Estimating genetic and non-genetic effects for host susceptibility, infectivity and recoverability using temporal epidemic data

Hosts differ widely in their response to infection and therefore also in their relative contribution to the spread of infection within and across populations. Three key epidemiological host traits affect infectious disease spread: susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection to others, once infected) and recoverability (propensity to recover quickly). Disease control strategies aimed at reducing disease spread may target improvement in any one of these traits. In this paper we introduce a novel software tool called SIRE (standing for "Susceptibility, Infectivity and Recoverability Estimation"), which allows, for the first time, simultaneous estimation of the genetic effect of a single nucleotide polymorphism (SNP), as well as of environmental and specific non-genetic influences on these three host traits. SIRE implements a Bayesian algorithm which makes use of temporal data (consisting of any combination of recorded individual infection times, recovery times or disease status measurements) from multiple epidemics whose dynamics can be represented by the susceptible-infectious-recovered (SIR) model. Validation of SIRE was achieved through simulation studies. Different data scenarios representing realistic recording schemes were simulated to evaluate the impact on the precision of parameter estimates. This analysis revealed that, for the majority of scenarios, SNP effects associated with recoverability can be estimated with highest precision and accuracy, followed by susceptibility and finally infectivity. In the latter case it was found that many epidemics with few individuals give substantially more statistical power to identify SNP effects than the reverse. Furthermore, precise estimates of SNP effects could be obtained even when only recovery times of individuals are known, albeit requiring around four times as many individuals to give equivalent precision. SIRE represents a new tool for analysing a wide range of experimental and field disease data with the aim of discovering and validating SNPs and other factors controlling infectious disease transmission.