An agent-based movement model to assess the impact of landscape fragmentation on disease transmission

Landscape changes can result in habitat fragmentation and reduced landscape connectivity, limiting the ability of animals to move across space and altering infectious disease dynamics in wildlife. In this study, we develop and implement an agent-based model to assess the impacts of animal movement behavior and landscape structure on disease dynamics. We model a susceptible/infective disease state system applicable to the transmission of feline immunodeficiency virus in bobcats in the urbanized landscape of coastal southern California. Our agent-based model incorporates animal movement behavior, pathogen prevalence, transmission probability, and habitat fragmentation to evaluate how these variables influence disease spread in urbanizing landscapes. We performed a sensitivity analysis by simulating the system under 4200 different combinations of model parameters and evaluating disease transmission outcomes. Our model reveals that host movement behavior and response to landscape features play a pivotal role in determining how habitat fragmentation influences disease dynamics. Importantly, interactions among habitat fragmentation and movement had non-linear and counter-intuitive effects on disease transmission. For example, the model predicts that an intermediate level of non-habitat permeability and directionality will result in the highest rates of between-patch disease transmission. Agent-based models serve as computational laboratories that provide a powerful approach for quantitatively and visually exploring the role of animal behavior and anthropogenic landscape change on contacts among agents and the spread of disease. Such questions are challenging to study empirically given that it is difficult or impossible to experimentally manipulate actual landscapes and the animals and pathogens that move through them. Modeling the relationship between habitat fragmentation, animal movement behavior, and disease spread will improve understanding of the spread of potentially destructive pathogens through wildlife populations, as well as domestic animals and humans