Spatial distribution of bednet coverage under routine distribution through the public health sector in a rural district in Kenya.


Autoria(s): O'Meara, WP; Smith, N; Ekal, E; Cole, D; Ndege, S
Data(s)

2011

Identificador

http://www.ncbi.nlm.nih.gov/pubmed/22022481

PONE-D-11-08192

PLoS One, 2011, 6 (10), pp. e25949 - ?

http://hdl.handle.net/10161/5957

1932-6203

Relação

PLoS One

10.1371/journal.pone.0025949

PLoS One

Tipo

Journal Article

Cobertura

United States

Resumo

Insecticide-treated nets (ITNs) are one of the most important and cost-effective tools for malaria control. Maximizing individual and community benefit from ITNs requires high population-based coverage. Several mechanisms are used to distribute ITNs, including health facility-based targeted distribution to high-risk groups; community-based mass distribution; social marketing with or without private sector subsidies; and integrating ITN delivery with other public health interventions. The objective of this analysis is to describe bednet coverage in a district in western Kenya where the primary mechanism for distribution is to pregnant women and infants who attend antenatal and immunization clinics. We use data from a population-based census to examine the extent of, and factors correlated with, ownership of bednets. We use both multivariable logistic regression and spatial techniques to explore the relationship between household bednet ownership and sociodemographic and geographic variables. We show that only 21% of households own any bednets, far lower than the national average, and that ownership is not significantly higher amongst pregnant women attending antenatal clinic. We also show that coverage is spatially heterogeneous with less than 2% of the population residing in zones with adequate coverage to experience indirect effects of ITN protection.

Formato

e25949 - ?

Idioma(s)

ENG

Palavras-Chave #Cluster Analysis #Family Characteristics #Female #Geography #Health Facilities #Humans #Infant #Insecticide-Treated Bednets #Kenya #Models, Biological #Mosquito Control #Multivariate Analysis #Ownership #Pregnancy #Public Health #Public Sector #Regression Analysis #Rural Population