The Case for Using Geocodes and Activity Codes at Project Appraisal: Insights from a World Bank Anti-Malaria Project in the DRC

Putting timely and actionable information like this in the hands of government and IGO officials who make development policy decisions with far-reaching consequences is a central part of AidData's raison d'être.

July 24, 2012
Bradley C. Parks, Doug Nicholson

As many readers of The First Tranche know, AidData's Mapping for Results partnership with the World Bank Institute resulted in the publication of a geocoded dataset with more than 2500 active World Bank projects in 144 countries. Using these data, the map below visualizes the "spatial footprint" of a single World Bank malaria prevention project in the Democratic Republic of the Congo (DRC).  In 2005, the World Bank initiated a $150 million "Emergency Multisectoral Reconstruction and Rehabilitation Project (EMRRP)" with a set of broadly-defined health objectives and a strong malaria component encompassing 83 health zones across the country. In 2010, the World Bank doubled down on the malaria component, providing an additional $80 million in funding. The Bank's project appraisal documentation indicates that the additional funds were set aside to “[provide] approximately 8.4 million long-lasting insecticidal nets (LLINs)…”.

The EMRRP supported activities in 88 unique physical locations. The map below visualizes the spatial distribution of these activities and overlays these activities on a base map provided by the Malaria Atlas Project. The base map provides subnational data on malaria prevalence among children (ages 2-10) for 2010. Light pink represents areas where less than 5% of children are infected with malaria. Medium pink areas indicate malaria prevalence between 5% and 40%. Maroon areas indicate malaria prevalence over 40%.

World Bank Malaria project location


We don’t know what type of data or maps Task Team Leaders at the Bank might have used to prepare this particular project, yet it appears that they did a reasonably good job of targeting the areas of great need and vulnerability. Project sites follow rivers, and the majority of project activities lie within areas where malaria prevalence is above 40%. Unfortunately, while the EMRRP appears to be a case of smart aid targeting, new researchsuggests that evidence-based targeting may be the exception rather than the rule.

But what if maps like this one became a standard part of the due diligence and project approval process at development banks and aid agencies? What if all World Bank projects had to be geocoded, activity coded, and spatially visualized prior to Board approval? Would this type of transparency help weed out poorly targeted projects? If the Board required that maps like this one be disseminated prior to up-or-down project approval vote, would Task Team Leaders spend more time thinking about their spatial targeting and coordination strategies?

Or, better yet, imagine if Board members could generate customized maps like this one without having to rely on Task Team Leaders. Imagine a visual analytic platform that fused development indicators with queried project locations at the activity level. World Bankers could choose from hundreds of sub-national development indicators (e.g. poverty, child mortality, quality of infrastructure, quality of governance, violence) and query the aid activities of any donor in any recipient country. For example, a Bank staffer or Board member interested in HIV prevention projects in Uganda could overlay all locations of HIV prevention projects in 2010 with sub-national HIV prevalence statistics for 2010. With a few additional clicks, he or she could render a second map with the same 2010 HIV prevention project locations overlaid with HIV incidence statistics for 2012. In two glances, this individual would have an idea of (a) whether 2010 HIV prevention campaigns in Uganda were efficiently sited, and (b) whether these activities had any apparent impact on new HIV cases in 2012. Putting timely and actionable information like this in the hands of government and IGO officials who make development policy decisions with far-reaching consequences is a central part of AidData's raison d'être. But a key barrier to creating this type of platform is access to timely, activity-coded, and georeferenced project-level data, which is why AidData's team devotes a huge amount of time to the collection, standardization, categorization, publication, and visualization of development finance information. We also support the efforts of the Open Aid Partnership to encourage donors to geocode and map their activities.


You can find more information about our mapping initiatives here:

You can access geocoded datasets here:

Brad Parks is the Executive Director of AidData at William & Mary. He leads a team of over 30 program evaluators, policy analysts, and media and communication professionals who work with governments and international organizations to improve the ways in which overseas investments are targeted, monitored, and evaluated. He is also a Research Professor at William & Mary’s Global Research Institute.

Doug Nicholson is an AidData Post-Baccalaureate Fellow at the College of William & Mary. Brad Parks is the Co-Executive Director of AidData and Research Faculty at the College of William & Mary.