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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Millennium development goal 6 and HIV infection in Zambia: what can we learn from successive household surveys?</title><author><name sortKey="Kandala, Ngianga Bakwin" sort="Kandala, Ngianga Bakwin" uniqKey="Kandala N" first="Ngianga-Bakwin" last="Kandala">Ngianga-Bakwin Kandala</name></author><author><name sortKey="Brodish, Paul" sort="Brodish, Paul" uniqKey="Brodish P" first="Paul" last="Brodish">Paul Brodish</name></author><author><name sortKey="Buckner, Bates" sort="Buckner, Bates" uniqKey="Buckner B" first="Bates" last="Buckner">Bates Buckner</name></author><author><name sortKey="Foster, Susan" sort="Foster, Susan" uniqKey="Foster S" first="Susan" last="Foster">Susan Foster</name></author><author><name sortKey="Madise, Nyovani" sort="Madise, Nyovani" uniqKey="Madise N" first="Nyovani" last="Madise">Nyovani Madise</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">21099671</idno><idno type="pmc">3145216</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3145216</idno><idno type="RBID">PMC:3145216</idno><idno type="doi">10.1097/QAD.0b013e328340fe0f</idno><date when="2011">2011</date><idno type="wicri:Area/Pmc/Corpus">001201</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001201</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Millennium development goal 6 and HIV infection in Zambia: what can we learn from successive household surveys?</title><author><name sortKey="Kandala, Ngianga Bakwin" sort="Kandala, Ngianga Bakwin" uniqKey="Kandala N" first="Ngianga-Bakwin" last="Kandala">Ngianga-Bakwin Kandala</name></author><author><name sortKey="Brodish, Paul" sort="Brodish, Paul" uniqKey="Brodish P" first="Paul" last="Brodish">Paul Brodish</name></author><author><name sortKey="Buckner, Bates" sort="Buckner, Bates" uniqKey="Buckner B" first="Bates" last="Buckner">Bates Buckner</name></author><author><name sortKey="Foster, Susan" sort="Foster, Susan" uniqKey="Foster S" first="Susan" last="Foster">Susan Foster</name></author><author><name sortKey="Madise, Nyovani" sort="Madise, Nyovani" uniqKey="Madise N" first="Nyovani" last="Madise">Nyovani Madise</name></author></analytic><series><title level="j">AIDS (London, England)</title><idno type="ISSN">0269-9370</idno><idno type="eISSN">1473-5571</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec id="S1"><title>Background</title><p id="P1">Geographic location represents an ecological measure of HIV status and is a strong predictor of HIV prevalence. Given the complex nature of location effects, there is limited understanding of their impact on policies to reduce HIV prevalence.</p></sec><sec sec-type="methods" id="S2"><title>Methods</title><p id="P2">Participants were 3,949 and 10,874 respondents from two consecutive Zambia Demographic and Health Surveys from 2001/7 (mean age for men and women: 30.3 and 27.7 years, HIV prevalence 14.3% in 2001/2002; 30.3 and 28.0 years, HIV prevalence of 14.7% in 2007). A Bayesian geo-additive mixed model based on Markov Chain Monte Carlo techniques was used to map the change in the spatial distribution of HIV/AIDS prevalence at the provincial level during the six-year period, accounting for important risk factors.</p></sec><sec id="S3"><title>Findings</title><p id="P3">Overall HIV/AIDS prevalence changed little over the 6-year period, but the mapping of residual spatial effects at the provincial level suggested different regional patterns. A pronounced change in odds ratios in Lusaka and Copperbelt provinces in 2001/2 and in Lusaka and Central provinces in 2007 were observed following adjustment for spatial autocorrelation. Western province went from a lower prevalence area in 2001 (13.4%) to a higher prevalence area in 2007 (17.3%). Southern province went from the highest prevalence area in 2001 (17.3%) to a lower prevalence area in 2007 (15.9%).</p></sec><sec id="S4"><title>Interpretation</title><p id="P4">Findings from two consecutive surveys corroborate the Zambian government’s effort to achieve MDG 6. The novel finding of increased prevalence in Western province warrants further investigation. Spatially-adjusted provincial-level HIV/AIDS prevalence maps are a useful tool for informing policies to achieve MDG 6 in Zambia.</p></sec></div></front></TEI><pmc article-type="research-article" xml:lang="en"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
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<front><journal-meta><journal-id journal-id-type="nlm-journal-id">8710219</journal-id><journal-id journal-id-type="pubmed-jr-id">1493</journal-id><journal-id journal-id-type="nlm-ta">AIDS</journal-id><journal-title-group><journal-title>AIDS (London, England)</journal-title></journal-title-group><issn pub-type="ppub">0269-9370</issn><issn pub-type="epub">1473-5571</issn></journal-meta><article-meta><article-id pub-id-type="pmid">21099671</article-id><article-id pub-id-type="pmc">3145216</article-id><article-id pub-id-type="doi">10.1097/QAD.0b013e328340fe0f</article-id><article-id pub-id-type="manuscript">NIHMS308292</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Millennium development goal 6 and HIV infection in Zambia: what can we learn from successive household surveys?</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kandala</surname><given-names>Ngianga-Bakwin</given-names></name></contrib><contrib contrib-type="author"><name><surname>Brodish</surname><given-names>Paul</given-names></name></contrib><contrib contrib-type="author"><name><surname>Buckner</surname><given-names>Bates</given-names></name></contrib><contrib contrib-type="author"><name><surname>Foster</surname><given-names>Susan</given-names></name></contrib><contrib contrib-type="author"><name><surname>Madise</surname><given-names>Nyovani</given-names></name></contrib></contrib-group><pub-date pub-type="nihms-submitted"><day>14</day><month>7</month><year>2011</year></pub-date><pub-date pub-type="ppub"><day>2</day><month>1</month><year>2011</year></pub-date><pub-date pub-type="pmc-release"><day>28</day><month>7</month><year>2011</year></pub-date><volume>25</volume><issue>1</issue><fpage>95</fpage><lpage>106</lpage><abstract><sec id="S1"><title>Background</title><p id="P1">Geographic location represents an ecological measure of HIV status and is a strong predictor of HIV prevalence. Given the complex nature of location effects, there is limited understanding of their impact on policies to reduce HIV prevalence.</p></sec><sec sec-type="methods" id="S2"><title>Methods</title><p id="P2">Participants were 3,949 and 10,874 respondents from two consecutive Zambia Demographic and Health Surveys from 2001/7 (mean age for men and women: 30.3 and 27.7 years, HIV prevalence 14.3% in 2001/2002; 30.3 and 28.0 years, HIV prevalence of 14.7% in 2007). A Bayesian geo-additive mixed model based on Markov Chain Monte Carlo techniques was used to map the change in the spatial distribution of HIV/AIDS prevalence at the provincial level during the six-year period, accounting for important risk factors.</p></sec><sec id="S3"><title>Findings</title><p id="P3">Overall HIV/AIDS prevalence changed little over the 6-year period, but the mapping of residual spatial effects at the provincial level suggested different regional patterns. A pronounced change in odds ratios in Lusaka and Copperbelt provinces in 2001/2 and in Lusaka and Central provinces in 2007 were observed following adjustment for spatial autocorrelation. Western province went from a lower prevalence area in 2001 (13.4%) to a higher prevalence area in 2007 (17.3%). Southern province went from the highest prevalence area in 2001 (17.3%) to a lower prevalence area in 2007 (15.9%).</p></sec><sec id="S4"><title>Interpretation</title><p id="P4">Findings from two consecutive surveys corroborate the Zambian government’s effort to achieve MDG 6. The novel finding of increased prevalence in Western province warrants further investigation. Spatially-adjusted provincial-level HIV/AIDS prevalence maps are a useful tool for informing policies to achieve MDG 6 in Zambia.</p></sec></abstract><kwd-group><kwd>MDG 6</kwd><kwd>HIV prevalence</kwd><kwd>geographic location</kwd><kwd>spatial autocorrelation</kwd></kwd-group><funding-group><award-group><funding-source country="United States">National Institute of Child Health & Human Development : NICHD</funding-source><award-id>R24 HD050924-05 || HD</award-id></award-group></funding-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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