Population, behavioural and environmental drivers of malaria prevalence in the Democratic Republic of Congo

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  • Messina, Jane P
    • Affiliation: Carolina Population Center
  • Taylor, Steve
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
    • Other Affiliation: Duke University Medical Center
  • Meshnick, Steven R.
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Linke, Andrew M
    • Other Affiliation: University of Colorado at Boulder
  • Tshefu, Antoinette K
    • Other Affiliation: Université de Kinshasa
  • Atua, Benjamin
    • Other Affiliation: Programme National de Lutte contre le Paludisme (PNLP)
  • Mwandagalirwa, Kashamuka
    • Other Affiliation: Kinshasa General Hospital (HGK)
  • Emch, Michael
    • Affiliation: Carolina Population Center
Abstract
  • 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 which may 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-distance weighting 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 the individual level. Paradoxically, the number of battle events since 1994 surrounding one's community was negatively associated with malaria risk (p < 0.0001). Conclusions This research demonstrates the feasibility of using population-based behavioural and molecular surveillance 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 the DRC 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.
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Resource type
  • Article
Rights statement
  • In Copyright
Rights holder
  • Jane P Messina et al.; licensee BioMed Central Ltd.
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Journal title
  • Malaria Journal
Journal volume
  • 10
Journal issue
  • 1
Page start
  • 161
Language
  • English
Is the article or chapter peer-reviewed?
  • Yes
ISSN
  • 1475-2875
Bibliographic citation
  • Malaria Journal. 2011 Jun 09;10(1):161
Publisher
  • BioMed Central Ltd
Access right
  • Open Access
Date uploaded
  • August 23, 2012

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