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Lyme disease, Ebola and malaria all developed in animals before making the leap to infect humans. Predicting when such a 'zoonotic' disease will spark an outbreak remains difficult, but a new study suggests that artificial intelligence could give these efforts a boost. A computer model that incorporates machine learning can pinpoint, with 90% accuracy, rodent species that are known to harbour pathogens that can spread to humans, researchers report this week in the Proceedings of the National Academy of Sciences1. The model also identified more than 150 species that are likely to be disease reservoirs but have yet to be confirmed as such.

The hollow Cola tree growing in a remote area of southeastern Guinea was once home to thousands of bats routinely hunted and killed by the neighborhood children. It was also a popular spot to play. A year ago, one child in particular lived within fifty meters of the tree: a two-year-old boy who died in December 2013 and later was identified as the first person in west Africa known to have developed Ebola.