This article looks at donors’ ability to target the highest exposure to malaria risk when information in a given health context is fragmented. The case study examined in this analysis focuses on malaria transmission caused by mining activities in the Democratic Republic of Congo, as well as on financial and epidemiological data from health facilities. This exercise seeks to estimate how local aid is matching the local malaria burden. Using fine-grained data on mines and health infrastructure, no evidence was found that local populations exposed to the highest risk of malaria transmission receive a proportionately higher share of aid compared to neighbouring areas with reduced exposure to malaria risk.