Human-induced climate change caused by fossil fuel-derived greenhouse gas emissions has disrupted global ecosystems, shifted disease–vector populations, and expanded vector-borne diseases into previously unaffected areas. As these changes occur, traditional epidemiological surveillance and control mechanisms face major challenges. Artificial intelligence (AI) is an emerging technology in epidemiology and public health that offers the promise of analyzing and interpreting vast datasets far more comprehensively than traditional methods. In this manuscript, we examine how artificial intelligence can enhance vector-borne disease prediction and surveillance, strengthen vector control and public health response, and support clinical and laboratory diagnostic capabilities in the context of a changing climate. Despite its environmental trade-offs, AI offers transformative potential to help humanity adapt to the coming climate impacts on infectious diseases.
Oehler et al. (Tue,) studied this question.