The Cost and Impact of Scaling Up Pre-exposure Prophylaxis for HIV Prevention: A Systematic Review of Cost-Effectiveness Modelling Studies
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{"title"=>"The Cost and Impact of Scaling Up Pre-exposure Prophylaxis for HIV Prevention: A Systematic Review of Cost-Effectiveness Modelling Studies", "type"=>"generic", "authors"=>[{"first_name"=>"Gabriela B.", "last_name"=>"Gomez", "scopus_author_id"=>"13410760100"}, {"first_name"=>"Annick", "last_name"=>"Borquez", "scopus_author_id"=>"25649124000"}, {"first_name"=>"Kelsey K.", "last_name"=>"Case", "scopus_author_id"=>"36149097400"}, {"first_name"=>"Ana", "last_name"=>"Wheelock", "scopus_author_id"=>"54891662200"}, {"first_name"=>"Anna", "last_name"=>"Vassall", "scopus_author_id"=>"57195727373"}, {"first_name"=>"Catherine", "last_name"=>"Hankins", "scopus_author_id"=>"35832461700"}], "year"=>2013, "source"=>"PLoS Medicine", "identifiers"=>{"sgr"=>"84875470987", "doi"=>"10.1371/journal.pmed.1001401", "issn"=>"15491277", "pui"=>"368602100", "isbn"=>"10.1371/journal.pmed.1001401", "pmid"=>"23554579", "scopus"=>"2-s2.0-84875470987"}, "id"=>"699f5f86-597c-37d4-bdb4-816ab74cccdf", "abstract"=>"BACKGROUND: Cost-effectiveness studies inform resource allocation, strategy, and policy development. However, due to their complexity, dependence on assumptions made, and inherent uncertainty, synthesising, and generalising the results can be difficult. We assess cost-effectiveness models evaluating expected health gains and costs of HIV pre-exposure prophylaxis (PrEP) interventions.\\n\\nMETHODS AND FINDINGS: We conducted a systematic review comparing epidemiological and economic assumptions of cost-effectiveness studies using various modelling approaches. The following databases were searched (until January 2013): PubMed/Medline, ISI Web of Knowledge, Centre for Reviews and Dissemination databases, EconLIT, and region-specific databases. We included modelling studies reporting both cost and expected impact of a PrEP roll-out. We explored five issues: prioritisation strategies, adherence, behaviour change, toxicity, and resistance. Of 961 studies retrieved, 13 were included. Studies modelled populations (heterosexual couples, men who have sex with men, people who inject drugs) in generalised and concentrated epidemics from Southern Africa (including South Africa), Ukraine, USA, and Peru. PrEP was found to have the potential to be a cost-effective addition to HIV prevention programmes in specific settings. The extent of the impact of PrEP depended upon assumptions made concerning cost, epidemic context, programme coverage, prioritisation strategies, and individual-level adherence. Delivery of PrEP to key populations at highest risk of HIV exposure appears the most cost-effective strategy. Limitations of this review include the partial geographical coverage, our inability to perform a meta-analysis, and the paucity of information available exploring trade-offs between early treatment and PrEP.\\n\\nCONCLUSIONS: Our review identifies the main considerations to address in assessing cost-effectiveness analyses of a PrEP intervention--cost, epidemic context, individual adherence level, PrEP programme coverage, and prioritisation strategy. Cost-effectiveness studies indicating where resources can be applied for greatest impact are essential to guide resource allocation decisions; however, the results of such analyses must be considered within the context of the underlying assumptions made. Please see later in the article for the Editors' Summary.", "link"=>"http://www.mendeley.com/research/cost-impact-scaling-up-preexposure-prophylaxis-hiv-prevention-systematic-review-costeffectiveness-mo-13", "reader_count"=>92, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Librarian"=>1, "Researcher"=>16, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>4, "Student > Master"=>23, "Other"=>8, "Student > Bachelor"=>10, "Lecturer > Senior Lecturer"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Librarian"=>1, "Researcher"=>16, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>15, "Student > Postgraduate"=>4, "Student > Master"=>23, "Other"=>8, "Student > Bachelor"=>10, "Lecturer > Senior Lecturer"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>9, "Nursing and Health Professions"=>8, "Mathematics"=>3, "Agricultural and Biological Sciences"=>5, "Medicine and Dentistry"=>38, "Philosophy"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Business, Management and Accounting"=>3, "Psychology"=>8, "Social Sciences"=>10, "Decision Sciences"=>1, "Economics, Econometrics and Finance"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>38}, "Social Sciences"=>{"Social Sciences"=>10}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Psychology"=>{"Psychology"=>8}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>5}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>8}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>3}, "Mathematics"=>{"Mathematics"=>3}, "Unspecified"=>{"Unspecified"=>9}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"United States"=>3, "Nigeria"=>1, "India"=>1}, "group_count"=>20}

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  • {"files"=>["https://ndownloader.figshare.com/files/1006897"], "description"=>"<p>Thresholds used to determine cost-effectiveness, based on World Bank database <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001401#pmed.1001401-World1\" target=\"_blank\">[23]</a>. Bold-black signifies an estimate is cost-effective or very cost-effective with regards to the country-specific threshold.</p>a<p>For South Africa, an intervention is considered very cost-effective at a threshold of less than 1× GDP per capita, US$8,070.</p>b<p>In Alistar et al., several scenarios were considered for ART recruitment rates of 25%, 50%, 75%, and 100% in addition to the 40% status quo coverage as per guidelines and following universal access.</p>c<p>In Cremin et al., several scenarios were considered for ART coverage. ART200: coverage of ART in HIV-infected people starting at CD4 count of <200 cells/ml; ART350: coverage of ART in HIV-infected people starting at CD4 count of <350 cells/ml; universal ART: coverage of ART in HIV-infected people starting at any CD4 count level.</p>d<p>In Desai et al., the authors considered three effectiveness mechanisms: basic, adherence-dependent, and exposure-dependent.</p>e<p>For USA, an intervention is considered very cost-effective at a threshold of less than 1× GDP per capita, US$48,442.</p>f<p>For USA, an intervention is considered cost-effective between 1× GDP per capita, US$48,442 and 3× GDP per capita, US$145,326.</p>g<p>For Peru, an intervention is considered very cost-effective at a threshold of less than 1× GDP per capita, US$ US$6,009.</p>h<p>For Ukraine, an intervention is considered very cost-effective at a threshold of less than 1× GDP per capita, US$3,615.</p>i<p>For Ukraine, an intervention is considered cost-effective between 1× GDP per capita, US$3,615 and 3× GDP per capita, US$10,845.</p><p>cov., coverage; CS, cost saving; freq, frequency; MC, male circumcision; MMT, methadone maintenance treatment; QoL, quality of life; resist., resistance.</p>", "links"=>[], "tags"=>["estimates"], "article_id"=>667528, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001401.t005", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cost_effectiveness_estimates_by_scenario_/667528", "title"=>"Cost-effectiveness estimates by scenario.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-12 02:05:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/1006883"], "description"=>"<p>Study type refers to the type of model and the inclusion of risk heterogeneity in the population modelled. Setting/MoT refers to the geographical setting and the mode of transmission modelled.</p>a<p>Female∶male ratio 1.66, based on data from urban antenatal care attendees in Zambia.</p>b<p>Model initiated at a high prevalence then fitted to Department of Health data.</p>c<p>Two types of couples were defined: (1) lower risk couples based on reported data from the Partners in Prevention HSV/HIV Transmission Study <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001401#pmed.1001401-Lingappa1\" target=\"_blank\">[49]</a>, and (2) couples at a higher risk reflecting a higher incidence. “Partners in Prevention” assumptions: incidence low (1.8/100 person-years at risk, high condom use); “more typical couples” assumptions: 50% of serodiscordant couples involved HIV-1 infected men. Compared to the partners in prevention cohort: condom use within the stable partnership was reduced by 25%, 50% more of the HIV-1 uninfected partners in couples had external partners, and frequency of unprotected sex with external partners was doubled.</p>d<p>Very high risk was defined as a participant reporting unprotected sex in the last 6 mo or in exchange for money or drugs, anonymous sex, ≥5 sexual or needle sharing partners, and/or an STI diagnosis in the last 6 mo.</p>e<p>The authors run the model separately for low risk and high risk populations. Therefore PrEP use in one group does not have an impact on the other (the mixing is considered totally assortative).</p><p>IDU, injection drug use; MMSM, men who mostly have sex with men; MMSW, men who mostly have sex with women; n/a, not applicable; SW, sex worker;</p><p>Trans, transgender or trans-sexual; USA (NYC), United States of America (New York City).</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>667509, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001401.t001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_design_/667509", "title"=>"Study design.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-12 02:05:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/1006864"], "description"=>"a<p>Period trying to conceive and while pregnant.</p>b<p>The authors also considered a scenario of 2.5% coverage, but explored results for the 25% scenario.</p>c<p>Defined as those with more than five partners per y.</p>d<p>Coverage includes only people fully adherent to PrEP.</p><p>init, initiation; MC, male circumcision; MMT, methadone maintenance treatment; n/a, not applicable.</p>", "links"=>[], "tags"=>["programmes"], "article_id"=>667490, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001401.t002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Alternative_programmes_compared_/667490", "title"=>"Alternative programmes compared.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-12 02:04:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/1006844"], "description"=>"a<p>Coverage includes only people fully adherent to PrEP.</p><p>IDU, injection drug users; init., initiation; MC, male circumcision; n/a, not applicable.</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>667472, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001401.t003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Impact_assumptions_/667472", "title"=>"Impact: assumptions.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-12 02:04:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/985179", "https://ndownloader.figshare.com/files/985180", "https://ndownloader.figshare.com/files/985181", "https://ndownloader.figshare.com/files/985183"], "description"=>"<div><p>Background</p><p>Cost-effectiveness studies inform resource allocation, strategy, and policy development. However, due to their complexity, dependence on assumptions made, and inherent uncertainty, synthesising, and generalising the results can be difficult. We assess cost-effectiveness models evaluating expected health gains and costs of HIV pre-exposure prophylaxis (PrEP) interventions.</p> <p>Methods and Findings</p><p>We conducted a systematic review comparing epidemiological and economic assumptions of cost-effectiveness studies using various modelling approaches. The following databases were searched (until January 2013): PubMed/Medline, ISI Web of Knowledge, Centre for Reviews and Dissemination databases, EconLIT, and region-specific databases. We included modelling studies reporting both cost and expected impact of a PrEP roll-out. We explored five issues: prioritisation strategies, adherence, behaviour change, toxicity, and resistance. Of 961 studies retrieved, 13 were included. Studies modelled populations (heterosexual couples, men who have sex with men, people who inject drugs) in generalised and concentrated epidemics from Southern Africa (including South Africa), Ukraine, USA, and Peru. PrEP was found to have the potential to be a cost-effective addition to HIV prevention programmes in specific settings. The extent of the impact of PrEP depended upon assumptions made concerning cost, epidemic context, programme coverage, prioritisation strategies, and individual-level adherence. Delivery of PrEP to key populations at highest risk of HIV exposure appears the most cost-effective strategy. Limitations of this review include the partial geographical coverage, our inability to perform a meta-analysis, and the paucity of information available exploring trade-offs between early treatment and PrEP.</p> <p>Conclusions</p><p>Our review identifies the main considerations to address in assessing cost-effectiveness analyses of a PrEP intervention—cost, epidemic context, individual adherence level, PrEP programme coverage, and prioritisation strategy. Cost-effectiveness studies indicating where resources can be applied for greatest impact are essential to guide resource allocation decisions; however, the results of such analyses must be considered within the context of the underlying assumptions made.</p> <p> <i>Please see later in the article for the Editors' Summary</i></p> </div>", "links"=>[], "tags"=>["scaling", "pre-exposure", "prophylaxis", "hiv", "systematic", "cost-effectiveness", "studies"], "article_id"=>650589, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001401.s001", "https://dx.doi.org/10.1371/journal.pmed.1001401.s002", "https://dx.doi.org/10.1371/journal.pmed.1001401.s003", "https://dx.doi.org/10.1371/journal.pmed.1001401.s004"], "stats"=>{"downloads"=>46, "page_views"=>26, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/The_Cost_and_Impact_of_Scaling_Up_Pre_exposure_Prophylaxis_for_HIV_Prevention_A_Systematic_Review_of_Cost_Effectiveness_Modelling_Studies__/650589", "title"=>"The Cost and Impact of Scaling Up Pre-exposure Prophylaxis for HIV Prevention: A Systematic Review of Cost-Effectiveness Modelling Studies", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-03-13 09:41:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/985178"], "description"=>"<p>Region-specific databases can be accessed as follows: African Index Medicus, <a href=\"http://indexmedicus.afro.who.int/\" target=\"_blank\">http://indexmedicus.afro.who.int/</a>; Eastern Mediterranean Literature, <a href=\"http://www.emro.who.int/\" target=\"_blank\">http://www.emro.who.int/</a>; Index Medicus for South-East Asia Region, <a href=\"http://www.hellis.org/\" target=\"_blank\">http://www.hellis.org/</a>; LILACS, Latin America, <a href=\"http://www.bireme.br/iah2/homepagei.htm\" target=\"_blank\">http://www.bireme.br/iah2/homepagei.htm</a>.</p>", "links"=>[], "tags"=>["diagram"], "article_id"=>650588, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001401.g001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_diagram_of_study_selection_/650588", "title"=>"Flow diagram of study selection.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-13 09:41:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/1006918"], "description"=>"<p>approx, approximately; CDC, Centers for Disease Control and Prevention; n/a, not applicable/not available; person-y, person-year; VCT, voluntary counselling and testing.</p>a<p>Assumed.</p>", "links"=>[], "tags"=>["assumptions"], "article_id"=>667543, "categories"=>["Biotechnology"], "users"=>["Gabriela B. Gomez", "Annick Borquez", "Kelsey K. Case", "Ana Wheelock", "Anna Vassall", "Catherine Hankins"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001401.t004", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cost_assumptions_US_in_publication_/667543", "title"=>"Cost: assumptions (US$ in publication).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-12 02:05:43"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"14", "full-text"=>"16", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"15", "full-text"=>"14", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
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  • {"unique-ip"=>"16", "full-text"=>"20", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"17", "full-text"=>"23", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"15", "full-text"=>"18", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"18", "full-text"=>"20", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"21", "full-text"=>"19", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"17", "full-text"=>"18", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"20", "full-text"=>"24", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"25", "full-text"=>"31", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"25", "full-text"=>"25", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"31", "full-text"=>"26", "pdf"=>"13", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"16", "full-text"=>"18", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Immunology", "average_usage"=>[266, 466, 591, 701, 799, 887, 982, 1067, 1155, 1237, 1317, 1395, 1458]}, {"subject_area"=>"/Medicine and health sciences/Epidemiology", "average_usage"=>[263, 452, 568, 671, 758, 847, 921, 1023, 1101, 1187, 1264, 1340, 1394]}, {"subject_area"=>"/Medicine and health sciences/Immunology", "average_usage"=>[262, 463, 587, 693, 790, 882, 965, 1051, 1135, 1218, 1300, 1376, 1438]}, {"subject_area"=>"/Medicine and health sciences/Public and occupational health", "average_usage"=>[291, 491, 610, 723, 817, 906, 991, 1071, 1153, 1238, 1324, 1411, 1478]}, {"subject_area"=>"/Social sciences", "average_usage"=>[289, 475, 593, 703, 805, 902, 990, 1078, 1158, 1250, 1336, 1417, 1482]}]}
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