Modelling management strategies for chronic disease in wildlife: Predictions for the control of respiratory disease in bighorn sheep

Controlling persistent infectious disease in wildlife populations is an ongoing challenge for wildlife managers and conservationists worldwide, and chronic diseases in particular remain a pernicious problem. Here, we develop a dynamic pathogen transmission model capturing key features of Mycoplasma ovipneumoniae infection, a major cause of population declines in North American bighorn sheep Ovis canadensis. We explore the effects of model assumptions and parameter values on disease dynamics, including density- versus frequency-dependent transmission, the inclusion of a carrier class versus a longer infectious period, host survival rates, disease-induced mortality and recovery rates and the epidemic growth rate. Along the way, we estimate the basic reproductive ratio, R-0, for M. ovipneumoniae in bighorn sheep to fall between approximately 1.36 and 1.74. We apply the model to compare efficacies across a suite of management actions following an epidemic, including test-and-remove, depopulation-and-reintroduction, range expansion, herd augmentation and density reduction. Our results suggest that test-and-remove, depopulation-and-reintroduction and range expansion could help persistently infected bighorn sheep herds recovery following an epidemic. By contrast, augmentation could lead to worse outcomes than those expected in the absence of management. Other management actions that improve host survival or reduce disease-induced mortality are also likely to improve population size and persistence of chronically infected herds. Synthesis and applications. Dynamic transmission models like the one employed here offer a structured, logical approach for exploring hypotheses, planning field experiments and designing adaptive management. We find that management strategies that removed infected animals or isolated them within a structured metapopulation were most successful at facilitating herd recovery from a low-prevalence, chronic pathogen. Ideally, models like ours should operate iteratively with field experiments to triangulate on better approaches for managing wildlife diseases.