Appendix 3: Case Study - GRID3 Health Catchment Areas

Goal: To improve health catchment area layers and micro-planning tools

Method:

• Produce referenced geospatial data and model population density at high resolution.

• Derive complete and precise georeferenced micro-plans.

• Allow data driven decision making.

Data composition:

• A complete map of settlements with name and basic administrative information (territory, village, town, hamlets)

• Full map of health facilities with unique identifier

• Health zone boundaries at provincial, zone and health area levels

• Grided populations

Data sources:

• DHIS2 (health facilities unique identifier)

• Health zones/areas created by other organizations (MSF, IFRC, etc)

• Field workers through participatory mapping

Data validation: Participatory mapping - use of health teams with field knowledge to delineate boundaries to trace and agree on precise limits of health areas generated upstream through satellite images.

Design tools/Technology: Novel-t (a mobile application that makes it possible to collect data while following movements of head nurses to better define their field of action and limits of health areas)

Steps:

• Use satellite imagery to detect residential areas.

• Create contours (point to raster, raster to contour).

• Classify settlements (e.g Hamlet: any settlement with 1 – 50 buildings)

• Compilation, assessment, and consolidation of existing geospatial data.

• Produce preliminary boundary layers (geospatial list of settlements + tabular list of villages = boundaries delineated based on village names)

• Data collection and participatory mapping by health zone teams in the field to validate already existing health boundaries created through satellite imagery.