A mobile app that identifies disease-carrying insects from their wing patterns is being developed as part of a project using AI to help diagnose tropical diseases.
Neglected tropical diseases affect more than one billion people worldwide, predominantly in low-income communities across Africa, Asia, and Latin America.
Conditions such as leishmaniasis, dengue and schistosomiasis can cause chronic illness, disability, and, in severe cases, death.
The new research will begin by focussing on leishmaniasis – a rare but potentially fatal disease transmitted by sandflies. More than ninety species of sandflies are known to transmit Leishmania parasites.
The research team will use high-resolution microscopic images to train a machine learning model to recognise different sandfly species from their distinctive wing patterns.
This technology will underpin the development of a mobile app designed to enable scientists and health workers to monitor vector populations more accurately, target control measures with precision, and respond swiftly to emerging outbreaks - ultimately reducing the risk of disease transmission. The app will also serve as a valuable training tool for medical students and newly appointed health workers, enhancing their skills in vector identification and disease prevention.
Professor Tossapon Boongoen from the Aberystwyth University’s Department of Computer Science, who is part of the international research team, said:
“Rapid and accurate identification of disease vectors is critical for controlling outbreaks. Insects can migrate far beyond their usual habitats, sometimes travelling unexpected distances due to climate change. By pinpointing which species are present, one can trace the origin of disease clusters within communities and respond more effectively.
“Traditional diagnostic methods are often slow and require specialists to use them, creating major challenges in regions with limited healthcare access. With AI, we have the potential to transform disease detection into a faster, smarter, and more proactive process. This technology also opens the door to discovering new or previously undetected insect species that may pose emerging health risks.”
The longer-term aim of the research is to expand the technology to identify other insects that spread infectious diseases.
Professor Boongoen added:
“The potential is enormous - the whole team really hopes it can make a real difference to tackling some of the world’s deadliest diseases. Working across disciplines and continents, we are looking at practical, accessible AI solutions which could help health workers respond faster, improve treatment outcomes, and strengthen outbreak control in vulnerable regions.”
The project is funded by the Academy of Medical Science and led by the Centre of Excellence in Vector Biology and Vector Borne Diseases at Chulalongkorn University in Thailand. Other collaborators include the Liverpool School of Tropical Medicine, Naresuan University in Thailand, Instutut Pasteur in France, Charles University in the Czech Republic, and the Artificial Intelligence Association of Thailand.