Synergistic integration of climate change and zoonotic diseases by artificial intelligence: a holistic approach for sustainable solutions

Abstract

Artificial intelligence (AI) is a rapidly evolving field that can impel research in communicable diseases with respect to climate projections, ecological indicators and environmental impact, at the same time revealing new, previously overlooked events. A number of zoonotic and vector-borne diseases already show signs of expanding their northern geographical ranges and appropriate risk assessment and decision support are urgently needed. The deployment of AI-enabled monitoring systems tracking animal populations and environmental changes is of immense potential in the study of transmission under different climate scenarios. In addition, AI's capability to identify new treatments should not only accelerate drug and vaccine discovery but also help predicting their effectiveness, while its contribution to genetic pathogen speciation would assist the evaluation of spillover risks with regard to viral infections from animals to human. Close collaboration between AI experts, epidemiologists and other stakeholders is not only crucial for responding to challenges interconnected with a variety of variables effectively, but also necessary to warrant responsible AI use. Despite its wider successful implementation in many fields, AI should be seen as a complement to, rather than a replacement of, traditional public health measures.