Genotype and sex-based host variation in behavior and susceptibility drives population disease dynamics

Lauren A White, Jonathon Siva-Jothy, Meggan E. Craft, Pedro Ferreira Do Vale

Research output: Contribution to journalArticlepeer-review

Abstract

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation.
Original languageEnglish
Article number20201653
JournalProceedings of the Royal Society B-Biological Sciences
Volume287
Issue number1938
Early online date11 Nov 2020
DOIs
Publication statusPublished - 11 Nov 2020

Keywords

  • drosophila melanogaster
  • disease transmission
  • social aggregation
  • virus shedding
  • contact networks
  • disease modelling
  • transmission heterogeneity

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