Geographical Factors Affecting Bed Net Ownership, a Tool for the Elimination of Anopheles-Transmitted Lymphatic Filariasis in Hard-to-Reach Communities
Identifieur interne : 004463 ( Pmc/Curation ); précédent : 004462; suivant : 004464Geographical Factors Affecting Bed Net Ownership, a Tool for the Elimination of Anopheles-Transmitted Lymphatic Filariasis in Hard-to-Reach Communities
Auteurs : Michelle C. Stanton ; Moses J. Bockarie ; Louise A. Kelly-HopeSource :
- PLoS ONE [ 1932-6203 ] ; 2013.
Abstract
Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = −0.28, −0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67–7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy.
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DOI: 10.1371/journal.pone.0053755
PubMed: 23308281
PubMed Central: 3538722
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Geographical Factors Affecting Bed Net Ownership, a Tool for the Elimination of <italic>Anopheles</italic>-Transmitted Lymphatic Filariasis in Hard-to-Reach Communities</title><author><name sortKey="Stanton, Michelle C" sort="Stanton, Michelle C" uniqKey="Stanton M" first="Michelle C." last="Stanton">Michelle C. Stanton</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Bockarie, Moses J" sort="Bockarie, Moses J" uniqKey="Bockarie M" first="Moses J." last="Bockarie">Moses J. Bockarie</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Kelly Hope, Louise A" sort="Kelly Hope, Louise A" uniqKey="Kelly Hope L" first="Louise A." last="Kelly-Hope">Louise A. Kelly-Hope</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">23308281</idno><idno type="pmc">3538722</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3538722</idno><idno type="RBID">PMC:3538722</idno><idno type="doi">10.1371/journal.pone.0053755</idno><date when="2013">2013</date><idno type="wicri:Area/Pmc/Corpus">004464</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">004464</idno><idno type="wicri:Area/Pmc/Curation">004463</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">004463</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Geographical Factors Affecting Bed Net Ownership, a Tool for the Elimination of <italic>Anopheles</italic>-Transmitted Lymphatic Filariasis in Hard-to-Reach Communities</title><author><name sortKey="Stanton, Michelle C" sort="Stanton, Michelle C" uniqKey="Stanton M" first="Michelle C." last="Stanton">Michelle C. Stanton</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Bockarie, Moses J" sort="Bockarie, Moses J" uniqKey="Bockarie M" first="Moses J." last="Bockarie">Moses J. Bockarie</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author><author><name sortKey="Kelly Hope, Louise A" sort="Kelly Hope, Louise A" uniqKey="Kelly Hope L" first="Louise A." last="Kelly-Hope">Louise A. Kelly-Hope</name><affiliation><nlm:aff id="aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = −0.28, −0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67–7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Gardon, J" uniqKey="Gardon J">J Gardon</name></author><author><name sortKey="Gardon Wendel, N" uniqKey="Gardon Wendel N">N Gardon-Wendel</name></author><author><name sortKey="Demanga Ngangue Kamgno, J" uniqKey="Demanga Ngangue Kamgno J">J Demanga-Ngangue, Kamgno</name></author><author><name sortKey="Chippaux, Jp" uniqKey="Chippaux J">JP Chippaux</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zoure, Hgm" uniqKey="Zoure H">HGM Zouré</name></author><author><name sortKey="Wanji, S" uniqKey="Wanji S">S Wanji</name></author><author><name sortKey="Noma, M" uniqKey="Noma M">M Noma</name></author><author><name sortKey="Amazigo, Uv" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">23308281</article-id><article-id pub-id-type="pmc">3538722</article-id><article-id pub-id-type="publisher-id">PONE-D-12-28534</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0053755</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth Sciences</subject><subj-group><subject>Geography</subject><subj-group><subject>Human Geography</subject><subj-group><subject>Spatial Analysis</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine</subject><subj-group><subject>Epidemiology</subject><subj-group><subject>Spatial Epidemiology</subject></subj-group></subj-group><subj-group><subject>Infectious Diseases</subject><subj-group><subject>Neglected Tropical Diseases</subject><subj-group><subject>Lymphatic Filariasis</subject></subj-group></subj-group><subj-group><subject>Infectious Disease Control</subject><subject>Vectors and Hosts</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Social and Behavioral Sciences</subject><subj-group><subject>Geography</subject><subj-group><subject>Geoinformatics</subject><subj-group><subject>Spatial Autocorrelation</subject></subj-group></subj-group><subj-group><subject>Human Geography</subject></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Geographical Factors Affecting Bed Net Ownership, a Tool for the Elimination of <italic>Anopheles</italic>-Transmitted Lymphatic Filariasis in Hard-to-Reach Communities</article-title><alt-title alt-title-type="running-head">Geographical Factors Affecting Bed Nets</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Stanton</surname><given-names>Michelle C.</given-names></name><xref ref-type="aff" rid="aff1"></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>Bockarie</surname><given-names>Moses J.</given-names></name><xref ref-type="aff" rid="aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Kelly-Hope</surname><given-names>Louise A.</given-names></name><xref ref-type="aff" rid="aff1"></xref></contrib></contrib-group><aff id="aff1"><addr-line>Centre for Neglected Tropical Diseases, Liverpool School of Tropical Medicine, Liverpool, United Kingdom</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Yukich</surname><given-names>Joshua</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>Tulane University School of Public Health and Tropical Medicine, United States of America</addr-line></aff><author-notes><corresp id="cor1">* E-mail: <email>michelle.stanton@liv.ac.uk</email></corresp><fn fn-type="conflict"><p><bold>Competing Interests: </bold>This study was partially supported through a grant from the commercial funder GlaxoSmithKline. This does not alter the authors' adherence to all of the PLOS ONE policies on sharing data and materials.</p></fn><fn fn-type="con"><p>Conceived and designed the experiments: MCS LKH. Analyzed the data: MCS LKH. Wrote the paper: MCS LKH MJB.</p></fn></author-notes><pub-date pub-type="collection"><year>2013</year></pub-date><pub-date pub-type="epub"><day>7</day><month>1</month><year>2013</year></pub-date><volume>8</volume><issue>1</issue><elocation-id>e53755</elocation-id><history><date date-type="received"><day>13</day><month>9</month><year>2012</year></date><date date-type="accepted"><day>4</day><month>12</month><year>2012</year></date></history><permissions><copyright-year>2013</copyright-year><copyright-holder>Stanton et al</copyright-holder><license><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><abstract><p>Vector control, including the use of bed nets, is recommended as a possible strategy for eliminating lymphatic filariasis (LF) in post-conflict countries such as the Democratic Republic of Congo (DRC). This study examined the geographical factors that influence bed net ownership in DRC in order to identify hard-to-reach communities that need to be better targeted. In particular, urban/rural differences and the influence of population density, proximity to cities and health facilities, plus access to major transport networks were investigated. Demographic and Health Survey geo-referenced cluster level data were used to map bed net coverage (proportion of households with at least one of any type of bed net or at least one insecticide-treated net (ITN)), and ITN density (ITNs per person) for 260 clusters. Bivariate and multiple logistic or Poisson regression analyses were used to determine significant relationships. Overall, bed net (30%) and ITN (9%) coverage were very low with significant differences found between urban and rural clusters. In rural clusters, ITN coverage/density was positively correlated with population density (r = 0.25, 0.27 respectively, p<0.01), and negatively with the distance to the two largest cities, Kinshasa or Lubumbashi (r = −0.28, −0.30 respectively, p<0.0001). Further, ownership was significantly negatively correlated with distance to primary national roads and railways (all three measures), distance to main rivers (any bed net only) and distance to the nearest health facility (ITNs only). Logistic and Poisson regression models fitted to the rural cluster data indicated that, after controlling for measured covariates, ownership levels in the Bas-Congo province close to Kinshasa were much larger than that of other provinces. This was most noticeable when considering ITN coverage (odds ratio: 5.3, 95% CI: 3.67–7.70). This analysis provides key insights into the barriers of bed net ownership, which will help inform both LF and malaria bed net distribution campaigns as part of an integrated vector management strategy.</p></abstract><funding-group><funding-statement>The study was supported through a grant from the Department for International Development (DFID) and GlaxoSmithKline (GSK) for research on the elimination of lymphatic filariasis. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><page-count count="11"></page-count></counts></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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