A model-based approach for investigation and mitigation of disease spillover risks to wildlife: Dogs, foxes and canine distemper in central India

Multi-host pathogens can pose a serious conservation threat when free-ranging domestic animal populations occur alongside susceptible populations of wild species. An example is canine distemper virus (CDV), which can occur at high prevalence in domestic dog (Canis familiaris) populations from which it may be transmitted (spillover) into wild carnivore populations. Effective management of such disease threats is hindered by our limited understanding of the the dynamics of interspecific CDV transmission in natural settings. We used a modeling approach to better understand CDV spillover threats to wild Indian foxes (Vulpes bengalensis) occurring in a protected grassland habitat in central India. An agent-based stochastic simulation model was built, and parameterized with data from ecological and epidemiological studies. Based on the sensitivity analyses of the model, the CDV incidence rate in dogs was most influenced by the proportion of roamer dogs in the dog population. The CDV incidence rate in dogs was also sensitive to the CDV introduction frequency in the dog population. The proportion of roamer dogs in the dog population also influenced the number of CDV spillover events. The basic reproductive number (R0) for CDV in the model fox population was 0.85, indicating that CDV could not be independently sustained in the fox population. We used the model to explore potential management strategies to mitigate the risk of CDV spillover. Vaccination of local dog populations was an ineffective disease control strategy, while fox vaccination was highly effective. Interventions potentially resulting in lower contact rates between dogs and foxes, like reduction in village dog density and restricting dog movements in fox habitat, implemented in a sustained and integrated manner would be most effective in mitigating disease threats to foxes. Such modeling approaches can be used to better understand disease threats for other species of management concern, and to contrast potential management interventions.