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Dryad

Reactivation of latent infections with migration shapes population-level disease dynamics

Cite this dataset

Becker, Daniel; Ketterson, Ellen; Hall, Richard (2020). Reactivation of latent infections with migration shapes population-level disease dynamics [Dataset]. Dryad. https://doi.org/10.5061/dryad.z612jm68p

Abstract

Annual migration is common across animal taxa and can dramatically shape the spatial and temporal patterns of infectious disease. Although migration can decrease infection prevalence in some contexts, these energetically costly long-distance movements can also have immunosuppressive effects that may interact with transmission processes in complex ways. Here we develop a mechanistic model for the reactivation of latent infections driven by physiological changes or energetic costs associated with migration (i.e., “migratory relapse”) and its effects on disease dynamics. We determine conditions under which migratory relapse can amplify or reduce infection prevalence across pathogen and host traits (e.g., infectious periods, virulence, overwinter survival, timing of relapse) and transmission phenologies. We show that relapse at either the start or end of migration can dramatically increase prevalence across the annual cycle and may be crucial for maintaining pathogens with low transmissibility and short infectious periods in migratory populations. Conversely, relapse at the start of migration can reduce the prevalence of highly virulent pathogens by amplifying culling of infected hosts during costly migration, especially for highly transmissible pathogens and those transmitted during migration or the breeding season. Our study provides a mechanistic foundation for understanding the spatiotemporal patterns of relapsing infections in migratory hosts, with implications for zoonotic surveillance and understanding how infection patterns will respond to shifts in migratory propensity associated with environmental change. Further, our work suggests incorporating within-host processes into population-level models of pathogen transmission may be crucial for reconciling the range of migration–infection relationships observed across migratory species.