Modelling plant disease spread via high-resolution human mobility networks

Abstract Human mobility plays a crucial role in the spread of human diseases but is rarely quantified in plant disease epidemics. To address this gap, we integrate a unique, high-resolution network of human movements in New Zealand with a metapopulation model to mechanistically simulate pathogen transmission. We calibrate the model on the nationwide 2010 kiwifruit vine disease (Psa-V) outbreak and show that it reproduces the observed spatio-temporal spread, confirming that the human mobility network is a strong foundation for modelling human-mediated transmission dynamics. By analysing spatial infection trends, we find that most dispersal occurs locally, as often illustrated in the plant-outbreak literature. However, sporadic long-range connections are necessary to model a nationwide outbreak. Using the model as an in silico laboratory, we demonstrate that the severity of human-mediated pathogen transmission is highly sensitive to the timing and location of initial importation. We observe a potential causal link between seasonal labour patterns and epidemic risk in high-traffic seasons. This study showcases a novel data-driven framework for modelling the spatio-temporal spread of agricultural pathogens when human-mediated dispersal is epidemiologically relevant, underscoring the importance of leveraging human mobility networks for building better biosecurity systems.