AI in community health monitoring and early warning systems

AI is a transformative tool in global health and education, which is contributing to the rapid shift from conventional reactive practices to proactive data-driven approaches, leading to improvement in these sectors. In many high-income countries, AI has been efficient in rendering assistance to disease detection, remote monitoring, treatment optimization, and personalized learning experiences. However, the adoption of AI has not yet reached a comparable level in some countries thus, this study investigated how AI can be leveraged upon the Nigerian context to enhance community health monitoring and early warning systems within the domain of health education and preventive practice. Drawing on recent literature and case examples, the paper specifically identified and discussed the current applications of AI technologies for community health monitoring and early warning and examined the barriers and enablers to implementing AI-driven monitoring and early warning systems for community health education. The results revealed that although there have been some early AI applications in Nigerian health and educational system, a large portion of the community health education sector is still ill-prepared to incorporate AI tools into monitoring and early warning systems. Low digital literacy, disjointed data systems, inadequate infrastructure, and a lackluster integration of AI into health education practices are major obstacles. In conclusion, the paper highlighted the significant role of artificial intelligence in strengthening community health monitoring systems. Also, that integrating AI innovations with community health education frameworks can enhance community resilience, strengthen preventive health measures, and support the early identification of potential health risks. Additionally, the potential of multi-source environmental and health data platforms, alongside educational partnerships, demonstrates promising opportunities for improved capacity development and more responsive community health systems.