The impacts of disease on host vital rates can be demonstrated using longitudinal studies, but these studies can be expensive and logistically challenging. We examined the utility of hidden variable models to infer the individual effects of infectious disease from population-level measurements of survival when longitudinal studies are not possible. Our approach seeks to explain temporal deviations in population-level survival after introducing a disease causative agent when disease prevalence cannot be directly measured by coupling survival and epidemiological models. We tested this approach using an experimental host system (Drosophila melanogaster) with multiple distinct pathogens to validate the ability of the hidden variable model to infer per-capita disease rates. We then applied the approach to a disease outbreak in harbor seals (Phoca vituline) that had data on observed strandings but no epidemiological data. We found that our hidden variable modeling approach could successfully detect the per-capita effects of disease from monitored survival rates in both the experimental and wild populations. Our approach may prove useful for detecting epidemics from public health data in regions where standard surveillance techniques are not available and in the study of epidemics in wildlife populations, where longitudinal studies can be especially difficult to implement.

JAGS (https://sourceforge.net/projects/mcmc-jags/files/JAGS/4.x/) and R (https://cran.r-project.org/) need to be installed to reproduce these analyses.Funding provided by: National Institute of General Medical SciencesCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000057Award Number: P20GM104420Funding provided by: National Institute of General Medical SciencesCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000057Award Number: P30GM103324Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: DBI-0939454Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100008982Award Number: DMS-1029485

Fly survival data was collected from an experimental design that monitored daily survival in populations of flies that were challenged with the Drosophila C virus (DCV) and Drosophila X virus (DXV). Seal stranding data was digitized from an existing report by Brasseur, "Stranding and Rehabilitation in Numbers: Population development and stranding data on the Dutch coasts 1990-2016". Surveys covered the coastline of the Dutch Wadden Sea and nearby areas.