Modeling Accessibility to Public Health Facilities in Resource-Limited Settings Through GIS and Geo-AI Applications

Locating appropriate health facilities based on the community’s needs and demands for optimal usage is vital for successful health systems planning. Indicators to measure equitable access to health services based on the community’s risks to local diseases have been revolutionized by adopting public health informatics and big data analytics. Spatial epidemiological tools and computational methods using geographic information system (GIS) and artificial intelligence (AI) algorithms have eased the community’s place-based health assessments based on real-time ground truth approaches and virtual modes. Such population health management interventions are time-saving and cost-effective as compared to conventional measurement approaches in determining the accessibility and distribution of health facilities. This chapter systematically appraises the health burden afflicted within communities from health services inaccessibility. The chapter discusses key concepts and approaches to evaluate and model health facilities’ accessibility within the GIS and AI environment while discussing their potential advantages and disadvantages constructed via two real-life case studies from the Malaysian perspective.