254:growth & development; D014376:Tuberculosis / Q000235:genetics* / Q000401:mortality / Q000635:transmission; D014481:United States / Q000453:epidemiology