Machine learning identifies bat species that can spread deadly Nipah

Machine learning identifies bat species that can spread deadly Nipah

Researchers have developed a model using machine learning (ML) to identify bat species likely to carry the Nipah virus, with a particular focus on India. Four new species of bats have been identified that require special attention.

“While more and more people know that bats play a role in the spread of Nipah virus in Southeast Asia, we know less about which species pose the greatest risk. Our goal was to help identify additional species that are most likely to carry Nipah to we monitor and protect public health in a targeted manner,” said Barbara Han, a staff member of the American Cary Institute of Ecosystem Studies. India is home to an estimated 113 species of bats. According to a study published in the journal PLOS Neglected Tropical Diseases, only 31 of these species were sampled for Nipah virus, and antibodies were found in 11 species indicating host potential. Nipah virus is a particularly deadly, newly emerging poultry virus that can be transmitted to humans from the body fluids of infected bats. Eating bat-contaminated fruit or drinking date palm sap has been identified as a route of infection. Domestic pigs are also intermediate hosts that can infect humans. If people are infected, they can directly transmit the virus to other people, which can cause an epidemic. There is no vaccine and the virus has a high fatality rate.For the study, a form of artificial intelligence, machine learning, was used to determine the species of bats that potentially carry the Nipah virus, The Quint magazine published in New Delhi reported.”By examining the characteristics of the bat species that carry the Nipah virus, our model was able to make predictions about additional bat species in India that could transmit the virus to humans. These bats are currently off the public health radar and deserve further investigation,” Han said. For the study, the research group systematized data published worldwide on bat species known to carry Nipah and other henipaviruses. Ultimately, 48 characteristics of 523 bat species were recorded in the register, including feeding methods, information on feeding, migratory behavior, geographic range and reproduction. During the test, the algorithm identified the known Nipah-positive bat species with 83 percent accuracy. Six species of bats found in Asia, Australia and Oceania have also been identified with characteristics that may make them competent hosts and should be prioritized for monitoring. Four of these species occur in India, two of them in Kerala.”We set out to make trait-based predictions of likely henipavirus reservoirs near Kerala. Our focus was narrow, but the model successfully identified Nipah hosts, showing that this method can serve as a powerful tool to identify Nipah and other in managing the surveillance of disease systems,” stated Raina K. Plowright, a researcher at the American Montana State University.”Identifying disease-carrying species is an important first step in surveillance planning. We must also prioritize research into which virus strains pose the greatest risk to humans. Ultimately, the goal is to eradicate the risk, not to put out fires,” Han summarized their work. most important goal.Hardware, software, tests, interesting and colorful news from the world of IT by clicking here!

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