A Surprising Prevention Success: Why Did the HIV Epidemic Decline in Zimbabwe?
Publication Date
February 08, 2011
Journal
PLOS Medicine
Authors
Daniel T. Halperin, Owen Mugurungi, Timothy B. Hallett, Backson Muchini, et al
Volume
8
Issue
2
Pages
e1000414
DOI
https://dx.plos.org/10.1371/journal.pmed.1000414
Publisher URL
http://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.1000414
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/21346807
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3035617
Europe PMC
http://europepmc.org/abstract/MED/21346807
Web of Science
000287657600008
Scopus
79952268522
Mendeley
http://www.mendeley.com/research/surprising-prevention-success-hiv-epidemic-decline-zimbabwe
Events
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Mendeley | Further Information

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CrossRef

Scopus | Further Information

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  • {"files"=>["https://ndownloader.figshare.com/files/799610"], "description"=>"<p>Form(s) of evidence supporting conclusion: M, epidemiological modeling; QN, survey data; P, program data; QL, qualitative data. See <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414.s005\" target=\"_blank\">Text S1</a> for details.</p>a<p>Extent to which changes in the factor concerned can reduce HIV transmission <i>at the population level</i>, as measured and modeled in scientific studies [M & QN].</p>b<p>Extent to which changes in the given behavioral or biological determinant (by population sub-group) have occurred as observed in longitudinal surveys and/or program data.</p>c<p>Extent to which the changes in risk behavior etc. occurred during the period of most rapid reduction in risk as determined by the epidemiological modeling assessment (i.e., about 1999–2003).</p>d<p>Transmission probability could be affected by, for example, levels of blood safety, prevalence of other sexually transmitted infections, HIV medications, or male circumcision.</p>", "links"=>[], "tags"=>["proximate", "causes", "hiv"], "article_id"=>469976, "categories"=>["Computational Biology", "Medicine", "Cancer", "Information And Computing Sciences"], "users"=>["Daniel T. Halperin", "Owen Mugurungi", "Timothy B. Hallett", "Backson Muchini", "Bruce Campbell", "Tapuwa Magure", "Clemens Benedikt", "Simon Gregson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000414.t001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contributions_of_proximate_causes_to_the_HIV_decline_in_Zimbabwe_/469976", "title"=>"Contributions of proximate causes to the HIV decline in Zimbabwe.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-02-08 02:46:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/399940", "https://ndownloader.figshare.com/files/399981", "https://ndownloader.figshare.com/files/400018", "https://ndownloader.figshare.com/files/400043", "https://ndownloader.figshare.com/files/400082", "https://ndownloader.figshare.com/files/400150"], "description"=>"A Surprising Prevention Success: Why Did the HIV Epidemic Decline in Zimbabwe?", "links"=>[], "tags"=>["did", "hiv"], "article_id"=>139002, "categories"=>["Biological Sciences", "Medicine", "Cancer", "Information And Computing Sciences"], "users"=>["Daniel T. Halperin", "Owen Mugurungi", "Timothy B. Hallett", "Backson Muchini", "Bruce Campbell", "Tapuwa Magure", "Clemens Benedikt", "Simon Gregson"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1000414.s001", "https://dx.doi.org/10.1371/journal.pmed.1000414.s002", "https://dx.doi.org/10.1371/journal.pmed.1000414.s003", "https://dx.doi.org/10.1371/journal.pmed.1000414.s004", "https://dx.doi.org/10.1371/journal.pmed.1000414.s005", "https://dx.doi.org/10.1371/journal.pmed.1000414.s006"], "stats"=>{"downloads"=>30, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Surprising_Prevention_Success_Why_Did_the_HIV_Epidemic_Decline_in_Zimbabwe_/139002", "title"=>"A Surprising Prevention Success: Why Did the HIV Epidemic Decline in Zimbabwe?", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-02-08 02:30:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/799478"], "description"=>"<p>Estimates are for men aged 17–43 years (in Botswana, ages 14–48 years) in the years 2000–2006, chosen to maximize the overlap of temporal range between surveys and the age groups that contribute most to HIV transmission. All those with any secondary education were counted as having secondary education. “Married” category does not include those who were cohabiting but not married. Sources: DHS surveys performed in the years indicated in the legend, with the exception of Botswana (using the methodologically similar Botswana AIDS Impact Survey, 2001).</p>", "links"=>[], "tags"=>["men", "areas", "african"], "article_id"=>469842, "categories"=>["Computational Biology", "Medicine", "Cancer", "Information And Computing Sciences"], "users"=>["Daniel T. Halperin", "Owen Mugurungi", "Timothy B. Hallett", "Backson Muchini", "Bruce Campbell", "Tapuwa Magure", "Clemens Benedikt", "Simon Gregson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000414.g002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Levels_of_marriage_and_secondary_education_among_men_in_urban_areas_in_eight_southern_African_countries_/469842", "title"=>"Levels of marriage and secondary education among men in urban areas in eight southern African countries.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-02-08 02:44:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/799651"], "description"=>"<p>Form(s) of evidence supporting conclusion: M, epidemiological modeling; QN, survey or other quantitative data; P, program data; QL, qualitative data. See <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414.s005\" target=\"_blank\">Text S1</a> for details.</p>a<p>Extent to which change in the factor concerned is likely to effect behavior change, and thereby reduce HIV transmission at the population level.</p>b<p>Extent to which the intervention was scaled-up during the period of most rapid reduction in risk as determined by the epidemiological modeling assessment (i.e., about 1999–2003).</p>c<p>Behavior change programs as a whole probably contributed to reducing HIV risk but, given the limitations in the available data, it was not possible to isolate the contributions (if any) of each individual program area.</p><p>“?” indicates greater uncertainty.</p>", "links"=>[], "tags"=>["factors", "programs", "hiv"], "article_id"=>470014, "categories"=>["Computational Biology", "Medicine", "Cancer", "Information And Computing Sciences"], "users"=>["Daniel T. Halperin", "Owen Mugurungi", "Timothy B. Hallett", "Backson Muchini", "Bruce Campbell", "Tapuwa Magure", "Clemens Benedikt", "Simon Gregson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000414.t002", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Contributions_of_underlying_factors_and_programs_to_the_HIV_decline_in_Zimbabwe_/470014", "title"=>"Contributions of underlying factors and programs to the HIV decline in Zimbabwe.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-02-08 00:00:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/799396"], "description"=>"<p>(A) Estimated trends in HIV prevalence, incidence, and AIDS deaths using a mathematical model of HIV transmission fitted to antenatal and household-based estimates of HIV prevalence, 1980–2010. HIV incidence peaks around 1991 and declines as part of the natural course of epidemic maturation; incidence decline is accelerated between about 1999 and 2003 due to reductions in sexual risk behavior <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414-Hallett2\" target=\"_blank\">[14]</a>. (As has been noted <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414-Hallett2\" target=\"_blank\">[14]</a>, incidence declined a little earlier in urban areas. The model suggests behavior change could have continued partly into 2004 in rural areas, but the majority of changes were concentrated within the 1999–2003 period <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414-Hallett2\" target=\"_blank\">[14]</a>.) (B) Changes in key indicators of sexual partnership formation taken from the nationally representative DHSs (1999 and 2005/6) and surveys in Manicaland, rural eastern Zimbabwe (1998–2000 and 2001–2003) <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414-Gregson1\" target=\"_blank\">[13]</a>,<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000414#pmed.1000414-Gregson2\" target=\"_blank\">[16]</a>.</p>", "links"=>[], "tags"=>["epidemiological"], "article_id"=>469759, "categories"=>["Computational Biology", "Medicine", "Cancer", "Information And Computing Sciences"], "users"=>["Daniel T. Halperin", "Owen Mugurungi", "Timothy B. Hallett", "Backson Muchini", "Bruce Campbell", "Tapuwa Magure", "Clemens Benedikt", "Simon Gregson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000414.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_epidemiological_findings_/469759", "title"=>"Summary of epidemiological findings.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-02-08 02:42:39"}

PMC Usage Stats | Further Information

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