New approach predicts disease transmission among wildlife and humans
Using machine learning, researchers can forecast outbreaks of pathogens such as coronavirus and monkeypox
Peer-Reviewed PublicationTAMPA, Fla. (Sept. 1, 2022) – The rate that emerging wildlife diseases infect humans has steadily increased over the last three decades. Viruses, such as the global coronavirus pandemic and recent monkeypox outbreak, have heightened the urgent need for disease ecology tools to forecast when and where disease outbreaks are likely.
A University of South Florida assistant professor helped develop a methodology that will do just that – predict disease transmission from wildlife to humans, from one wildlife species to another and determine who is at risk of infection.
The methodology is a machine-learning approach that identifies the influence of variables, such as location and climate, on known pathogens. Using only small amounts of information, the system is able to identify community hot spots at risk of infection on both global and local scales.
“Our main goal is to develop this tool for preventive measures,” said co-principal investigator Diego Santiago-Alarcon, a USF assistant professor of integrative biology. “It’s difficult to have an all-purpose methodology that can be used to predict infections across all the diverse parasite systems, but with this research, we contribute to achieving that goal.”
With help from researchers at the Universiad Veracruzana and Instituto de Ecologia, located in Mexico, Santiago-Alarcon examined three host-pathogen systems – avian malaria, birds with West Nile virus and bats with coronavirus – to test the reliability and accuracy of the models generated by the methodology.
The team found that for the three systems, the species most frequently infected was not necessarily the most susceptible to the disease. To better pinpoint hosts with higher risk of infection, it was important to identify relevant factors, such as climate and evolutionary relationships.
By integrating geographic, environmental and evolutionary development variables, the researchers identified host species that have previously not been recorded as infected by the parasite under study, providing a way to identify susceptible species and eventually mitigate pathogen risk.
“We feel confident that the methodology is successful, and it can be applied widely to many host-pathogen systems,” Santiago-Alarcon said. “We now enter into a phase of improvement and refinement.”
The results, published in the Proceedings of the National Academy of Sciences, prove the methodology is able to provide reliable global predictions for the studied host–pathogen systems, even when using a small amount of information. This new approach will help direct infectious disease surveillance and field efforts, providing a cost-effective strategy to better determine where to invest limited disease resources.
Predicting what kind of pathogen will produce the next medical or veterinary infection is challenging, but necessary. As the rate of human impact on natural environments increases, opportunity for novel diseases will continue to rise.
“Humanity, and indeed biodiversity in general, are experiencing more and more infectious disease challenges as a result of our incursion and destruction of the natural order worldwide through things like deforestation, global trade and climate change,” said Andrés Lira-Noriega, research fellow at the Instituto de Ecologia. “This imposes the need of having tools like the one we are publishing to help us predict where new threats in terms of new pathogens and their reservoirs may occur or arise.”
The team plans to continue their research to further test the methodology on additional host-pathogen systems and extend the study of disease transmission to predict future outbreaks. The goal is to make the tool easily accessible through an app for the scientific community by the end of 2022.
About the University of South Florida
The University of South Florida, a high-impact global research university dedicated to student success, generates an annual economic impact of more than $6 billion. Over the past 10 years, no other public university in the country has risen faster in U.S. News and World Report’s national university rankings than USF. Serving more than 50,000 students on campuses in Tampa, St. Petersburg and Sarasota-Manatee, USF is designated as a Preeminent State Research University by the Florida Board of Governors, placing it in the most elite category among the state’s 12 public universities. USF has earned widespread national recognition for its success graduating under-represented minority and limited-income students at rates equal to or higher than white and higher income students. USF is a member of the American Athletic Conference. Learn more at www.usf.edu.
JOURNAL
Proceedings of the National Academy of Sciences
METHOD OF RESEARCH
Data/statistical analysis
SUBJECT OF RESEARCH
People
ARTICLE TITLE
Wildlife susceptibility to infectious diseases at global scales
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