Neglecting movement-disease feedback biases wildlife epidemic forecasts
In wildlife populations, movement drives host contact networks and disease spread. Growing evidence from veterinary science and experimental biology shows that infection commonly modifies host movement itself, a widespread feature of host biology. Yet conventional wildlife disease models treat movement as independent of infection, a mechanistic omission that could bias epidemic forecasts and management decisions. Here, we introduce a general framework in which recent infection temporarily alters a hosts home-ranging behavior and where pathogens are shed, integrating movement and disease ecology through spatially explicit, individual-based simulations. We show that infection-modified movement (IMM) responses, including anorexia, disorientation, and hypokinesia, can enhance or suppress epidemics, and most responses reverse direction depending on environmental conditions, grouping structure, and social behavior. We further show that models without IMM alternately underestimate and overestimate epidemic size as ecological context changes. Because our model parameters map onto quantities routinely estimated from tracking and surveillance data, our framework enables movement-disease feedback to be measured and incorporated into wildlife disease models.