A Massey University expert has contributed to American research that suggests undiscovered potential hotspots and bat-hosts of Ebola and other filoviruses.
The paper, Undiscovered bat hosts of filoviruses, was published in PLOS Neglected Tropical Diseases and represents a collaboration between Massey, the University of Georgia, the University of California and is led by Dr Barbara Han, a disease ecologist at the Cary Institute of Ecosystem Studies.
The researchers have developed a model to identify potential carriers of filoviruses using an algorithm that analyses traits of filovirus-positive bat species in order to identify hotspots where those species co-occur around the world.
Lead author Dr Han says preventing future outbreaks of Ebola viruses in humans and other vulnerable animal populations will require identifying the natural reservoirs of filoviruses.
“Using machine learning methods developed for artificial intelligence, we were able to bring together data from ecology, biogeography and public health to identify bat species with a high probability of harbouring Ebola and other filoviruses,” she says.
(Top) Overlapping geographic ranges of the 21 bat species that have tested positive for filoviruses, (Bottom) the ranges of the additional bat species predicted to carry filoviruses through the analysis.
Mapping the hotspots
The team developed the ‘profile’ of filovirus-positive bat species by looking at life history, physiological, and ecological attributes of the 21 bat species known to harbour filoviruses. Using 57 variables, from diet and reproductive behaviour to migratory patterns and species density, an algorithm learned features that distinguish bats that have tested positive for filoviruses from other bat species with 87 per cent accuracy.
Massey University’s Dr Hayman, who co-authored the paper, says the model allowed researchers to move beyond their own biases and find patterns in the data that only a machine could identify.
“Instead of looking at a map and predicting where outbreaks will occur in relation to previous outbreaks, it looks at the map and predicts outbreaks where the identified species are found. If you look at our models, bat species predicted to be positive for filoviruses are widely distributed outside of equatorial Africa, with a majority of species overlapping in Indochina,” he says.
“The Ebola virus may have faded from the public eye, but the conditions, animals and viruses are still present around the world and there is still a great need to maintain surveillance and research.”
While the model identified several bat species known to be filovirus hosts, it also identified unknown species whose trait profiles indicate that they should be surveillance targets. When the world’s bat species were compared against this filovirus-positive bat profile, many new potential bat hosts were identified based on their traits. While many are found in sub-Saharan Africa, once mapped they were more widely distributed than the team expected, ranging across Southeast Asia and Central and South America.
The model will be used to guide researchers’ efforts on the ground investigating potential hotspots.
The paper can be accessed online here.
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