title: Exploring the impact of targeted distribution of free bed nets on households bed net ownership, socio-economic disparities and childhood malaria infection rates: analysis of national malaria survey data from three sub-Saharan Africa countries.
abstract: BACKGROUND
  The last decade has witnessed increased funding for malaria control. Malaria experts have used the opportunity to advocate for rollout of such interventions as free bed nets. A free bed net distribution strategy is seen as the quickest way to improve coverage of effective malaria control tools especially among poorest communities. Evidence to support this claim is however, sparse. This study explored the effectiveness of targeted free bed net distribution strategy in achieving equity in terms of ownership and use of bed nets and also reduction of malaria prevalence among children under-five years of age.
  
  
  METHODS
  National malaria indicator survey (MIS) data from Angola, Tanzania and Uganda was used in the analysis. Hierarchical multilevel logistic regression models were used to analyse the relationship between variables of interest. Outcome variables were defined as: childhood test-confirmed malaria infections, household ownership of any mosquito net and children's use of any mosquito nets. Marginal effects of having free bed net distribution on households with different wealth status were calculated.
  
  
  RESULTS
  Angolan children from wealthier households were 6.4 percentage points less likely to be parasitaemic than those in poorest households, whereas those from Tanzania and Uganda were less likely to test malaria positive by 7 and 11.6 percentage points respectively (p < 0.001). The study estimates and present results on the marginal effects based on the impact of free bed net distribution on children's malaria status given their socio-economic background. Poorest households were less likely to own a net by 21.4% in Tanzania, and 2.8% in Uganda, whereas both poorer and wealthier Angolan households almost achieved parity in bed net ownership (p < 0.001). Wealthier households had a higher margin of using nets than poorest people in both Tanzania and Uganda by 11.4% and 3.9% respectively. However, the poorest household in Angola had a 6.1% net use advantage over children in wealthier households (p < 0.001).
  
  
  CONCLUSIONS
  This is the first study to use nationally representative data to explore inequalities in bed net ownership and related consequences on childhood malaria infection rates across different countries. While targeted distribution of free bed nets improved overall bed net ownership, it did not overcome ownership inequalities as measured by household socioeconomic status. Use of bed nets was disproportionately lower among poorest children, except for Angola where bed net use was higher among poorest households when compared to children in wealthier households. The study highlights the need for malaria control world governing bodies and policy makers to continue working on finding appropriate strategies to improve access to effective malaria control tools especially by the poorest who often times bears the brunt of malaria burden than their wealthier counterparts.
authors.affiliation: Department of Health Policy & Management, Rollins School of Public Health (RSPH) of Emory University, 1518 Clifton Rd 16NE, Atlanta, GA 30322, USA. jdnjau@emory.edu
authors.forename: Joseph D
authors.initials: JD
authors.lastname: Njau
authors.forename: Rob
authors.initials: R
authors.lastname: Stephenson
authors.forename: Manoj
authors.initials: M
authors.lastname: Menon
authors.forename: S Patrick
authors.initials: SP
authors.lastname: Kachur
authors.forename: Deborah A
authors.initials: DA
authors.lastname: McFarland
mesh_terms: D000810:Angola / Q000453:epidemiology; D002675:Child, Preschool; D005191:Family Characteristics; D005260:Female; D006302:Health Services Research; D006801:Humans; D007223:Infant; D057148:Insecticide-Treated Bednets / Q000191:economics / Q000600:supply & distribution*; D008288:Malaria / Q000453:epidemiology* / Q000517:prevention & control*; D008297:Male; D010067:Ownership / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D013636:Tanzania / Q000453:epidemiology; D014454:Uganda / Q000453:epidemiology