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Multi-strain disease dynamics on metapopulation networks
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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

Corresponding Author:[email protected]

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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
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Abstract

A much-updated version of this work is now available published open-access at Scientific Reportshttps://www.nature.com/articles/s41598-022-12774-5
Many pathogens have clusters of variation in their genotypes that we refer to as strain structure. Importantly, when considering related pathogen strains, host immunity to one strain is often neither independent from nor equivalent to immunity to other strains. This partial cross-reactive immunity can thus allow repeated infection with (different strains of) the same pathogen and shapes disease dynamics across a population, in turn influencing the effectiveness of intervention strategies. To better understand the dynamics governing multi-strain pathogens in complex landscapes, we combine two frameworks well-studied in their own right: multi-strain disease dynamics and metapopulation network structure. We simulate the dynamics of a multi-strain disease on a network of populations connected by migration and characterize the joint effects of disease model parametrization and network structure on these dynamics. We find that the movement of (partially) immune individuals tends to have a larger impact than the movement of infectious individuals, dampening infection dynamics in populations further along a chain. When disease parameters differ between populations, we find that dynamics can propagate from one population to another, alternatively stabilizing or destabilizing destinations populations based on the dynamics of origin populations. In addition to providing novel insights into the role of host movement on disease dynamics, this work provides a framework for future predictive modelling of multi-strain diseases across generalized population structures.