Researchers hope to use bat migrations to determine where and when the next Ebola outbreak will happen.
In 2014, the virus swept through West Africa, killing more than 11,000 people and infecting over 28,000, according to the World Health Organization. The outbreak is thought to have originated with a young boy in Guinea who was playing near a hollow tree full of bats, known carriers of the Ebola virus.
As the outbreak grew, scientists began creating models to predict the spread of Ebola as it is passed from person to person. In a paper published earlier this year, Javier Buceta, a researcher at Lehigh University, focused on tracking the virus through bats instead.
Buceta and his team hoped be able to pinpoint the places and times of year where people are most likely to be exposed to the disease. “If you know beforehand when it is more likely that an outbreak can happen,” Buceta said, “you can use your resources in an optimized way.”
Ebola spreads through contact with infected bodily fluids: blood, saliva, or excrement. In Africa, the disease may jump to humans when bats and people are living in close proximity, increasing the chances of water or food contamination, or when humans are hunting bats for meat. If policy-makers could predict areas where infected bats are likely to be, they could encourage locals to take extra precautions and be prepared to contain a potential outbreak before it can spread.
But determining where humans and bats may overlap is more complicated than it might seem. Africa has more than 300 species of bats, each with different food sources, habitat preferences, and movement patterns. And researchers are still missing a lot of information about how Ebola travels in bat populations.
“[Scientists] have not done a lot of research on bats,” said Raina Plowright, an infectious disease ecologist and epidemiologist at Montana State University. “We don’t know much about the individual immune mechanisms of many wildlife species.”
Plowright and her team have focused on bats in Australia infected with Hensa virus, another disease that can be transferred to humans. She said there are several theories for how diseases might function within a population of bats, and each of them would require different models to predict where and when humans might be at risk for infection.
“We ask totally different questions,” Plowright said. “It’s really critical—to understand spillover [of pathogens into humans] we need to know how these viruses maintain within bats.”
The theory Buceta uses is based on the idea that Ebola spreads through bats like chicken pox. Animals are infected, recover, and then gain immunity, although it is possible this immunity could fade over time. There is some evidence that this is how Marburg virus, a better-studied relative of Ebola, functions in bats.
Buceta’s model provides a way to estimate how many bats might be infected at any time. Bats would be more likely to become infected when they were gathered together competing for resources. As food becomes scarce, due to the changing seasons, sudden droughts, or other factors, Buceta predicts increased competition followed by waves of migratory bats carrying Ebola to new areas.
David Hayman, an associate professor at Massey University in New Zealand, is working on a similar modeling project, linking previous studies on deforestation and bat reproductive rates to the species most likely to carry Ebola. He said Buceta’s model could help inform future studies, but he questions whether migratory bats are tied to the spread of Ebola.
“From the biology perspective, it doesn’t look like the bats that migrate are typically infected with Marburg and Ebola virus, from the limited data we’ve got in the field,” Hayman said. It is possible the virus was already circulating in the local bat population and other factors triggered the spillover into humans.
Buceta’s further work in this area may be illuminating. In a paper that is currently under review, his team has applied the 2013 data for seasonal weather, vegetation, and other factors that would impact resources for bats in Africa to his model.
“When we apply all that data to our model, to our Ebola model,” he said, “we were able to pinpoint the area and the time of the year when the outbreak happened in 2014.”