Over 65 percent of people in the Democratic Republic of the Congo (DRC) live more than 5 kilometres from a health facility, compromising their ability to access timely healthcare. This problem directly contributes to DRC’s high child mortality rate; according to DRC’s Ministry of Health, over 80 percent of children who die from malaria, cholera, and other common diseases do so at home or on the way to find treatment. 

In 2005, the ministry launched a community health strategy that aims to improve access to quality healthcare in remote areas via community care sites (sites de soins communautaires, SSCs). These sites are volunteer-led clinics equipped to treat certain cases of malaria, diarrhoea and pneumonia, screen for malnutrition, and conduct epidemiological surveillance. After two decades of efforts, there are now 10,198 SSCs in operation throughout the country. 

And yet, since DRC’s last nationwide census was held in 1984, the data that have been used to place new SSCs have been very outdated. In response, GRID3 and the Clinton Health Access Initiative (CHAI) worked with the ministry to use GRID3 geospatial data to gain a better understanding of today’s communities that, in turn, will help to ensure new SSCs are built in areas where they are needed the most. 

DRC’s National Program for the Elimination of Cholera and the Control of Other Diarrheal Diseases (PNECHOL-MD) partnered with GRID3 and CHAI for a pilot initiative. The pilot focused on using geospatial data in combination with a site placement optimisation algorithm from GRID3 partner Flowminder in two health zones (Ndjoko Mpunda and Banga Lubaka) to establish new SSCs that would reach unserved areas with the highest population density. 

Initial discussions began in February 2021, just as GRID3 was launching data collection fieldwork for the GRID3 Mapping for Health project. After learning about the importance of SSCs and the interest that the PNECHOL-MD had in mapping these facilities, GRID3 began collecting data on existing SSCs in Kasaï, Kasaï-Oriental, Lomami, and Haut-Katanga; specifically, it collected data on the SSC locations via GPS-enabled smartphones. Together with other collected geospatial data, GRID3 created datasets featuring health zone and health area boundaries, settlement points, areas that were covered by existing health facilities, and populations that were located within a one-hour walk of the facility.  

These data were also fed into the optimisation algorithm to model optimal locations for potential new sites and maximise the population reached by a new SSC (and minimise overlaps in catchment areas). Potential sites were ranked by population density within the service radius; the rankings were then used by DRC officials in their decision-making about where to place six new SSCs in Kasaï (these new facilities have been in operation since December 2021). The GRID3-produced maps helped to show the travel time from settled areas to the nearest health centre and SSC. They also helped to show barriers (such as natural features or conflicts) that prevent populations from accessing basic healthcare. 

Following the creation of health zone maps for Ndjoko Mpunda and Banga Lubaka, GRID3 then produced maps for all 18 health zones. 

“The production of geospatial data will make it possible to meet real needs in the communities; by using this data, we will know how to provide support and intervention for first aid, especially for children under 5 years old,”

says Dr. Albert Kadjunda, Technical Director at the PNECHOL-MD. 

GRID3’s geospatial solutions also provide a strong foundation for planning the placement of other SSC sites throughout the country.