Undiscovered Bat Hosts of Filoviruses

Abstract

Ebola and other filoviruses pose significant public health and conservation threats by causing high mortality in primates, including humans. Preventing future outbreaks of ebolavirus depends on identifying wildlife reservoirs, but extraordinarily high biodiversity of potential hosts in temporally dynamic environments of equatorial Africa contributes to sporadic, unpredictable outbreaks that have hampered efforts to identify wild reservoirs for nearly 40 years. Using a machine learning algorithm, generalized boosted regression, we characterize potential filovirus-positive bat species with estimated 87% accuracy. Our model produces two specific outputs with immediate utility for guiding filovirus surveillance in the wild. First, we report a profile of intrinsic traits that discriminates hosts from non-hosts, providing a biological caricature of a filovirus-positive bat species. This profile emphasizes traits describing adult and neonate body sizes and rates of reproductive fitness, as well as species' geographic range overlap with regions of high mammalian diversity. Second, we identify several bat species ranked most likely to be filovirus-positive on the basis of intrinsic trait similarity with known filovirus-positive bats. New bat species predicted to be positive for filoviruses are widely distributed outside of equatorial Africa, with a majority of species overlapping in Southeast Asia. Taken together, these results spotlight several potential host species and geographical regions as high-probability targets for future filovirus surveillance.

Fig 1. The trait profile of filovirus-positive bat species.

Partial dependence plots of the top 8 predictor variables from a generalized boosted regression analysis illustrate the trait profile of bat species that are positive for filoviruses in the wild. Plots appear in order of predictive importance from left to right, top to bottom. Line graphs depict the marginal effect of a given variable for correctly predicting filovirus-positive status in bats. Blue frequency histograms show the distribution of available trait values across all 1116 bat species while the solid curve shows the trait tendencies for filovirus-positive bat species.

Fig 2. Range maps of known and predicted additional filovirus-positive bat species.

Overlapping geographic ranges of 21 bat species that have tested positive for filoviruses (top), and additional bat species predicted to carry filoviruses in the 90^th percentile probability through generalized boosted regression analysis (bottom).

Fig 3. Magnified range maps of known and predicted filovirus-positive bat species.

Magnifications of hotspots of filovirus-positive bat species in sub-Saharan Africa (left), and hotspots in Southeast Asia showing overlapping geographic ranges for predicted new filovirus carriers within the 90^th percentile probability (right).