AI Tools in the Diagnosis and Prediction of Endemic Zoonotic Diseases in Asia and Africa

The rapid advancement of Artificial Intelligence (AI)–based gadgets and technologies at global levels demonstrate examples and evidences to complement various fields, including engineering, robotics, electronics, and life sciences. These AI tools possess the potential and capacity to improve diagnosis and treatment of zoonotic diseases endemic in Asian and African countries. In this chapter, the emphasis is on the advances and development of AI instruments tailored to the monitoring, diagnosis, and prognosis of zoonotic diseases that present potential public health threats in these regions. The chapter describes research gap and space for the employment of machine learning, natural language processing, and data analytics to analyze diseases’ profiles, modeling disease’s potential occurrence, and enabling timely responses. The chapter also highlights some of the limitations encountered when deploying AI solutions to manipulate data shallowness, hardware constraints, and professional reliance on health professionals, veterinarians, and technologists. AI tools offer the promise of revolutionizing zoonotic disease management, but their success depends on the health information structures, capacity-building, trained technical staff, training of healthcare professionals, and stakeholder’s involvement. Specifically, the sustainability of health for humans, animals, and the environment systems depends on the valid AI technologies to the disease surveillance and response frameworks. Lastly, this chapter also argues published literature to discuss appropriate strategies or remedial measures for the government and healthcare professionals to create enabling environment by controlling zoonotic diseases in Asia and Africa.