Ebrahim Abbasi
Abstract Vector-borne diseases (VBDs) cause over 700 million cases annually, exacerbated by insecticide resistance, climate change, and urbanization. Conventional control strategies are increasingly insufficient. A narrative review (2015–2025) was conducted across PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar. Over 3500 records were screened; 16 studies were included, focusing on AI applications (e.g. machine learning, geospatial analytics) and biotechnological tools (e.g. CRISPR-Cas9, Wolbachia). The reviewed literature demonstrated that AI-based tools improve vector surveillance, outbreak prediction, and resource allocation, while biotechnological approaches such as Wolbachia-based interventions and gene-editing technologies show considerable potential for reducing disease transmission. Several studies highlighted the advantages of integrating AI with biotechnology to improve the precision, scalability, and sustainability of vector control programs. AI–biotechnology integration offers an emerging framework for sustainable, equitable IVM, though challenges include infrastructure gaps, ethics, and regulation.