title: Assessing bed net use and non-use after long-lasting insecticidal net distribution: a simple framework to guide programmatic strategies.
abstract: BACKGROUND
  Insecticide-treated nets (ITNs) are becoming increasingly available to vulnerable populations at risk for malaria. Their appropriate and consistent use is essential to preventing malaria, but ITN use often lags behind ITN ownership. In order to increase ITN use, it is necessary to devise strategies that accurately identify, differentiate, and target the reasons and types of non-use.
  
  
  METHODS
  A simple method based on the end-user as the denominator was employed to classify each individual into one of four ITN use categories: 1) living in households not owning an ITN; 2) living in households owning, but not hanging an ITN; 3) living in households owning and hanging an ITN, but who are not sleeping under one; and 4) sleeping under an ITN. This framework was applied to survey data designed to evaluate long-lasting insecticidal nets (LLINs) distributions following integrated campaigns in five countries: Togo, Sierra Leone, Madagascar, Kenya and Niger.
  
  
  RESULTS
  The percentage of children <5 years of age sleeping under an ITN ranged from 51.5% in Kenya to 81.1% in Madagascar. Among the three categories of non-use, children living in households without an ITN make up largest group (range: 9.4%-30.0%), despite the efforts of the integrated child health campaigns. The percentage of children who live in households that own but do not hang an ITN ranged from 5.1% to 16.1%. The percentage of children living in households where an ITN was suspended, but who were not sleeping under it ranged from 4.3% to 16.4%. Use by all household members in Sierra Leone (39.9%) and Madagascar (60.4%) indicate that integrated campaigns reach beyond their desired target populations.
  
  
  CONCLUSIONS
  The framework outlined in this paper provides a helpful tool to examine the deficiencies in ITN use. Monitoring and evaluation strategies designed to assess ITN ownership and use can easily incorporate this approach using existing data collection instruments that measure the standard indicators.
authors.affiliation: Centers for Disease Control and Prevention, Center for Global Health, Division of Parasitic Diseases and Malaria, 4770 Buford Hwy MS F-22, Atlanta, GA 30341, USA. jev8@cdc.gov
authors.forename: Jodi L
authors.initials: JL
authors.lastname: Vanden Eng
authors.forename: Julie
authors.initials: J
authors.lastname: Thwing
authors.forename: Adam
authors.initials: A
authors.lastname: Wolkon
authors.forename: Manisha A
authors.initials: MA
authors.lastname: Kulkarni
authors.forename: Ayub
authors.initials: A
authors.lastname: Manya
authors.forename: Marcy
authors.initials: M
authors.lastname: Erskine
authors.forename: Allen
authors.initials: A
authors.lastname: Hightower
authors.forename: Laurence
authors.initials: L
authors.lastname: Slutsker
mesh_terms: D000293:Adolescent; D000328:Adult; D017954:Africa South of the Sahara; D017677:Age Distribution; D000367:Age Factors; D002648:Child; D002675:Child, Preschool; D005191:Family Characteristics; D005260:Female; D019538:Health Care Surveys; D006798:Housing; D006801:Humans; D007223:Infant; D057148:Insecticide-Treated Bednets; D008288:Malaria / Q000517:prevention & control* / Q000635:transmission; D008297:Male; D008875:Middle Aged; D009032:Mosquito Control / Q000295:instrumentation* / Q000379:methods; D057147:Mosquito Nets / Q000706:statistics & numerical data* / Q000600:supply & distribution; D010067:Ownership / Q000706:statistics & numerical data; D015397:Program Evaluation; D055815:Young Adult