A study published in eLife examined the effectiveness in testing blood collected by flies for traces of unknown pathogens, which is improving current predictive methods in global outbreaks.

Methods of predicting the next global outbreak are important ways to save lives before infections travel from animal host to humans. Current methods involve testing animal tissues and organs for the presence of infectious disease. With the number of endangered animals increasing year-by-year, these methods can strain protected species. In response, researchers are studying how using DNA collected by blood-sucking flies can be used as a non-invasive method of infection prediction.

"This is a huge public health issue that urgently requires new tools for the active monitoring of outbreaks and rapid diagnosis of the pathogens involved," explained senior author Franck Prugnolle, an evolutionary geneticist from the National Center for Scientific Research (CNRS) in Montpellier, France. "We wanted to investigate whether blood-feeding insects could act as a sampling tool out in the wild environment, allowing us to monitor the presence and emergence of infectious disease."

Over 16 weeks, researchers collected 4,000 flies from the national parks in Gabon in Central Africa. Three types of flies were collected, 30 percent being the tsetse fly. The blood was tested for host identification and the presence of malaria. Blood was collected from a variety of 20 different animals, including elephants, reptiles and birds. The analyzed samples revealed malaria in 9 percent of blood meals and 18 different undocumented malaria species, while identifying a natural host of the malaria species that was previously unknown.

"These results show that blood meals of the engorged flies can be successfully used to analyze the diversity of known malaria parasites," said Prugnolle. "This approach of 'xenosurveillance' could detect pathogens before they spread to humans, as well as the emergence of new diseases in wild animals that may threaten their long-term survival."