Molecular malaria epidemiology: mapping and burden estimates for the Democratic Republic of the Congo, 2007.

backgroundEpidemiologic data on malaria are scant in many high-burden countries including the Democratic Republic of the Congo (DRC), which suffers the second-highest global burden of malaria. Malaria control efforts in regions with challenging infrastructure require reproducible and efficient surveillance. We employed new high-throughput molecular testing to characterize the state of malaria control in the DRC and estimate childhood mortality attributable to excess malaria transmission. METHODS AND

findingsThe Demographic and Health Survey was a cross-sectional, population-based cluster household survey of adults aged 15-59 years in 2007 employing structured questionnaires and dried blood spot collection. Parasitemia was detected by real-time PCR, and survey responses measured adoption of malaria control measures and under-5 health indices. The response rate was 99% at the household level, and 8,886 households were surveyed in 300 clusters; from 8,838 respondents molecular results were available. The overall prevalence of parasitemia was 33.5% (95% confidence interval [C.I.] 32-34.9); P. falciparum was the most prevalent species, either as monoinfection (90.4%; 95% C.I. 88.8-92.1) or combined with P. malariae (4.9%; 95% C.I. 3.7-5.9) or P. ovale (0.6%; 95% C.I. 0.1-0.9). Only 7.7% (95% CI 6.8-8.6) of households with children under 5 owned an insecticide-treated bednet (ITN), and only 6.8% (95% CI 6.1-7.5) of under-fives slept under an ITN the preceding night. The overall under-5 mortality rate was 147 deaths per 1,000 live births (95% C.I. 141-153) and between clusters was associated with increased P. falciparum prevalence; based on the population attributable fraction, 26,488 yearly under-5 deaths were attributable to excess malaria transmission.

conclusionsAdult P. falciparum prevalence is substantial in the DRC and is associated with under-5 mortality. Molecular testing offers a new, generalizable, and efficient approach to characterizing malaria endemicity in underserved countries.