| Literature DB >> 28489304 |
Konstans Wells1, Rodrigo K Hamede2, Douglas H Kerlin1, Andrew Storfer3, Paul A Hohenlohe4, Menna E Jones2, Hamish I McCallum1.
Abstract
Emerging infectious diseases rarely affect all members of a population equally and determining how individuals' susceptibility to infection is related to other components of their fitness is critical to understanding disease impacts at a population level and for predicting evolutionary trajectories. We introduce a novel state-space model framework to investigate survival and fecundity of Tasmanian devils (Sarcophilus harrisii) affected by a transmissible cancer, devil facial tumour disease. We show that those devils that become host to tumours have otherwise greater fitness, with higher survival and fecundity rates prior to disease-induced death than non-host individuals that do not become infected, although high tumour loads lead to high mortality. Our finding that individuals with the greatest reproductive value are those most affected by the cancer demonstrates the need to quantify both survival and fecundity in context of disease progression for understanding the impact of disease on wildlife populations.Entities:
Keywords: Bayesian capture-recapture; disease burden; disease progression; disease risk; fecundity; individual fitness; pathogenesis; transmissible cancer; tumour growth
Mesh:
Year: 2017 PMID: 28489304 PMCID: PMC6759051 DOI: 10.1111/ele.12776
Source DB: PubMed Journal: Ecol Lett ISSN: 1461-023X Impact factor: 9.492