It can be challenging to provide consistent health services in urban slums, which often contain populations with some of the lowest levels of access to government services. Simple data collection tools, geospatial analysis, and local stakeholder expertise can be combined to develop targeted solutions to help fix this.

Typically, limited data is available on the location, size, and population of slums, which makes it hard to plan, deliver and oversee services. Limited access to health facilities, linguistic barriers, and atypical working hours of slum dwellers further contribute to the challenge. In addition, slum areas often attract displaced populations or refugees, who can face stigma or other barriers when seeking services.

However, three activities in combination can form a basis for improving services in slums:

Combine basic technology with local expertise to map slums

Data is often limited on the location, shape, and size of urban slums. However, basic smartphones with GIS functionality can rapidly collect this data. In Addis Ababa, it took four people ten days to map and locate all 88 slums in the city, with the support of four government health workers. Policy-makers now know the number, size and location of slums for the first time, and can use this information to improve services.

Use simple surveys to understand challenges

There is typically a lack of Information on specific issues facing populations in urban slums. Simple surveys can be used to collect data during brief visits to slums, and then inform evidence-based decision-making on how to improve service delivery. In Addis Ababa, our small team used a mobile application to survey 355 mothers in ten days. The resulting analysis revealed issues and challenges, previously unknown, that are now being addressed.

Use innovative data sources and geospatial analysis to identify population needs

A lack of reliable data on the population of urban slums, or their distance from health facilities, can make it difficult to identify and resolve access challenges. To remedy this, innovative population density data, health facility location data, and urban slum-shape data was collected and analysed, with the outputs visualised on a bespoke geospatial dashboard for managers. This provides managers with a clear view of the nearest health facility to each slum area, and helps identify those slum areas which are far from health facilities and require additional service delivery solutions.

Based on this new data and insights, the government was able to adopt a collaborative approach with partners, pooling expertise, experience and resources to address the challenges. Once data and analysis on slum locations was available, our teams supported the government and partners to review insights, prioritise intervention areas, and develop targeted solutions.

Specifically, improved messaging, training and supervision are being used to boost the effectiveness of existing services, while new integrated outreach services have been launched. Together these actions are leading to strong improvements in services in these critical areas.