Using host traits to predict reservoir host species of rabies virus

Wildlife are important reservoirs for many pathogens, yet the role that different species play in pathogen maintenance frequently remains unknown. This is the case for rabies, a viral disease of mammals. While Carnivora (carnivores) and Chiroptera (bats) are the canonical mammalian orders known to be responsible for the maintenance and onward transmission of Rabies lyssavirus (RABV), the role of most species within these orders remains unknown and is continually changing as a result of contemporary host shifting. We combined a trait-based analytical approach with gradient boosting machine learning models (GBM models) to identify physiological and ecological host features associated with being a reservoir for RABV. We then used a cooperative game theory approach to determine species-specific traits associated with known RABV reservoirs. Being a carnivore reservoir for RABV was associated with phylogenetic similarity to known RABV reservoirs, along with other traits such as having larger litters and earlier sexual maturity. For bats, location in the Americas and geographic range were the most important predictors of RABV reservoir status, along with having a large litter. Our models identified 44 carnivore and 34 bat species that are currently not recognized as RABV reservoirs, but have trait profiles suggesting their capacity to be or become reservoirs. Further, our findings suggest that potential reservoir species among bats and carnivores occur both within and outside of areas with current rabies circulation. These results show the ability of a trait-based approach to detect potential reservoirs of infection and could inform rabies control programs and surveillance efforts by identifying the types of species and traits that facilitate RABV maintenance and transmission. Author summary Rabies, a fatal viral disease transmitted via the bite of an infected animal, causes over 59,000 human deaths each year. While domestic dogs are responsible for most human cases, wild animals, particularly carnivores and bats, play an essential role in rabies persistence. Several carnivore and bat species have been identified in the field and laboratory as important rabies reservoirs that can maintain different rabies variants. However, the role of many other carnivore and bat species remains unknown and additional insights are hampered by logistical and funding limitations of field and laboratory research. Using machine learning, we used information on known rabies reservoirs to forecast previously unidentified rabies reservoirs. Our models predicted 44 carnivore and 34 bat species that could already be serving as unrecognized rabies reservoirs or that have trait profiles suggesting their capacity to become reservoirs via future host shifting. In many cases, the distribution of these predicted reservoirs overlaps geographically with known reservoir ranges. Our findings can help understand rabies circulation in wildlife and is a first step to guide future epidemiological surveillance in neglected species.