Mobile HIV Screening in Cape Town, South Africa: Clinical Impact, Cost and Cost-Effectiveness
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{"title"=>"Mobile HIV screening in Cape Town, South Africa: Clinical impact, cost and cost-effectiveness", "type"=>"journal", "authors"=>[{"first_name"=>"Ingrid V.", "last_name"=>"Bassett", "scopus_author_id"=>"7003499474"}, {"first_name"=>"Darshini", "last_name"=>"Govindasamy", "scopus_author_id"=>"36494578000"}, {"first_name"=>"Alison S.", "last_name"=>"Erlwanger", "scopus_author_id"=>"55838410000"}, {"first_name"=>"Emily P.", "last_name"=>"Hyle", "scopus_author_id"=>"8634799500"}, {"first_name"=>"Katharina", "last_name"=>"Kranzer", "scopus_author_id"=>"23008694200"}, {"first_name"=>"Nienke", "last_name"=>"Van Schaik", "scopus_author_id"=>"36949783400"}, {"first_name"=>"Farzad", "last_name"=>"Noubary", "scopus_author_id"=>"7801418327"}, {"first_name"=>"A. David", "last_name"=>"Paltiel", "scopus_author_id"=>"7004306826"}, {"first_name"=>"Robin", "last_name"=>"Wood", "scopus_author_id"=>"7404053384"}, {"first_name"=>"Rochelle P.", "last_name"=>"Walensky", "scopus_author_id"=>"6602540593"}, {"first_name"=>"Elena", "last_name"=>"Losina", "scopus_author_id"=>"7003799126"}, {"first_name"=>"Linda Gail", "last_name"=>"Bekker", "scopus_author_id"=>"7003924915"}, {"first_name"=>"Kenneth A.", "last_name"=>"Freedberg", "scopus_author_id"=>"7004947755"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84899887387", "doi"=>"10.1371/journal.pone.0085197", "sgr"=>"84899887387", "isbn"=>"1932-6203", "pmid"=>"24465503", "issn"=>"19326203", "pui"=>"373020732"}, "id"=>"81c3888f-edb3-3a81-9bd5-9a1afed8bfe3", "abstract"=>"BACKGROUND: Mobile HIV screening may facilitate early HIV diagnosis. Our objective was to examine the cost-effectiveness of adding a mobile screening unit to current medical facility-based HIV testing in Cape Town, South Africa.\\n\\nMETHODS AND FINDINGS: We used the Cost Effectiveness of Preventing AIDS Complications International (CEPAC-I) computer simulation model to evaluate two HIV screening strategies in Cape Town: 1) medical facility-based testing (the current standard of care) and 2) addition of a mobile HIV-testing unit intervention in the same community. Baseline input parameters were derived from a Cape Town-based mobile unit that tested 18,870 individuals over 2 years: prevalence of previously undiagnosed HIV (6.6%), mean CD4 count at diagnosis (males 423/µL, females 516/µL), CD4 count-dependent linkage to care rates (males 31%-58%, females 49%-58%), mobile unit intervention cost (includes acquisition, operation and HIV test costs, $29.30 per negative result and $31.30 per positive result). We conducted extensive sensitivity analyses to evaluate input uncertainty. Model outcomes included site of HIV diagnosis, life expectancy, medical costs, and the incremental cost-effectiveness ratio (ICER) of the intervention compared to medical facility-based testing. We considered the intervention to be \"very cost-effective\" when the ICER was less than South Africa's annual per capita Gross Domestic Product (GDP) ($8,200 in 2012). We projected that, with medical facility-based testing, the discounted (undiscounted) HIV-infected population life expectancy was 132.2 (197.7) months; this increased to 140.7 (211.7) months with the addition of the mobile unit. The ICER for the mobile unit was $2,400/year of life saved (YLS). Results were most sensitive to the previously undiagnosed HIV prevalence, linkage to care rates, and frequency of HIV testing at medical facilities.\\n\\nCONCLUSION: The addition of mobile HIV screening to current testing programs can improve survival and be very cost-effective in South Africa and other resource-limited settings, and should be a priority.", "link"=>"http://www.mendeley.com/research/mobile-hiv-screening-cape-town-south-africa-clinical-impact-cost-costeffectiveness", "reader_count"=>58, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>3, "Librarian"=>1, "Student > Doctoral Student"=>2, "Researcher"=>7, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>6, "Student > Master"=>11, "Other"=>4, "Student > Bachelor"=>7, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>3, "Librarian"=>1, "Student > Doctoral Student"=>2, "Researcher"=>7, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>6, "Student > Master"=>11, "Other"=>4, "Student > Bachelor"=>7, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Nursing and Health Professions"=>6, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>22, "Agricultural and Biological Sciences"=>3, "Arts and Humanities"=>1, "Business, Management and Accounting"=>2, "Social Sciences"=>11, "Computer Science"=>3, "Economics, Econometrics and Finance"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>22}, "Social Sciences"=>{"Social Sciences"=>11}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Computer Science"=>{"Computer Science"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>6}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"United States"=>1, "United Kingdom"=>1, "South Africa"=>1}, "group_count"=>5}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1355650", "https://ndownloader.figshare.com/files/1355651", "https://ndownloader.figshare.com/files/1355652"], "description"=>"<div><p>Background</p><p>Mobile HIV screening may facilitate early HIV diagnosis. Our objective was to examine the cost-effectiveness of adding a mobile screening unit to current medical facility-based HIV testing in Cape Town, South Africa.</p><p>Methods and Findings</p><p>We used the Cost Effectiveness of Preventing AIDS Complications International (CEPAC-I) computer simulation model to evaluate two HIV screening strategies in Cape Town: 1) medical facility-based testing (the current standard of care) and 2) addition of a mobile HIV-testing unit intervention in the same community. Baseline input parameters were derived from a Cape Town-based mobile unit that tested 18,870 individuals over 2 years: prevalence of previously undiagnosed HIV (6.6%), mean CD4 count at diagnosis (males 423/µL, females 516/µL), CD4 count-dependent linkage to care rates (males 31%–58%, females 49%–58%), mobile unit intervention cost (includes acquisition, operation and HIV test costs, $29.30 per negative result and $31.30 per positive result). We conducted extensive sensitivity analyses to evaluate input uncertainty. Model outcomes included site of HIV diagnosis, life expectancy, medical costs, and the incremental cost-effectiveness ratio (ICER) of the intervention compared to medical facility-based testing. We considered the intervention to be “very cost-effective” when the ICER was less than South Africa's annual <i>per capita</i> Gross Domestic Product (GDP) ($8,200 in 2012). We projected that, with medical facility-based testing, the discounted (undiscounted) HIV-infected population life expectancy was 132.2 (197.7) months; this increased to 140.7 (211.7) months with the addition of the mobile unit. The ICER for the mobile unit was $2,400/year of life saved (YLS). Results were most sensitive to the previously undiagnosed HIV prevalence, linkage to care rates, and frequency of HIV testing at medical facilities.</p><p>Conclusion</p><p>The addition of mobile HIV screening to current testing programs can improve survival and be very cost-effective in South Africa and other resource-limited settings, and should be a priority.</p></div>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "cape"], "article_id"=>908137, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0085197.s001", "https://dx.doi.org/10.1371/journal.pone.0085197.s002", "https://dx.doi.org/10.1371/journal.pone.0085197.s003"], "stats"=>{"downloads"=>8, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mobile_HIV_Screening_in_Cape_Town_South_Africa_Clinical_Impact_Cost_and_Cost_Effectiveness_/908137", "title"=>"Mobile HIV Screening in Cape Town, South Africa: Clinical Impact, Cost and Cost-Effectiveness", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-01-22 03:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355648"], "description"=>"*<p>Incremental cost-effectiveness ratios <1× South African <i>per capita</i> gross domestic product ($8,200) considered very cost-effective based on WHO suggestions <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085197#pone.0085197-WHO1\" target=\"_blank\">[28]</a>. Costs in 2012 US$. Discounted at 3% per year (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085197#s2\" target=\"_blank\">methods</a>). YLS: years of life saved.</p>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "outcomes", "cost-effectiveness", "cape"], "article_id"=>908135, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085197.t002", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_outcomes_and_cost_effectiveness_of_mobile_unit_HIV_testing_in_Cape_Town_South_Africa_/908135", "title"=>"Model outcomes and cost-effectiveness of mobile unit HIV testing in Cape Town, South Africa.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-22 03:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355649"], "description"=>"*<p>Statistically significant difference between males and females.</p>†<p>Parameter derived and/or calculated from reference data.</p>‡<p>Comprising of one nurse practitioner ($84,200), one registered nurse ($71,100), three counselors ($47,500), one educator ($1,200) and one nurse practitioner at 20% time ($12,200).</p>§<p>Made up of one driver ($27,100), one project manager ($152,300), one data capturer/administrator ($22,000), diesel ($7,500) and general maintenance ($900).</p>∥<p>Assumed that van could be resold after 2 years of use.</p>¶<p>Costs include initial and confirmatory HIV test, staff salaries, and space in a voluntary counseling and testing site.</p><p>SD: standard deviation; POC: point-of-care; ART: antiretroviral therapy; WHO: World Health Organization; TB: tuberculosis.</p>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "ranges", "examined", "cape"], "article_id"=>908136, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085197.t001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_base_case_input_parameters_and_sensitivity_analyses_ranges_examined_for_an_analysis_of_a_mobile_HIV_testing_unit_Cape_Town_South_Africa_/908136", "title"=>"Summary of base case input parameters and sensitivity analyses ranges examined for an analysis of a mobile HIV testing unit Cape Town, South Africa.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-22 03:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355647"], "description"=>"<p>This represents the total undiscounted costs for the cohort of 18,870 for HIV-related costs over the first 2 years, to be incurred by the Western Cape Department of Health. For both strategies HIV-related costs are comprised of HIV screening, routine CD4 and HIV RNA monitoring, ART and prophylaxis, and HIV-related inpatient and outpatient costs. Costs are ×1,000 USD. HIV: human immunodeficiency virus, ART: antiretroviral therapy.</p>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "hiv-related", "cohort", "costs", "years", "facility-based"], "article_id"=>908134, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085197.g004", "stats"=>{"downloads"=>2, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_HIV_related_cohort_costs_over_initial_2_years_in_facility_based_and_mobile_intervention_strategies_/908134", "title"=>"Total HIV-related cohort costs over initial 2 years in facility-based and mobile intervention strategies.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355644"], "description"=>"<p>The charts display the proportion of HIV-infected individuals linked to care with the medical facility-based strategy, and the mobile unit intervention strategy. HIV: human immunodeficiency virus, OI: Opportunistic Infection.</p>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "mechanisms", "linkage", "cape"], "article_id"=>908131, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085197.g001", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_derived_mechanisms_of_HIV_linkage_in_Cape_Town_South_Africa_/908131", "title"=>"Model-derived mechanisms of HIV linkage in Cape Town, South Africa.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355646"], "description"=>"<p>Prevalence of undiagnosed HIV is varied on the horizontal axis and linkage to care on the vertical axis. Figure a) represents the base case medical facility-based program HIV testing frequency of once every 4 years. Figure b) represents annual medical facility-based program HIV testing. Light gray represents scenarios with an incremental cost-effectiveness ratio (ICER) <1× South African <i>per capita</i> gross domestic product ($8,200), dark gray represents scenarios with an ICER $8,200/YLS to $24,600/YLS and black represents scenarios with an ICER >$24,600/YLS. HIV: human immunodeficiency virus, ICER: incremental cost-effectiveness ratio.</p>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "prevalence", "linkage", "facility-based"], "article_id"=>908133, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085197.g003", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multi_way_sensitivity_analyses_on_prevalence_of_HIV_linkage_to_care_and_facility_based_HIV_testing_frequency_/908133", "title"=>"Multi-way sensitivity analyses on prevalence of HIV, linkage to care and facility-based HIV testing frequency.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355645"], "description"=>"<p>The bar graphs shows the proportion (out of the initial 1,240 HIV-infected population) at 5 years who are alive, diagnosed, linked to and retained in care, are on ART, and are HIV RNA suppressed on ART. HIV: human immunodeficiency virus, RNA: ribonucleic acid, ART: antiretroviral therapy.</p>", "links"=>[], "tags"=>["Infectious diseases", "Sexually transmitted diseases", "aids", "Viral diseases", "hiv", "HIV diagnosis and management", "Non-clinical medicine", "Health economics", "Cost effectiveness", "Public health", "Health screening", "Economics", "Cost-effectiveness analysis", "hiv-infected", "individuals", "cape", "years"], "article_id"=>908132, "categories"=>["Medicine", "Sociology"], "users"=>["Ingrid V. Bassett", "Darshini Govindasamy", "Alison S. Erlwanger", "Emily P. Hyle", "Katharina Kranzer", "Nienke van Schaik", "Farzad Noubary", "A. David Paltiel", "Robin Wood", "Rochelle P. Walensky", "Elena Losina", "Linda-Gail Bekker", "Kenneth A. Freedberg"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085197.g002", "stats"=>{"downloads"=>2, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_derived_survival_and_engagement_in_care_of_HIV_infected_individuals_in_Cape_Town_at_5_years_from_the_start_of_observation_/908132", "title"=>"Model-derived survival and engagement in care of HIV-infected individuals in Cape Town at 5 years from the start of observation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:16:27"}

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