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Multi-strain disease dynamics on a metapopulation network
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  • Matthew Michalska-Smith,
  • Kimberly VanderWaal,
  • Montserrat Torremorell,
  • Cesar Corzo,
  • Meggan E Craft
Matthew Michalska-Smith
Department of Plant Pathology, University of Minnesota, St. Paul MN, USA, Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN USA
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Kimberly VanderWaal
Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN USA
Montserrat Torremorell
Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN USA
Cesar Corzo
Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN USA
Meggan E Craft
Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN USA
Author Profile

Abstract

Many of the most impactful diseases that affect humans, livestock, and  wildlife have clusters in their population-genetic variability that we classify as strains. Importantly, host immunity to one of these strains  is neither independent from nor equivalent to immunity to related strains. This partial cross-protective immunity affects disease dynamics  across the population as a whole and can dramatically influence  intervention strategies. While the study of multi-strain diseases goes  back decades, this work has not yet been generalized to a loosely  connected collection of subpopulations, i.e. a metapopulation. Starting  from the strain theory of host-pathogen systems proposed by \citet{Gupta_1998}, we simulate multi-strain disease dynamics on a network of  interconnected populations, characterizing the effects of  parameterization and network structures on these dynamics. We find that  dynamics propagate through the metapopulation network, even if  parameters vary between populations. Moreover, in chains of  connected populations experiencing cyclical dynamics, the movement of  (partially) immune individuals dampens the dynamics of populations  further along the chain. This work serves as an important first step in  extending prior results on multi-strain diseases to a generalized  population structure. This extension is particularly apt in the case of  livestock production, where a system of mostly isolated populations  (farms) is connected through the forced movement of individuals.