A new era could begin in monitoring wildlife pathogens

For decades, research on wildlife parasites and pathogens has often relied on methods that require capturing, handling, or even euthanizing animals. These invasive approaches can impose considerable stress on wildlife. However, according to a recently published article by researchers at the HUN-REN Centre for Ecological Research, a growing number of modern, non-invasive methods are now available that enable the monitoring of parasites and pathogens without placing substantial stress or burden on wild animals, showing that in many cases, animals do not even need to be captured. For example, genetic traces obtained from the environment, such as environmental DNA (eDNA) collected from water samples, can reveal the presence of mosquito larvae before they become widespread in a particular area. In addition, blood meal analysis, screened from blood-feeding arthropods, including ticks and mosquitoes, can be used to identify the host species they fed on and detect the pathogens circulating in the host's blood. Camera trap images can also help identify diseases with characteristic clinical signs, such as sarcoptic mange in red foxes. Furthermore, samples preserved in museum collections provide valuable information on the historical occurrence of infections and parasite diversity, reducing the need to recapture or resample the wildlife populations under investigation.

Public participation is also becoming increasingly important. Through citizen science, hikers, and nature enthusiasts, can contribute to scientific research by taking photographs, reporting their observations, or submitting ticks and mosquitoes for analysis. These data greatly expand the spatial and temporal coverage of surveillance efforts and can help the early detection of invasive species. One example is the Hungarian Mosquito Monitoring Project (mosquitosurveillance.hu), a citizen science initiative coordinated by the authors that has been running since 2019 and engages the public in documenting the spread of invasive mosquitoes across Hungary. The project has also developed a predictive system that identifies areas where these blood-feeding insects, including the Asian tiger mosquito, are most likely to appear. Furthermore, artificial intelligence and machine learning are opening up more opportunities. By integrating ecological, genetic, and environmental data from multiple sources, researchers can predict which regions or wildlife species are most likely to experience the emergence of new infectious diseases.

The authors highlight that these novel approaches cannot entirely replace conventional surveillance methods in every situation. Nevertheless, they can substantially reduce the impact of research on wildlife. The most reliable results are achieved by combining multiple complementary methods and ensuring that new approaches are rigorously validated. According to the authors, the growing adoption of non-invasive surveillance methods benefits nature conservation, animal health, and ultimately human health alike. These innovative tools enable earlier detection of emerging infections and provide a more accurate understanding of how pathogens and parasites spread, while making wildlife research more ethical and sustainable.