Improving geographical accessibility modeling for operational use by local health actors

Area of Science:

• Geographic Information Systems (GIS)
• Health Services Research
• Remote Sensing

Background:

• Geographic accessibility to healthcare is a major barrier in rural developing regions.
• Limited local geographic data hinders targeted interventions for improving healthcare access.
• This study addresses the need for precise, context-specific accessibility estimates in rural Madagascar.

Purpose of the Study:

• To develop highly accurate, localized estimates of geographic accessibility to healthcare facilities in rural Madagascar.
• To support the design and implementation of interventions aimed at improving healthcare access for underserved populations.
• To create actionable data for local health authorities to address access barriers.

Main Methods:

• Utilized a participatory approach to map infrastructure and residential areas on OpenStreetMap (OSM).
• Employed Open Source Routing Machine (OSMR) to calculate shortest routes from households to health facilities.
• Integrated remote sensing data (land cover, DEM, rainfall) and GPS-tracked walking routes to model travel speed and predict travel times.

Main Results:

• Mapped over 100,000 buildings, 23,000 km of footpaths, and 4925 residential areas in Ifanadiana district.
• Found that over 75% of the population is more than one hour from a primary health care center (PHC).
• Identified specific remote areas and vulnerable populations with significant travel times (>5 hours to PHCs, >1 hour to CHSs).

Conclusions:

• Demonstrates a method for context-specific geographic accessibility modeling actionable by local health actors.
• Highlights the critical role of precise accessibility data in achieving universal health coverage (UHC) in rural settings.
• Emphasizes the importance of such approaches for global health equity in underserved areas.