Assessing multiple free-roaming dog control strategies in a flexible agent-based model

Abstract

Abstract Management of free-roaming dog populations is required to mitigate the threat of pathogens like rabies, minimize conflict with people, wildlife, and livestock and improve dog welfare. Historically, lethal removal has been the primary management tool, but is giving way to more humane sterilization and vaccination strategies. However, the implementation of control can vary widely between locations. This work describes an agent-based stochastic model, ‘StreetDogSim’ that can be used as a planning tool to investigate the predicted impact of different strategies with variable implementation approaches and adjustable parameters to match local conditions. Here, we explore the effects of different management strategies including lethal, vaccine-only, and vaccinate and sterilize, with additional variation in their duration, intensity, and vaccine quality on important population metrics such as overall size, demographics, vaccination coverage, time until effective population suppression, and duration of suppression. Under most model parameterizations, a strategy that targets females for sterilization with vaccination outperforms all other options with respect to population control and demographic changes.