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Crosscut & DHIS2
Crosscut’s Microplanning App brings automatically-generated catchment area maps directly into DHIS2, enabling health program teams to visualize service areas, estimate target populations, and plan outreach — without needing GIS expertise.
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About Crosscut
Crosscut is a geospatial microplanning tool that lets non-technical users generate accurate health facility catchment area maps in minutes. By drawing on publicly available datasets — population density, elevation, road networks, waterways, land cover, and administrative boundaries — Crosscut’s analytics engine produces maps that have been validated to be as accurate as those created by specialist GIS teams, at a fraction of the time and cost. Crosscut offers a free-to-use web application at app.crosscut.io and advisory services to global health implementing partners including USAID, UNICEF, the Gates Foundation, and others.
Crosscut is a Strategic DHIS2 Technology Partner.
DHIS2 use case
The DHIS2 Crosscut Microplanning App (available on GitHub) integrates Crosscut’s catchment area engine directly into DHIS2. Health teams can generate catchment boundaries for their DHIS2-registered health facilities, publish them back into DHIS2 as organization unit geometries, and immediately use them in DHIS2’s Maps and reporting modules — combining geographic catchment data with DHIS2 program data for coverage analysis and supply planning.
Key capabilities within the DHIS2 app:
- Generate catchment area boundaries for health facilities and publish them to DHIS2 with a single click
- Estimate target populations per catchment area to quickly calculate program coverage
- Visualize travel times to facilities to support outreach and session planning
- Create thematic maps in DHIS2’s Maps module by combining catchment areas with DHIS2 reporting data
- Designed for non-technical DHIS2 users — no GIS background required
Real-world example
Crosscut has supported geospatial microplanning work in global health programs in collaboration with partners including WHO, UNICEF, Abt Associates, Sightsavers, the Carter Center, and others. Use cases have spanned immunization microplanning, disease surveillance, and supply chain optimization in low- and middle-income country settings where accurate catchment data has historically been difficult and expensive to produce.