Abhra Chaudhuri, Pallab Chatterjee, Sajal Bhattacharya
Vector-borne diseases (VBDs) such as malaria, dengue, chikungunya, Japanese encephalitis etc., remain major public health concerns, particularly in densely populated countries like India claiming hundreds of thousands of lives each year. Consequently, their management and prevention are of utmost importance to public health authorities across the world. However, doing so involves various complex challenges relating to a thorough understanding of the interplay between the disease/vector, pathogen, reservoir host and victim, as well as complex environmental, ecological, and social phenomena, something that is achievable by human researchers only, with domain-specific expertise obtained through years of training, alongside the expenditure of significant public funds. Such stringent requirements often put economically underdeveloped societies at risk in the event that they are unable to afford the time and resources required to be invested in order to properly understand and manage such diseases. To this end, we propose the usage of the recent advancements in Artificial Intelligence (AI) to plan the management and mitigation of vector-borne diseases. We discuss potential applications of generative AI in developing a better understanding of novel and rare vector borne diseases, as well as a medium to provide automated assistance to non experts. Finally, we identify possible challenges that an institution might run into in the process of adopting AI as a way to augment their capabilities in dealing with vector-borne diseases.
Abhra Chaudhuri, Pallab Chatterjee, Sajal Bhattacharya, 2026. MANAGEMENT OF VECTOR-BORNE DISEASES WITH ARTIFICIAL INTELLIGENCE AND ITS LIMITATIONS. Journal of Medical Arthropodology & Public Health 6(1): 1175–1186.