Catching dogs with turtles: Using agent based modeling to optimize street dog control
Street dogs in the developing world cause serious issues like predating on wildlife, attacking people, and spreading rabies. Indian cities often have enormous free roaming dog populations that receive minimal assistance or management from humans. For local cultural reasons, animal birth control is preferred over lethal removal as an intervention technique and many cities have started programs to sterilize and vaccinate dogs. Because of minimal funding and scientific expertise, many of these programs do not prioritize the production of rigorously collected data to compare with other programs. This lack of data limits the claims that dog population managers can make as to the efficacy of their programs when seeking funding or other support from potential donors. We sought to create agent based-model of the street dog population of Jaipur, India and compare different collection techniques, specifically, a spatially random method and two methods that use surveys of the absolute number and percentage of intact dogs to focus collection effort in an administrative zone. This spatially random method simulates the normal techniques of most ABC programs. The model also accurately simulates the seasonal breeding of street dogs in Jaipur, while accounting for heterogeneous qualities in habitat across the city.
Our results show that using either surveys of the absolute number or percentage of intact dogs in zones to inform collection methods significantly increased the improved sterilization/vaccination percentages by 12% compared to the spatially random method, but does not increase the costs associated with surgical procedures. The dog population size significantly decreased by 6.7% using survey informed collection techniques, demonstrating the potential benefits for dog population managers. Since both of the dog collection methods that are informed by surveys produce similar results, this emphasizes the importance of science-based methods in dog control.