Background: Malaria is highly endemic in the Democratic Republic of Congo (DRC), but the limits and intensity of transmission within the country are unknown. It is important to discern these patterns as well as the drivers whichmay underlie them in order for effective prevention measures to be carried out.Methods: By applying high-throughput PCR analyses on leftover dried blood spots from the 2007 Demographic and Health Survey (DHS) for the DRC, prevalence estimates were generated and ecological drivers of malaria were explored using spatial statistical analyses and multilevel modelling.Results: Of the 7,746 respondents, 2268 (29.3%) were parasitaemic; prevalence ranged from 0-82% within geographically-defined survey clusters. Regional variation in these rates was mapped using the inverse-distanceweighting spatial interpolation technique. Males were more likely to be parasitaemic than older people or females(p < 0.0001), while wealthier people were at a lower risk (p < 0.001). Increased community use of bed nets (p =0.001) and community wealth (p < 0.05) were protective against malaria at the community level but not at theindividual level. Paradoxically, the number of battle events since 1994 surrounding oneLs community was negativelyassociated with malaria risk (p < 0.0001).Conclusions: This research demonstrates the feasibility of using population-based behavioural and molecularsurveillance in conjunction with DHS data and geographic methods to study endemic infectious diseases. This study provides the most accurate population-based estimates to date of where illness from malaria occurs in theDRC and what factors contribute to the estimated spatial patterns. This study suggests that spatial information and analyses can enable the DRC government to focus its control efforts against malaria