This report provides output for Phase 1 of DFID’s spatial mapping of nutrition programming project. The overall project comprises two discrete phases and aims to better understand if and how spatial analysis can help to coordinate and co-locate nutrition relevant programmes. The rationale for the project is based on the recognition that cross-sector actions are essential to achieve sustained reductions in undernutrition, yet to date limited information is readily available on the spatial overlap of interventions funded by DFID and others to tackle the problem. In addition, data on the determinants of malnutrition is rarely accurately mapped and prevalence data is often only specified at regional or district level.
To determine the potential and scope for spatial mapping and analysis to address these issues the focus of the initial phase was a feasibility analysis and assessment of data availability. Based on the findings a second phase will subsequently undertake a detailed country level analysis and synthesis.
The results for Phase I presented here detail 1) the methods and results of a literature review on the use to date of spatial mapping techniques in nutrition programming; 2) a review of the availability of data on nutrition specific and nutrition sensitive programming; and 3) a synthesis of the two reviews and a feasibility study with recommendations to support Phase 2 of the spatial mapping agenda which will entail the development of ‘heat maps’ of intervention intensity and accuracy of programme targeting in 4 countries.
The literature review identified two major groups of actors using spatial mapping: firstly, academic units and research institutions that often pursue an information only mandate providing national level data; secondly, typically non-governmental and UN organisations who were initially consumers, but are now increasingly becoming producers of spatial data due to the more widely available spatially-oriented and GIS-based technologies. The majority of data used in mapping comes from existing datasets and is multi-indicator.
The rationale for the current use of spatial mapping for health and nutrition largely matches the key elements of a project management cycle but with particular focus on the first stage: identification of the problem, making prevalence maps by far the most common. Coverage maps have been produced recently for evaluation purposes, but as yet, on-going, active monitoring using spatial data is not widespread. The key attraction and advantage of spatial analysis to proponents is its capacity to unmask variability and show accurate, detailed and differentiated patterns on multiple indicators across a programme area in a striking visual format. This is in contrast to the limited practical value at programme planning level of the current highly aggregated data available on health and nutrition indicators. The use of spatial maps to coordinate cross sector projects is as yet infrequent (mostly matrix type) but offers the potential to identify areas of overlap between interventions as well as areas of need or ‘hotspots’, hence promoting the coherent programming and appropriate intervention, which is essential to ensure a sustainable reduction in undernutrition.
Although spatial mapping is a powerful tool, case studies have demonstrated that in order to ensure that programmes are able to make effective and active use of spatial data, ‘buy-in’ and direct long-term engagement is essential at the political and practitioner level.
The data review identified three mapping methods used for reporting spatial data; polygon, pixel and hybrid polygon and pixel. The polygon-based approach using small area estimation, although not providing the highest resolution, appears to be the most accessible and available and does not require other ancillary geospatial data. It is, however possible to trial model based mapping in one country during Phase 2 of the project given the availability of ancillary data for all four focus countries. This will enable a useful comparison of the output of two different methods.
Based on a list of data requirements for each approach and the likely availability of that data in a given country, Tanzania, Ghana, Zambia and Yemen were selected as the focus for Phase 2. Survey and census data from nationally representative surveys is readily available for these countries with the exception of Yemen, where it is hoped this will soon be obtained. In terms of the secondary data requirements, action is needed in a few cases, particularly for a list of nutrition interventions by area for Ghana, Zambia and Yemen in order for their locations to be mapped; but otherwise much has already been obtained or requested. The relevant DFID country offices and country contacts have been provided with a checklist to retrieve and assess data to see if it can be mapped and can measure nutrition and nutrition sensitive indicators.
Despite the increased interest and capacity in spatially oriented approaches they are as yet seen as peripheral or novelty methods. Programme planning and resource allocation continue to be dominated by highly aggregated results from traditional nationally representative surveys. This is underpinned by the fact that goals tend to be set at country level without taking account of in-country spatial variation. The technological shift needs to be matched by a corresponding paradigm shift in the assessment of health and nutrition achievements, with equal importance attached to spatial homogeneity of results as to national aggregates. To meet need, effective programmes must be able to identify where it is most acute and target cross sector interventions to ensure a cohesive and effective response. Spatial mapping can identify hotspots and overlap, and orient planning, implementation, monitoring and coordination of programmes. This needs to be highlighted and evidenced by leading development actors to ensure the commitment of partners to capitalise on this essentially practical tool. Moving forward with Phase 2 of this DFID project will provide an opportunity to explore and demonstrate the value of spatial mapping and engage a wide audience as well as a wide number of active participants. Ensuring coordination with existing initiatives in the focus countries is recommended as is encouraging that the (geo)location (village name) be specified for all future routine or survey data collection.
