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Yan H, Luo Y, Wu H, Chen M, Li S, Tian Z, Zou G, Tang S, Bible PW, Hao Y, Gu J, Han Z, Liu Y. Evolving molecular HIV clusters revealed genotype-specific dynamics in Guangzhou, China (2008-2020). Int J Infect Dis 2024:107218. [PMID: 39181438 DOI: 10.1016/j.ijid.2024.107218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 08/19/2024] [Accepted: 08/19/2024] [Indexed: 08/27/2024] Open
Abstract
OBJECTIVES This study investigated the genotype-specific dynamics of molecular HIV clusters (MHCs) in Guangzhou, China, aiming to enhance HIV control. METHODS HIV pol sequences from people with HIV (PWH) in Guangzhou (2008-2020) were obtained for genotyping and molecular network creation. MHCs were identified and categorized into three types: emerging, growing, or stable. Clustering rates, proportions of cluster types and members within each type were calculated and their trends were assessed using joinpoint regression. RESULTS Among 8,395 PWH, the most prevalent HIV-1 genotypes were CRF07_BC (39.7%) and CRF01_AE (32.6%). The genotype composition has been stable since 2012 (Ps>0.05). The overall clustering rate was 43.3%, with significant variations across genotypes (P<0.001), indicating genotype-specific transmission fitness. Significant declines in overall and genotype-specific clustering rates towards the end of 2020 (Ps<0.05), potentially offer support for HIV control efforts in reducing local infections. The continuously increasing proportions of stable clusters and the gradually decreasing proportions of emerging and growing clusters (either Ps<0.05 or Ps>0.05) suggests a trend towards stable molecular network structure. However, growing clusters exhibited CRF55_01B, CRF07_BC and CRF59_01B dominance that indicate their priority for interventions. CONCLUSIONS The evolving molecular HIV clusters highlight the genotype-specific cluster dynamics, providing fresh insights for enhanced prevention and control strategies.
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Affiliation(s)
- Huanchang Yan
- School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, China; Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yeifei Luo
- Department of AIDS Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Hao Wu
- Department of AIDS Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Mingyu Chen
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Shunming Li
- Department of AIDS Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Zhenming Tian
- School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Guanyang Zou
- School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shixing Tang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Paul W Bible
- Department of Computer Science, DePauw University, Indiana, USA
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Jing Gu
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhigang Han
- Department of AIDS Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China; Institute of Public Health, Guangzhou Medical University & Guangzhou Center for Disease Control and Prevention, China
| | - Yu Liu
- School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, China.
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Banadakoppa Manjappa R, Bhattacharjee P, Shaw SY, Gitonga J, Kioko J, Songok F, Emmanuel F, Arimi P, Musyoki H, Masha RL, Blanchard J. A sub-national HIV epidemic appraisal in Kenya: a new approach for identifying priority geographies, populations and programmes for optimizing coverage for HIV prevention. J Int AIDS Soc 2024; 27 Suppl 2:e26245. [PMID: 38982894 PMCID: PMC11233855 DOI: 10.1002/jia2.26245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 04/04/2024] [Indexed: 07/11/2024] Open
Abstract
INTRODUCTION The HIV Prevention 2025 Roadmap, developed by UNAIDS, recommends the adoption of a precision prevention approach focused on priority populations and geographies. With reduction in new HIV acquisitions in many countries, designing a differentiated HIV prevention response, using a Programme Science approach, based on the understanding of the epidemic and transmission dynamics at a sub-national level, is critical. METHODS To support strategic planning, an epidemic appraisal at the sub-national level across 47 counties, with the 2019 population ranging from 0.14 million in Lamu to 4.40 million in Nairobi City, was conducted in Kenya using several existing data sources. Using 2021 Spectrum/EPP/Naomi model estimates of national and sub-national HIV incidence and prevalence, counties with high HIV incidence and prevalence were identified for geographic prioritization. The size of local key population (KP) networks and HIV prevalence in key and general populations were used to define epidemic typology and prioritize populations for HIV prevention programmes. Analysis of routine programme monitoring data for 2021 was used to assess coverage gaps in HIV prevention programmes, including prevention of vertical transmission, anti-retroviral therapy, KP programmes, adolescent girls and young women programme, and voluntary male medical circumcision programme. RESULTS Ten counties with more than 1000 incident acquisitions in 2021 accounted for 57% of new acquisitions. Twenty-four counties were grouped into the concentrated epidemic type-due to their low prevalence in the general population, high prevalence in KPs and relatively higher density of female sex workers and men who have sex with men populations. Four counties reflected a generalized epidemic, where HIV prevalence was more than 10% and 30%, respectively, among the general and key populations. The remaining 19 counties were classified as having mixed epidemics. Gaps in programmes were identified and counties where these gaps need to be addressed were also prioritized. CONCLUSIONS The HIV burden in Kenya is unevenly distributed and hence the mix of prevention strategies may vary according to the epidemic typology of the county. Prioritization of programmes based not only on disease burden and epidemic typology, but also on the prevailing gaps in coverage for reducing inequities is a key aspect of this appraisal.
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Affiliation(s)
| | - Parinita Bhattacharjee
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
- Partners for Health and Development in AfricaNairobiKenya
| | | | - Joshua Gitonga
- National Syndemic Diseases Control CouncilMinistry of HealthNairobiKenya
| | - Japheth Kioko
- Partners for Health and Development in AfricaNairobiKenya
| | - Franklin Songok
- National AIDS and STI Control ProgrammeMinistry of HealthNairobiKenya
| | - Faran Emmanuel
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
| | - Peter Arimi
- Partners for Health and Development in AfricaNairobiKenya
| | - Helgar Musyoki
- Global Fund to Fight AIDS, Tuberculosis and MalariaGenevaSwitzerland
| | - Ruth Laibon Masha
- National Syndemic Diseases Control CouncilMinistry of HealthNairobiKenya
| | - James Blanchard
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
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McClarty LM, Green K, Leung S, Ejeckam C, Adesina A, Shaw SY, Neufeld B, Isac S, Emmanuel F, Blanchard JF, Aliyu G. Advancing Programme Science approaches to understand gaps in HIV prevention programme coverage for key populations in 12 Nigerian states: findings from the 2020 Integrated Biological and Behavioural Surveillance Survey. J Int AIDS Soc 2024; 27 Suppl 2:e26269. [PMID: 38988042 PMCID: PMC11236907 DOI: 10.1002/jia2.26269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 04/29/2024] [Indexed: 07/12/2024] Open
Abstract
INTRODUCTION Effective HIV prevention programme coverage is necessary to achieve Nigeria's goal of ending the epidemic by 2030. Recent evidence highlights gaps in service coverage and utilization across the country. The Effective Programme Coverage framework is a Programme Science tool to optimize a programme's population-level impact by examining gaps in programme coverage using data generated through programme-embedded research and learning. We apply the framework using Integrated Biological and Behavioural Surveillance Survey (IBBSS) data from Nigeria to examine coverage of four prevention interventions-condoms, HIV testing, and needle and syringe programmes (NSP)-among four key population groups-female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID) and transgender people. METHODS Data from Nigeria's 2020 IBBSS, implemented in 12 states, were analysed to examine HIV prevention programme coverage among key populations. For each key population group and prevention intervention of interest, weighted IBBSS data were used to retrospectively generate coverage cascades that identify and quantify coverage gaps. Required coverage targets were informed by targets articulated in Nigeria's National HIV/AIDS Strategic Framework or, in their absence, by guidelines from policy normative bodies. Availability-, outreach- and utilization coverage proxy indicators were defined using variables from IBBSS data collection tools. Sankey diagrams are presented to visualize pathways followed by participants between coverage cascade steps. RESULTS Required coverage targets were missed for HIV testing and NSP among all key population groups. Condom availability coverage surpassed required coverage targets among FSW and MSM, while utilization coverage only among FSW exceeded the 90% required coverage target. Outreach coverage was low for all key population groups, falling below all required coverage targets. CONCLUSIONS Our findings identify critical gaps in HIV prevention programme coverage for key populations in Nigeria and demonstrate non-linear movement across coverage cascades, signalling the need for innovative solutions to optimize coverage of prevention services. Programme-embedded research is required to better understand how key population groups in Nigeria access and use different HIV prevention services so that programmes, policies and resource allocation decisions can be optimized to achieve effective programme coverage and population-level impact.
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Affiliation(s)
- Leigh M. McClarty
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
| | - Kalada Green
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
- West African Centre for Public Health and DevelopmentAbujaNigeria
| | - Stella Leung
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
| | | | - Adediran Adesina
- West African Centre for Public Health and DevelopmentAbujaNigeria
| | - Souradet Y. Shaw
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
| | - Bronwyn Neufeld
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
- National Sexually Transmitted and Blood Borne Infection LaboratoryPublic Health Agency of CanadaWinnipegManitobaCanada
| | - Shajy Isac
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
- India Health Action TrustDelhiIndia
| | - Faran Emmanuel
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
| | - James F. Blanchard
- Institute for Global Public HealthUniversity of ManitobaWinnipegManitobaCanada
| | - Gambo Aliyu
- National Agency for the Control of AIDSAbujaNigeria
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Zheng A, Detorio M, Dobbs T, Shanmugam V, Tan X, Vuong J, Domaoal RA, Lee K, Williams L, Jackson K, Parekh B, Yufenyuy EL. Continuous quality evaluation of the Asanté rapid test for recent infection for robust kit lot quality verification. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003195. [PMID: 38743714 DOI: 10.1371/journal.pgph.0003195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 04/16/2024] [Indexed: 05/16/2024]
Abstract
The Sedia Biosciences Asanté rapid test for recent infection (RTRI) can identify HIV infections and characterize HIV-1 as recent or long-term infection via the positive verification (V) line and long-term line (LT) line, respectively. Tracking with Recency Assays to Control the Epidemic (TRACE) program uses RTRI assays. Successful implementation of TRACE requires high-quality test performance. The goal of this study is to evaluate the additional quality practices established for new kit lots prior to field use. Asanté lot quality control data from the manufacturer is reviewed by the Centers for Disease Control and Prevention International Laboratory Branch (CDC-ILB) in the Division of Global HIV and TB using. If a lot passes manufacturer quality control and CDC-ILB review, test kits are sent to CDC-ILB for further evaluation. Evaluation by CDC includes inter-rater reliability and linear regressions comparing the V and LT lines against reference data as well as V and LT line data between testers. A Bland-Altman analysis was conducted to assess bias and systematic error. Overall, CDC-ILB passed 29 (91%) out of 32 Sedia Biosciences Asanté kit lots that initially passed manufacturing quality control from July 2017 to May 2020. Regression analyses demonstrate that test kits are performing as expected with consistent R2≥0.92 for both V and LT lines. On average, inter-rater reliability kappa was 0.9, indicating a strong level of agreement. Bland-Altman analyses demonstrate high agreement with little to no systematic error and bias. Ongoing evaluation of new RTRI kit lots is important to ensure high quality test performance. Rejecting 9% of kit lots highlight the importance of continuing to work with manufacturers to ensure consistent kit production and quality assurance (QA) activities. Investing in effective QA measures, conducting both pre- and post-market performance data reviews, could help improve RTRI accuracy and outcomes in similar testing programs.
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Affiliation(s)
- Amy Zheng
- Public Health Institute/Centers for Disease Control Global Health Fellowship Program, Oakland, California, United States of America
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Mervi Detorio
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Trudy Dobbs
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Vedapuri Shanmugam
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Xiaojuan Tan
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Jeni Vuong
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Robert A Domaoal
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Kemba Lee
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - LaTasha Williams
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Keisha Jackson
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Bharat Parekh
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Ernest L Yufenyuy
- Division of Global HIV & Tuberculosis, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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Luvuno ZPB, Wiafe E, Mpofana N, Urusla MM, Nxumalo CT. Fast-track interventions for HIV and AIDS epidemic control among key populations: A rapid review. Afr J Prim Health Care Fam Med 2024; 16:e1-e12. [PMID: 38708735 PMCID: PMC11079388 DOI: 10.4102/phcfm.v16i1.4088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 10/31/2023] [Accepted: 11/01/2023] [Indexed: 05/07/2024] Open
Abstract
BACKGROUND Targeted interventions for key populations remain critical for realisation of epidemic control for human immunodeficiency virus (HIV) infection because of the causal relationship between HIV infection in the general population and among key population groups. AIM To consolidate evidence on the fast-track interventions towards achieving HIV epidemic control among key populations. METHODS A rapid scoping review was conducted using the methodological framework by Arksey and O' Malley. The Population, Intervention, Context and Outcome (PICO) framework was used to identify relevant studies using key words with Boolean operators in electronic data bases, namely CINHAL, Web of Science, Psych Info and Sabinet. Studies were extracted using a modified data extraction tool, and results were presented narratively. RESULTS A total of 19 articles were included in this review. Most articles were primary studies (n = 17), while another involved the review of existing literature and policies (n = 2) and routinely collected data (n = 1). Most studies were conducted in the United States of America (n = 6), while another were conducted in China, Kenya, Botswana, South Africa and Mozambique. All studies revealed findings on tested interventions to achieve HIV epidemic control among key populations. CONCLUSION Effective interventions for HIV epidemic control were stand-alone behavioural preventive interventions, stand-alone biomedical preventive strategies and combination prevention approaches. Furthermore, the findings suggest that effective activities to achieve HIV epidemic control among key populations should be centred around prevention.Contribution: The findings of this study have policy and practice implications for high HIV burden settings such as South Africa in terms of interventions to facilitate realisation of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 95-95-95 targets, thereby contributing to HIV epidemic control.
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Affiliation(s)
- Zamasomi P B Luvuno
- Centre for Rural Health, School of Nursing and Public Health, University of KwaZulu-Natal, Howard Campus, Durban.
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6
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Masango BZ, Ferrandiz-Mont D, Chiao C. Voluntary medical male circumcision and educational gradient in relation to HIV infection among sexually active adult men in Eswatini: evidence from the national surveys in 2006-2007 and 2016. Int Health 2024; 16:208-218. [PMID: 37702181 PMCID: PMC10911536 DOI: 10.1093/inthealth/ihad070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/01/2023] [Accepted: 08/18/2023] [Indexed: 09/14/2023] Open
Abstract
BACKGROUND To address knowledge gaps, this study examined social determinants, such as education attainment and HIV prevention, among sexually active men (SAM), with a focus on voluntary medical male circumcision (VMMC). METHODS Two nationally representative surveys, the Eswatini Demographic and Health Survey 2006 and the Eswatini HIV Incidence Measurement Survey 2016, were used to estimate whether or not VMMC at the individual and community levels contributes to HIV disparities to any meaningful extent. Multilevel logistic regression models further explored the educational gradient in HIV infection for 2006-2007 and 2016 with regard to VMMC among SAM, while adjusting for household poverty, sexual practices and individual characteristics. RESULTS Among SAM with tertiary education, HIV prevalence declined from 25.0% in 2006-2007 to 10.5% in 2016. A 51% decrease in HIV prevalence was found to be associated with an increase in VMMC (adjusted odds ratio 0.49; 95% CI 0.40 to 0.60). Compared with SAM with tertiary education, those who had a lower level of education were more likely to have HIV infection and this education gradient effect had become particularly profound in 2016. CONCLUSIONS VMMC began to be promoted in 2008 in Eswatini and results suggest its effect, along with the education attainment effect, significantly resulted in a meaningful reduction in HIV prevalence among SAM by 2016.
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Affiliation(s)
| | - David Ferrandiz-Mont
- Public Health Surveillance and Emergency Response Department of Vallès Occidental and Vallès Oriental, Public Health Agency of Catalonia, Sant Cugat del Vallès, Barcelona 08173, Spain
| | - Chi Chiao
- Institute of Health and Welfare Policy, College of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan, ROC
- Institute of Public Health, College of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan, ROC
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Stannah J, Soni N, Lam JKS, Giguère K, Mitchell KM, Kronfli N, Larmarange J, Moh R, Nouaman M, Kouamé GM, Boily MC, Maheu-Giroux M. Trends in HIV testing, the treatment cascade, and HIV incidence among men who have sex with men in Africa: a systematic review and meta-analysis. Lancet HIV 2023; 10:e528-e542. [PMID: 37453439 DOI: 10.1016/s2352-3018(23)00111-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Gay, bisexual, and other men who have sex with men (MSM) are disproportionately affected by HIV. In Africa, MSM face structural barriers to HIV prevention and treatment that increase their vulnerability to HIV acquisition and transmission, and undermine the HIV response. In this systematic review, we aimed to explore progress towards increases in HIV testing, improving engagement in the HIV treatment cascade, and HIV incidence reductions among MSM in Africa. METHODS We searched Embase, MEDLINE, Global Health, Scopus, and Web of Science for cross-sectional and longitudinal studies reporting HIV testing, knowledge of status, care, antiretroviral therapy (ART) use, viral suppression, and HIV incidence among MSM in Africa published between Jan 1, 1980, and March 3, 2023. We pooled surveys using Bayesian generalised linear mixed-effects models, used meta-regression to assess time trends, and compared HIV incidence estimates among MSM with those of all men. FINDINGS Of 9278 articles identified, we included 152 unique studies published in 2005-23. In 2020, we estimate that 73% (95% credible interval [CrI] 62-87) of MSM had ever tested for HIV. HIV testing in the past 12 months increased over time in central, western, eastern, and southern Africa (odds ratio per year [ORyear] 1·23, 95% CrI 1·01-1·51, n=46) and in 2020 an estimated 82% (70-91) had tested in the past 12 months, but only 51% (30-72) of MSM living with HIV knew their HIV status. Current ART use increased over time in central and western (ORyear 1·41, 1·08-1·93, n=9) and eastern and southern Africa (ORyear 1·37, 1·04-1·84, n=17). We estimated that, in 2020, 73% (47-88) of all MSM living with HIV in Africa were currently on ART. Nevertheless, we did not find strong evidence to suggest that viral suppression increased, with only 69% (38-89) of MSM living with HIV estimated to be virally suppressed in 2020. We found insufficient evidence of a decrease in HIV incidence over time (incidence ratio per year 0·96, 95% CrI 0·63-1·50, n=39), and HIV incidence remained high in 2020 (6·9 per 100 person-years, 95% CrI 3·1-27·6) and substantially higher (27-199 times higher) than among all men. INTERPRETATION HIV incidence remains high, and might not be decreasing among MSM in Africa over time, despite some increases in HIV testing and ART use. Achieving the UNAIDS 95-95-95 targets for diagnosis, treatment, and viral suppression equitably for all requires renewed focus on this key population. Combination interventions for MSM are urgently required to reduce disparities in HIV incidence and tackle the social, structural, and behavioural factors that make MSM vulnerable to HIV acquisition. FUNDING US National Institutes of Health, UK Medical Research Council, Canadian Institutes of Health Research, and Fonds de Recherche du Québec-Santé. TRANSLATION For the French translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- James Stannah
- School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - Nirali Soni
- Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Jin Keng Stephen Lam
- Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Katia Giguère
- Institut national de santé publique du Québec, Québec, QC, Canada
| | - Kate M Mitchell
- Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK
| | - Nadine Kronfli
- Department of Medicine, Division of Infectious Diseases and Chronic Viral Illness Service, McGill University Health Centre, Montréal, QC, Canada; Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, McGill University Health Centre, Montréal, QC, Canada
| | - Joseph Larmarange
- Centre Population et Développement, Université Paris Cité, Institut de Recherche pour le Développement, Inserm, Paris, France
| | - Raoul Moh
- Pedagogical Unit of Dermatology and Infectiology, RTU Medical Science, Abidjan, Côte d'Ivoire; Programme PAC-CI, CHU de Treichville, Site ANRS, Abidjan, Côte d'Ivoire
| | - Marcellin Nouaman
- Programme PAC-CI, CHU de Treichville, Site ANRS, Abidjan, Côte d'Ivoire
| | | | - Marie-Claude Boily
- Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
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Castor D, Heck CJ, Quigee D, Telrandhe NV, Kui K, Wu J, Glickson E, Yohannes K, Rueda ST, Bozzani F, Meyers K, Zucker J, Deacon J, Kripke K, Sobieszczyk ME, Terris‐Prestholt F, Malati C, Obermeyer C, Dam A, Schwartz K, Forsythe S. Implementation and resource needs for long-acting PrEP in low- and middle-income countries: a scoping review. J Int AIDS Soc 2023; 26 Suppl 2:e26110. [PMID: 37439063 PMCID: PMC10339010 DOI: 10.1002/jia2.26110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 05/05/2023] [Indexed: 07/14/2023] Open
Abstract
INTRODUCTION Several low- and middle-income countries (LMICs) are preparing to introduce long-acting pre-exposure prophylaxis (LAP). Amid multiple pre-exposure prophylaxis (PrEP) options and constrained funding, decision-makers could benefit from systematic implementation planning and aligned costs. We reviewed national costed implementation plans (CIPs) to describe relevant implementation inputs and activities (domains) for informing the costed rollout of LAP. We assessed how primary costing evidence aligned with those domains. METHODS We conducted a rapid review of CIPs for oral PrEP and family planning (FP) to develop a consensus of implementation domains, and a scoping review across nine electronic databases for publications on PrEP costing in LMICs between January 2010 and June 2022. We extracted cost data and assessed alignment with the implementation domains and the Global Health Costing Consortium principles. RESULTS We identified 15 implementation domains from four national PrEP plans and FP-CIP template; only six were in all sources. We included 66 full-text manuscripts, 10 reported LAP, 13 (20%) were primary cost studies-representing seven countries, and none of the 13 included LAP. The 13 primary cost studies included PrEP commodities (n = 12), human resources (n = 11), indirect costs (n = 11), other commodities (n = 10), demand creation (n = 9) and counselling (n = 9). Few studies costed integration into non-HIV services (n = 5), above site costs (n = 3), supply chains and logistics (n = 3) or policy and planning (n = 2), and none included the costs of target setting, health information system adaptations or implementation research. Cost units and outcomes were variable (e.g. average per person-year). DISCUSSION LAP planning will require updating HIV prevention policies, technical assistance for logistical and clinical support, expanding beyond HIV platforms, setting PrEP achievement targets overall and disaggregated by method, extensive supply chain and logistics planning and support, as well as updating health information systems to monitor multiple PrEP methods with different visit schedules. The 15 implementation domains were variable in reviewed studies. PrEP primary cost and budget data are necessary for new product introduction and should match implementation plans with financing. CONCLUSIONS As PrEP services expand to include LAP, decision-makers need a framework, tools and a process to support countries in planning the systematic rollout and costing for LAP.
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Affiliation(s)
- Delivette Castor
- Division of Infectious DiseasesColumbia University Irving Medical CenterNew YorkNew YorkUSA
- Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
| | - Craig J. Heck
- Division of Infectious DiseasesColumbia University Irving Medical CenterNew YorkNew YorkUSA
- Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
| | - Daniela Quigee
- Division of Infectious DiseasesColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | | | - Kiran Kui
- Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
| | - Jiaxin Wu
- Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
| | | | - Kibret Yohannes
- University of Virginia School of MedicineCharlottesvilleVirginiaUSA
| | | | | | - Kathrine Meyers
- Division of Infectious DiseasesColumbia University Irving Medical CenterNew YorkNew YorkUSA
- The Aaron Diamond AIDS Research CenterColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Jason Zucker
- Division of Infectious DiseasesColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | | | | | | | | | - Christine Malati
- United States Agency for International DevelopmentWashingtonDCUSA
| | - Chris Obermeyer
- The Global Fund to Fight AIDS, Tuberculosis and MalariaGenevaSwitzerland
| | - Anita Dam
- United States Agency for International DevelopmentWashingtonDCUSA
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Bozzani FM, Terris-Prestholt F, Quaife M, Gafos M, Indravudh PP, Giddings R, Medley GF, Malhotra S, Torres-Rueda S. Costs and Cost-Effectiveness of Biomedical, Non-Surgical HIV Prevention Interventions: A Systematic Literature Review. PHARMACOECONOMICS 2023; 41:467-480. [PMID: 36529838 PMCID: PMC10085926 DOI: 10.1007/s40273-022-01223-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 11/10/2022] [Indexed: 05/10/2023]
Abstract
BACKGROUND Considerable evidence on the costs and cost-effectiveness of biomedical, non-surgical interventions to prevent human immunodeficiency virus (HIV) transmission has been generated over the last decade. This study aims to synthesize findings and identify remaining knowledge gaps to suggest future research priorities. METHODS A systematic literature review was carried out in August 2020 using the MEDLINE, Embase, Global Health and EconLit databases to retrieve economic evaluations and costing studies of oral pre-exposure prophylaxis (PrEP), injectable long-acting PrEP, vaginal microbicide rings and gels, HIV vaccines and broadly neutralizing antibodies. Studies reporting costs from the provider or societal perspective were included in the analysis. Those reporting on behavioural methods of prevention, condoms and surgical approaches (voluntary medical male circumcision) were excluded. The quality of reporting of the included studies was assessed using published checklists. RESULTS We identified 3007 citations, of which 87 studies were retained. Most were set in low- and middle-income countries (LMICs; n = 53) and focused on the costs and/or cost-effectiveness of oral PrEP regimens (n = 70). Model-based economic evaluations were the most frequent study design; only two trial-based cost-effectiveness analyses and nine costing studies were found. Less than half of the studies provided practical details on how the intervention would be delivered by the health system, and only three of these, all in LMICs, explicitly focused on service integration and its implication for delivery costs. 'Real-world' programme delivery mechanisms and costs of intervention delivery were rarely considered. PrEP technologies were generally found to be cost-effective only when targeting high-risk subpopulations. Single-dose HIV vaccines are expected to be cost-effective for all groups despite substantial uncertainty around pricing. CONCLUSIONS A lack of primary, detailed and updated cost data, including above-service level costs, from a variety of settings makes it difficult to evaluate the cost-effectiveness of specific delivery modes at scale, or to evaluate strategies for services integration. Closing this evidence gap around real-world implementation is vital, not least because the strategies targeting high-risk groups that are recommended by PrEP models may incur substantially higher costs and be of limited practical feasibility in some settings.
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Affiliation(s)
- Fiammetta M Bozzani
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK.
| | | | - Matthew Quaife
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | - Mitzy Gafos
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | - Pitchaya P Indravudh
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | | | - Graham F Medley
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
| | | | - Sergio Torres-Rueda
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
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Howes A, Risher KA, Nguyen VK, Stevens O, Jia KM, Wolock TM, Esra RT, Zembe L, Wanyeki I, Mahy M, Benedikt C, Flaxman SR, Eaton JW. Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001731. [PMID: 37075002 PMCID: PMC10115274 DOI: 10.1371/journal.pgph.0001731] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 02/23/2023] [Indexed: 04/20/2023]
Abstract
The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partner[s] and female sex workers [FSW]) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of the population but 10.6% of all expected new infections. Our risk group estimates provide data for HIV programmes to set targets and implement differentiated prevention strategies outlined in the Global AIDS Strategy. Successfully implementing this approach would result in more efficiently reaching substantially more of those at risk for infections.
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Affiliation(s)
- Adam Howes
- Department of Mathematics, Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Kathryn A. Risher
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
- Heidelberg Institute for Global Health, Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | - Van Kính Nguyen
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, United States of America
| | - Oliver Stevens
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Katherine M. Jia
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Timothy M. Wolock
- Department of Mathematics, Imperial College London, London, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Rachel T. Esra
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Lycias Zembe
- Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland
| | - Ian Wanyeki
- Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland
| | - Mary Mahy
- Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland
| | | | - Seth R. Flaxman
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Jeffrey W. Eaton
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
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11
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Who is Exposed to HIV Prevention Interventions? An Assessment of Associated Factors Among Adolescent Girls and Young Women in South Africa. AIDS Behav 2023:10.1007/s10461-023-04023-1. [PMID: 36856934 PMCID: PMC10387118 DOI: 10.1007/s10461-023-04023-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2023] [Indexed: 03/02/2023]
Abstract
This study examined the prevalence of HIV risk factors and their association with intervention exposure among adolescent girls and young women (AGYW) living in six South African districts in which a combination HIV-prevention intervention was being implemented. A cross-sectional household survey was conducted from 2017 to 2018 among a representative sample of AGYW aged 15-24 years living in the six districts. We used an electronic questionnaire for self-reported demographic and behavioural questions and blood samples were taken to confirm HIV status in the laboratory. Chi-Squared tests and multivariate binary logistic regression were used to examine associations between demographic characteristics, HIV acquisition and transmission risk factors and the likelihood of participating in any of the key components of the combination HIV-prevention intervention. Among the 4399 participants, 45.3% reported inconsistent condom use with casual partner and 46.6% with a main partner. Almost half of participants (47.8%) had participated in one or more components of the HIV-prevention intervention, and in a multivariate logistic regression, those reporting a higher number of HIV risk behaviours were no more (or less) likely to participate. Participants who were not in high school were significantly less likely to have participated in the intervention compared to those still in high school, when adjusting for age and HIV risk factors. The barriers to access and uptake of combination HIV prevention interventions among AGYW who are out of the education system need to be explored and combination HIV prevention interventions and implementation strategies need to be tailored to reach this population.
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Yang H, Li Y, He F, Yuan F, Liu L, Li L, Yuan D, Ye L, Zhou C, Zhang Y, Su L, Liang S. Demographic Characteristics and Hot-Spot Areas of Recent Infections Among New HIV Diagnoses in Sichuan, China, Between 2018 and 2020. Infect Drug Resist 2023; 16:779-789. [PMID: 36779044 PMCID: PMC9911905 DOI: 10.2147/idr.s394828] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 01/18/2023] [Indexed: 02/06/2023] Open
Abstract
Background Sichuan Province is severely affected by the HIV epidemic in China. Little is known about the characteristics of recent infections among new HIV diagnoses, which is critical to prevention strategies, evaluation of the HIV epidemic and health resource allocation. Meanwhile, individuals at primary stages of infection are related to the hot-spot areas of ongoing transmission in new HIV diagnoses, which is also rarely known. Objective This article aimed to report the proportion of recent infections among new HIV diagnoses, and to reveal demographic characteristics associated with HIV recent infections, and finally, to indicate the hot-spot areas of ongoing transmission in Sichuan province between 2018 and 2020. Methods Limiting Antigen (LAg)-Avidity assay was performed to detect recent infection within new HIV diagnoses reported in odd months between 2018 and 2020. Results were reclassified according to the data on CD4 cell count, antiretroviral treatment and the existence of an AIDS-defining illness. Logistic regression was used to determine characteristics associated with HIV recent infections. The spatial analysis was conducted with ArcGIS 10.7 to figure hot-spot areas of HIV recent infections. Results 42,089 newly diagnosed HIV-1 cases were tested using the LAg-Avidity EIA. In total, 5848 (13.89%) of those were classified as HIV recent infections. Female, age between 18-25 years and men who had sex with men were related to higher proportion of HIV recent infections. Logistic regression revealed that MSM aged between 18-25 years were more likely to be classified as recent infection. Spatial analysis demonstrated significant clustering in Chengdu, Yibin, Luzhou city between 2018 and 2020. Hot spots were mainly clustered in the center of Sichuan in 2018, but gradually spread to southwest and northwest between 2019 and 2020. Conclusion Enhanced preventive measures among relevant risk groups and areas where the potential HIV-1 transmission is ongoing is urgently needed to curb further spread.
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Affiliation(s)
- Hong Yang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yiping Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Fang He
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Fengshun Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Lunhao Liu
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ling Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Dan Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Li Ye
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Chang Zhou
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yan Zhang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Ling Su
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Shu Liang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China,Correspondence: Shu Liang; Ling Su, Email ;
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13
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Babatunde AO, Akin-Ajani OD, Abdullateef RO, Togunwa TO, Isah HO. Review of antiretroviral therapy coverage in 10 highest burden HIV countries in Africa: 2015-2020. J Med Virol 2023; 95:e28320. [PMID: 36397202 DOI: 10.1002/jmv.28320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 10/19/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022]
Abstract
Africa is responsible for two-thirds of the global total of new HIV infections. South Africa, Nigeria, Mozambique, Uganda, Tanzania, Zambia, Zimbabwe, Kenya, Malawi, and Ethiopia were responsible for 80% of HIV cases in Africa in 2014 according to the Joint United Nations Programme on HIV/AIDS (UNAIDS). This study assesses antiretroviral coverage strategies implemented by these countries after the initiation of the "Fast-Track strategy to end the AIDS epidemic by 2030." Data reported in this review were obtained from different e-bibliographic including PubMed, Google Scholar, and Research Gate. Key terms were "Antiretroviral therapy," "Antiretroviral treatment," "HIV treatment," "HIV medication," "HIV/AIDS therapy," "HIV/AIDS treatment" + each of the countries listed earlier. We also extracted data on antiretroviral therapy (ART) coverage from the UNAIDS database. About 50 papers published from 2015 to 2021 met the inclusion criteria. All 10 countries have experienced an increase in ART coverage from 2015 to 2020 with an average of 47.6% increment. Nigeria recorded the highest increase in the rate of ART coverage (72% increase) while Ethiopia had the least (30%). New strategies adopted to increase ART coverage and retention in most countries were community-based models and the use of mobile health technology rather than clinic-based. These strategies focus on promoting task shifting, door-to-door access to HIV services, and a long-term supply of antiretroviral medications. Most of these strategies are still in the piloting stage. However, some new strategies and frameworks have been adopted nationwide in countries like Mozambique, Tanzania, Zambia, Zimbabwe, Kenya, and Malawi. Identified challenges include lack of funding, inadequate testing and surveillance services, poor digital penetration, and cultural/religious beliefs. The adoption of community-based and digital health strategies could have contributed to increased ART coverage and retention. African countries should facilitate nationwide scaling of ART coverage strategies to attain the 95-95-95 goal by 2030.
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Affiliation(s)
- Abdulhammed O Babatunde
- Department of Medicine and Surgery, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Nigeria.,Healthy Africans Platform, Ibadan, Nigeria.,Federation of African Medical Students' Associations, Ibadan, Nigeria
| | - Oluwawapelumi D Akin-Ajani
- Department of Medicine and Surgery, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Ridwanullah O Abdullateef
- Department of Medicine and Surgery, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Taofeeq O Togunwa
- Department of Medicine and Surgery, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Haroun O Isah
- Department of Community Medicine and Primary Health Care, College of Medicine and Health Sciences, Bingham University, Jos, Nigeria
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14
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Haeuser E, Serfes AL, Cork MA, Yang M, Abbastabar H, Abhilash ES, Adabi M, Adebayo OM, Adekanmbi V, Adeyinka DA, Afzal S, Ahinkorah BO, Ahmadi K, Ahmed MB, Akalu Y, Akinyemi RO, Akunna CJ, Alahdab F, Alanezi FM, Alanzi TM, Alene KA, Alhassan RK, Alipour V, Almasi-Hashiani A, Alvis-Guzman N, Ameyaw EK, Amini S, Amugsi DA, Ancuceanu R, Anvari D, Appiah SCY, Arabloo J, Aremu O, Asemahagn MA, Jafarabadi MA, Awedew AF, Quintanilla BPA, Ayanore MA, Aynalem YA, Azari S, Azene ZN, Darshan BB, Babalola TK, Baig AA, Banach M, Bärnighausen TW, Bell AW, Bhagavathula AS, Bhardwaj N, Bhardwaj P, Bhattacharyya K, Bijani A, Bitew ZW, Bohlouli S, Bolarinwa OA, Boloor A, Bozicevic I, Butt ZA, Cárdenas R, Carvalho F, Charan J, Chattu VK, Chowdhury MAK, Chu DT, Cowden RG, Dahlawi SMA, Damiani G, Darteh EKM, Darwesh AM, das Neves J, Weaver ND, De Leo D, De Neve JW, Deribe K, Deuba K, Dharmaratne S, Dianatinasab M, Diaz D, Didarloo A, Djalalinia S, Dorostkar F, Dubljanin E, Duko B, El Tantawi M, El-Jaafary SI, Eshrati B, Eskandarieh S, Eyawo O, Ezeonwumelu IJ, Ezzikouri S, Farzadfar F, Fattahi N, Fauk NK, Fernandes E, Filip I, Fischer F, Foigt NA, Foroutan M, Fukumoto T, Gad MM, Gaidhane AM, Gebregiorgis BG, Gebremedhin KB, Getacher L, Ghadiri K, Ghashghaee A, Golechha M, Gubari MIM, Gugnani HC, Guimarães RA, Haider MR, Haj-Mirzaian A, Hamidi S, Hashi A, Hassanipour S, Hassankhani H, Hayat K, Herteliu C, Ho HC, Holla R, Hosseini M, Hosseinzadeh M, Hwang BF, Ibitoye SE, Ilesanmi OS, Ilic IM, Ilic MD, Islam RM, Iwu CCD, Jakovljevic M, Jha RP, Ji JS, Johnson KB, Joseph N, Joshua V, Joukar F, Jozwiak JJ, Kalankesh LR, Kalhor R, Kamyari N, Kanchan T, Matin BK, Karimi SE, Kayode GA, Karyani AK, Keramati M, Khan EA, Khan G, Khan MN, Khatab K, Khubchandani J, Kim YJ, Kisa A, Kisa S, Kopec JA, Kosen S, Laxminarayana SLK, Koyanagi A, Krishan K, Defo BK, Kugbey N, Kulkarni V, Kumar M, Kumar N, Kusuma D, La Vecchia C, Lal DK, Landires I, Larson HJ, Lasrado S, Lee PH, Li S, Liu X, Maleki A, Malik P, Mansournia MA, Martins-Melo FR, Mendoza W, Menezes RG, Mengesha EW, Meretoja TJ, Mestrovic T, Mirica A, Moazen B, Mohamad O, Mohammad Y, Mohammadian-Hafshejani A, Mohammadpourhodki R, Mohammed S, Mohammed S, Mokdad AH, Moradi M, Moraga P, Mubarik S, Mulu GBB, Mwanri L, Nagarajan AJ, Naimzada MD, Naveed M, Nazari J, Ndejjo R, Negoi I, Ngalesoni FN, Nguefack-Tsague G, Ngunjiri JW, Nguyen CT, Nguyen HLT, Nnaji CA, Noubiap JJ, Nuñez-Samudio V, Nwatah VE, Oancea B, Odukoya OO, Olagunju AT, Olakunde BO, Olusanya BO, Olusanya JO, Bali AO, Onwujekwe OE, Orisakwe OE, Otstavnov N, Otstavnov SS, Owolabi MO, Mahesh PA, Padubidri JR, Pana A, Pandey A, Pandi-Perumal SR, Kan FP, Patton GC, Pawar S, Peprah EK, Postma MJ, Preotescu L, Syed ZQ, Rabiee N, Radfar A, Rafiei A, Rahim F, Rahimi-Movaghar V, Rahmani AM, Ramezanzadeh K, Rana J, Ranabhat CL, Rao SJ, Rawaf DL, Rawaf S, Rawassizadeh R, Regassa LD, Rezaei N, Rezapour A, Riaz MA, Ribeiro AI, Ross JM, Rubagotti E, Rumisha SF, Rwegerera GM, Moghaddam SS, Sagar R, Sahiledengle B, Sahu M, Salem MR, Kafil HS, Samy AM, Sartorius B, Sathian B, Seidu AA, Shaheen AA, Shaikh MA, Shamsizadeh M, Shiferaw WS, Shin JI, Shrestha R, Singh JA, Skryabin VY, Skryabina AA, Soltani S, Sufiyan MB, Tabuchi T, Tadesse EG, Taveira N, Tesfay FH, Thapar R, Tovani-Palone MR, Tsegaye GW, Umeokonkwo CD, Unnikrishnan B, Villafañe JH, Violante FS, Vo B, Vu GT, Wado YD, Waheed Y, Wamai RG, Wang Y, Ward P, Wickramasinghe ND, Wilson K, Yaya S, Yip P, Yonemoto N, Yu C, Zastrozhin MS, Zhang Y, Zhang ZJ, Hay SI, Dwyer-Lindgren L. Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000-2018. BMC Med 2022; 20:488. [PMID: 36529768 PMCID: PMC9760541 DOI: 10.1186/s12916-022-02639-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 10/26/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15-59 years across SSA. METHODS We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. RESULTS We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. CONCLUSIONS As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.
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Affiliation(s)
- Emily Haeuser
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
| | - Audrey L Serfes
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Michael A Cork
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Mingyou Yang
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Hedayat Abbastabar
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - E S Abhilash
- Department of Botany, Sree Narayana Guru College Chelannur, Kozhikode, India
| | - Maryam Adabi
- Hamadan University of Medical Sciences, Hamadan, Iran
| | | | - Victor Adekanmbi
- Department of Population Medicine, Cardiff University, Cardiff, UK
| | - Daniel Adedayo Adeyinka
- Department of Community Health and Epidemiology, University of Saskatchewan, Saskatoon, SK, Canada
- Department of Public Health, Federal Ministry of Health, Abuja, Nigeria
| | - Saira Afzal
- Department of Community Medicine, King Edward Memorial Hospital, Lahore, Pakistan
- Department of Public Health, Public Health Institute, Lahore, Pakistan
| | - Bright Opoku Ahinkorah
- The Australian Centre for Public and Population Health Research (ACPPHR), University of Technology Sydney, Sydney, NSW, Australia
| | - Keivan Ahmadi
- School of Public Health, Imperial College London, London, UK
| | - Muktar Beshir Ahmed
- Department of Epidemiology, Jimma University, Jimma, Ethiopia
- Australian Center for Precision Health, University of South Australia, Adelaide, SA, Australia
| | - Yonas Akalu
- Department of Medical Physiology, University of Gondar, Gondar, Ethiopia
| | - Rufus Olusola Akinyemi
- Institute for Advanced Medical Research and Training, University of Ibadan, Ibadan, Nigeria
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Chisom Joyqueenet Akunna
- Department of Public Health, The Intercountry Centre for Oral Health (ICOH) for Africa, Jos, Nigeria
- Department of Public Health, Federal Ministry of Health, Garki, Nigeria
| | - Fares Alahdab
- Mayo Evidence-based Practice Center, Mayo Clinic Foundation for Medical Education and Research, Rochester, MN, USA
| | | | - Turki M Alanzi
- Health Information Management and Technology Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Kefyalew Addis Alene
- Faculty of Health Sciences, Curtin University, Perth, WA, Australia
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Perth, WA, Australia
| | - Robert Kaba Alhassan
- Institute of Health Research, University of Health and Allied Sciences, Ho, Ghana
| | - Vahid Alipour
- Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
- Department of Health Economics, Iran University of Medical Sciences, Tehran, Iran
| | | | - Nelson Alvis-Guzman
- Research Group in Hospital Management and Health Policies, Universidad de la Costa (University of the Coast), Barranquilla, Colombia
- Research Group in Health Economics, University of Cartagena, Cartagena, Colombia
| | - Edward Kwabena Ameyaw
- The Australian Centre for Public and Population Health Research (ACPPHR), University of Technology Sydney, Sydney, NSW, Australia
| | - Saeed Amini
- Department of Health Services Management, Khomein University of Medical Sciences, Khomein, Iran
| | - Dickson A Amugsi
- Department of Maternal and Child Wellbeing, African Population and Health Research Center, Nairobi, Kenya
| | - Robert Ancuceanu
- Pharmacy Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Davood Anvari
- Department of Parasitology, Mazandaran University of Medical Sciences, Sari, Iran
- Department of Parasitology, Iranshahr University of Medical Sciences, Iranshahr, Iran
| | - Seth Christopher Yaw Appiah
- Department of Sociology and Social Work, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
- Center for International Health, Ludwig Maximilians University, Munich, Germany
| | - Jalal Arabloo
- Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Olatunde Aremu
- Department of Public Health, Birmingham City University, Birmingham, UK
| | | | - Mohammad Asghari Jafarabadi
- Department of Biostatistics and Epidemiology, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Biostatistics and Epidemiology, Zanjan University of Medical Sciences, Zanjan, Iran
| | | | | | - Martin Amogre Ayanore
- Department of Health Policy Planning and Management, University of Health and Allied Sciences, Ho, Ghana
- Department of Health Economics, Centre for Health Policy Advocacy Innovation & Research in Africa (CHPAIR-Africa), Accra, Ghana
| | | | - Samad Azari
- Hospital Management Research Center, Iran University of Medical Sciences, Tehran, Iran
| | | | - B B Darshan
- Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
| | - Tesleem Kayode Babalola
- Discipline of Public Health Medicine, University of KwaZulu-Natal, Durban, South Africa
- Department of Community Health and Primary Care, University of Lagos, Lagos, Nigeria
| | - Atif Amin Baig
- Unit of Biochemistry, Universiti Sultan Zainal Abidin (Sultan Zainal Abidin University), Kuala Terengganu, Malaysia
| | - Maciej Banach
- Department of Hypertension, Medical University of Lodz, Lodz, Poland
- Polish Mothers' Memorial Hospital Research Institute, Lodz, Poland
| | - Till Winfried Bärnighausen
- Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Arielle Wilder Bell
- Department of Global Health and Social Medicine, Harvard University, Boston, MA, USA
- Department of Social Services, Tufts Medical Center, Boston, MA, USA
| | - Akshaya Srikanth Bhagavathula
- Department of Social and Clinical Pharmacy, Charles University, Hradec Kralova, Czech Republic
- Institute of Public Health, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Nikha Bhardwaj
- Department of Anatomy, All India Institute of Medical Sciences, Jodhpur, India
| | - Pankaj Bhardwaj
- Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Jodhpur, India
- School of Public Health, All India Institute of Medical Sciences, Jodhpur, India
| | - Krittika Bhattacharyya
- Department of Statistical and Computational Genomics, National Institute of Biomedical Genomics, Kalyani, India
- Department of Statistics, University of Calcutta, Kolkata, India
| | - Ali Bijani
- Social Determinants of Health Research Center, Babol University of Medical Sciences, Babol, Iran
| | - Zebenay Workneh Bitew
- Nutrition Department, St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
- St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Somayeh Bohlouli
- Department of Veterinary Medicine, Islamic Azad University, Kermanshah, Iran
| | | | - Archith Boloor
- Department of Internal Medicine, Manipal Academy of Higher Education, Mangalore, India
| | - Ivana Bozicevic
- WHO Collaborating Centre for HIV Strategic Information, University of Zagreb, Zagreb, Croatia
- Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK
| | - Zahid A Butt
- School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada
- Al Shifa School of Public Health, Al Shifa Trust Eye Hospital, Rawalpindi, Pakistan
| | - Rosario Cárdenas
- Department of Health Care, Metropolitan Autonomous University, Mexico City, Mexico
| | - Felix Carvalho
- Research Unit on Applied Molecular Biosciences (UCIBIO), University of Porto, Porto, Portugal
| | - Jaykaran Charan
- Department of Pharmacology, All India Institute of Medical Sciences, Jodhpur, India
| | - Vijay Kumar Chattu
- Department of Community Medicine, Datta Meghe Institute of Medical Sciences, Sawangi, India
- Saveetha Medical College, Saveetha University, Chennai, India
| | - Mohiuddin Ahsanul Kabir Chowdhury
- James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA
| | - Dinh-Toi Chu
- Center for Biomedicine and Community Health, VNU-International School, Hanoi, Vietnam
| | - Richard G Cowden
- Department of Psychology, University of the Free State, Park West, South Africa
| | - Saad M A Dahlawi
- Environmental Health Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Giovanni Damiani
- IRCCS Istituto Ortopedico Galeazzi (Galeazzi Orthopedic Institute IRCCS), University of Milan, Milan, Italy
- Department of Dermatology, Case Western Reserve University, Cleveland, OH, USA
| | | | - Aso Mohammad Darwesh
- Department of Information Technology, University of Human Development, Sulaymaniyah, Iraq
| | - José das Neves
- Institute for Research and Innovation in Health, University of Porto, Porto, Portugal
- Institute of Biomedical Engineering (INEB), University of Porto, Porto, Portugal
| | - Nicole Davis Weaver
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Diego De Leo
- Australian Institute for Suicide Research and Prevention, Griffith University, Mount Gravatt, QLD, Australia
| | - Jan-Walter De Neve
- Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany
| | - Kebede Deribe
- Wellcome Trust Brighton and Sussex Centre for Global Health Research, Brighton and Sussex Medical School, Brighton, UK
- School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia
| | - Keshab Deuba
- National Centre for AIDS and STD Control, Save the Children, Kathmandu, Nepal
- Department of Global Public Health, Karolinska Institute, Stockholm, Sweden
| | - Samath Dharmaratne
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Community Medicine, University of Peradeniya, Peradeniya, Sri Lanka
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Mostafa Dianatinasab
- Department of Epidemiology, Maastricht University, Maastricht, Netherlands
- Department of Epidemiology, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Daniel Diaz
- Center of Complexity Sciences, National Autonomous University of Mexico, Mexico City, Mexico
- Faculty of Veterinary Medicine and Zootechnics, Autonomous University of Sinaloa, Rosales, Culiacán, Mexico
| | - Alireza Didarloo
- Department of Community Medicine and Public Health, Urmia University of Medical Science, Urmia, Iran
| | - Shirin Djalalinia
- Development of Research and Technology Center, Ministry of Health and Medical Education, Tehran, Iran
| | - Fariba Dorostkar
- Department of Medical Laboratory Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Eleonora Dubljanin
- Institute of Microbiology and Immunology, University of Belgrade, Belgrade, Serbia
| | - Bereket Duko
- School of Public Health, Hawassa University, Hawassa, Ethiopia
- School of Public Health, Curtin University, Perth, WA, Australia
| | - Maha El Tantawi
- Pediatric Dentistry and Dental Public Health Department, Alexandria University, Alexandria, Egypt
| | | | - Babak Eshrati
- Preventive Medicine and Public Health Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Sharareh Eskandarieh
- Multiple Sclerosis Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Ifeanyi Jude Ezeonwumelu
- Institute for Health Science Research Germans Trias i Pujol, Autonomous University of Barcelona, Badalona, Spain
- IrsiCaixa AIDS Research Institute, Badalona, Spain
| | - Sayeh Ezzikouri
- Department of Virology, Pasteur Institute of Morocco, Casablanca, Morocco
| | - Farshad Farzadfar
- Non-communicable Diseases Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Nazir Fattahi
- Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Nelsensius Klau Fauk
- Torrens University Australia, Adelaide, SA, Australia
- Institute of Resource Governance and Social Change, Kupang, Indonesia
| | - Eduarda Fernandes
- Associated Laboratory for Green Chemistry (LAQV), University of Porto, Porto, Portugal
| | - Irina Filip
- Psychiatry Department, Kaiser Permanente, Fontana, CA, USA
- School of Health Sciences, A.T. Still University, Mesa, AZ, USA
| | - Florian Fischer
- Institute of Public Health, Charité Universitätsmedizin Berlin (Charité Medical University Berlin), Berlin, Germany
| | - Nataliya A Foigt
- Institute of Gerontology, National Academy of Medical Sciences of Ukraine, Kyiv, Ukraine
| | - Masoud Foroutan
- Department of Medical Parasitology, Abadan University of Medical Sciences, Abadan, Iran
- Faculty of Medicine, Abadan University of Medical Sciences, Abadan, Iran
| | | | - Mohamed M Gad
- Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA
- Gillings School of Global Public Health, University of North Carolina Chapel Hill, Chapel Hill, NC, USA
| | | | | | | | - Lemma Getacher
- Department of Public Health, Debre Berhan University, Debre Berhan, Ethiopia
| | - Keyghobad Ghadiri
- Infectious Disease Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
- Pediatric Department, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Ahmad Ghashghaee
- School of Public Health, Qazvin University of Medical Sciences, Qazvin, Iran
| | - Mahaveer Golechha
- Health Systems and Policy Research, Indian Institute of Public Health, Gandhinagar, India
| | | | - Harish Chander Gugnani
- Department of Microbiology, Saint James School of Medicine, The Valley, Anguilla
- Department of Epidemiology, Saint James School of Medicine, The Valley, Anguilla
| | | | | | - Arvin Haj-Mirzaian
- Department of Pharmacology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Obesity Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Samer Hamidi
- School of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai, United Arab Emirates
| | - Abdiwahab Hashi
- Department of Public Health, Jigjiga University, Jijiga, Ethiopia
| | - Soheil Hassanipour
- Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran
- Caspian Digestive Disease Research Center, Guilan University of Medical Sciences, Rasht, Iran
| | - Hadi Hassankhani
- School of Nursing and Midwifery, Tabriz University of Medical Sciences, Tabriz, Iran
- Independent Consultant, Tabriz, Iran
| | - Khezar Hayat
- Institute of Pharmaceutical Sciences, University of Veterinary and Animal Sciences, Lahore, Pakistan
- Department of Pharmacy Administration and Clinical Pharmacy, Xian Jiaotong University, Xian, China
| | - Claudiu Herteliu
- Department of Statistics and Econometrics, Bucharest University of Economic Studies, Bucharest, Romania
- School of Business, London South Bank University, London, UK
| | - Hung Chak Ho
- Department of Urban Planning and Design, University of Hong Kong, Hong Kong, China
| | - Ramesh Holla
- Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India
| | - Mostafa Hosseini
- Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran
- Pediatric Chronic Kidney Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mehdi Hosseinzadeh
- Institute of Research and Development, Duy Tan University, Da Nang, Vietnam
- Department of Computer Science, University of Human Development, Sulaymaniyah, Iraq
| | - Bing-Fang Hwang
- Department of Occupational Safety and Health, China Medical University, Taichung, Taiwan
| | | | - Olayinka Stephen Ilesanmi
- Department of Community Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Community Medicine, University College Hospital, Ibadan, Ibadan, Nigeria
| | - Irena M Ilic
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Milena D Ilic
- Department of Epidemiology, University of Kragujevac, Kragujevac, Serbia
| | - Rakibul M Islam
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Chidozie C D Iwu
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Mihajlo Jakovljevic
- Institute of Advanced Manufacturing Technologies, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
- Institute of Comparative Economic Studies, Hosei University, Tokyo, Japan
| | - Ravi Prakash Jha
- Department of Community Medicine, Dr. Baba Saheb Ambedkar Medical College & Hospital, Delhi, India
- Department of Community Medicine, Banaras Hindu University, Varanasi, India
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Kimberly B Johnson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Nitin Joseph
- Department of Community Medicine, Manipal Academy of Higher Education, Mangalore, India
| | - Vasna Joshua
- National Institute of Epidemiology, Indian Council of Medical Research, Chennai, India
| | - Farahnaz Joukar
- Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran
- Caspian Digestive Disease Research Center, Guilan University of Medical Sciences, Rasht, Iran
| | - Jacek Jerzy Jozwiak
- Department of Family Medicine and Public Health, University of Opole, Opole, Poland
| | - Leila R Kalankesh
- School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Rohollah Kalhor
- Institute for Prevention of Non-communicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran
- Health Services Management Department, Qazvin University of Medical Sciences, Qazvin, Iran
| | - Naser Kamyari
- Department of Biostatistics, Abadan University of Medical Sciences, Abadan, Iran
| | - Tanuj Kanchan
- Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, India
| | - Behzad Karami Matin
- Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Salah Eddin Karimi
- Social Determinants of Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Gbenga A Kayode
- International Research Center of Excellence, Institute of Human Virology Nigeria, Abuja, Nigeria
- Julius Centre for Health Sciences and Primary Care, Utrecht University, Utrecht, Netherlands
| | - Ali Kazemi Karyani
- Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | | | - Ejaz Ahmad Khan
- Department of Epidemiology and Biostatistics, Health Services Academy, Islamabad, Pakistan
| | - Gulfaraz Khan
- Department of Medical Microbiology & Immunology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Md Nuruzzaman Khan
- Department of Population Science, Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, Bangladesh
| | - Khaled Khatab
- Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield, UK
- College of Arts and Sciences, Ohio University, Zanesville, OH, USA
| | | | - Yun Jin Kim
- School of Traditional Chinese Medicine, Xiamen University Malaysia, Sepang, Malaysia
| | - Adnan Kisa
- School of Health Sciences, Kristiania University College, Oslo, Norway
- Department of Global Community Health and Behavioral Sciences, Tulane University, New Orleans, LA, USA
| | - Sezer Kisa
- Department of Nursing and Health Promotion, Oslo Metropolitan University, Oslo, Norway
| | - Jacek A Kopec
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
- Arthritis Research Canada, Richmond, Canada
| | | | | | - Ai Koyanagi
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), San Juan de Dios Sanitary Park, Sant Boi de Llobregat, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Kewal Krishan
- Department of Anthropology, Panjab University, Chandigarh, India
| | - Barthelemy Kuate Defo
- Department of Demography, University of Montreal, Montreal, QC, Canada
- Department of Social and Preventive Medicine, University of Montreal, Montreal, Canada
| | - Nuworza Kugbey
- University of Environment and Sustainable Development, Somanya, Ghana
| | - Vaman Kulkarni
- Department of Community Medicine, Manipal Academy of Higher Education, Mangalore, India
| | - Manasi Kumar
- Department of Psychiatry, University of Nairobi, Nairobi, Kenya
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Nithin Kumar
- Department of Community Medicine, Manipal Academy of Higher Education, Mangalore, India
| | - Dian Kusuma
- Imperial College Business School, Imperial College London, London, UK
- Faculty of Public Health, University of Indonesia, Depok, Indonesia
| | - Carlo La Vecchia
- Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | | | - Iván Landires
- Unit of Genetics and Public Health, Institute of Medical Sciences, Las Tablas, Panama
- Ministry of Health, Herrera, Panama
| | - Heidi Jane Larson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Savita Lasrado
- Department of Otorhinolaryngology, Father Muller Medical College, Mangalore, India
| | - Paul H Lee
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Xuefeng Liu
- Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Quantitative Health Science, Case Western Reserve University, Cleveland, OH, USA
| | - Afshin Maleki
- Department of Environmental Health Engineering, Tehran University of Medical Sciences, Tehran, Iran
- Environmental Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Preeti Malik
- Department of Pediatrics, Montefiore Medical Center, New York, NY, USA
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mohammad Ali Mansournia
- Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Walter Mendoza
- Peru Country Office, United Nations Population Fund (UNFPA), Lima, Peru
| | - Ritesh G Menezes
- Forensic Medicine Division, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | | | - Tuomo J Meretoja
- Breast Surgery Unit, Helsinki University Hospital, Helsinki, Finland
- University of Helsinki, Helsinki, Finland
| | - Tomislav Mestrovic
- Clinical Microbiology and Parasitology Unit, Dr. Zora Profozic Polyclinic, Zagreb, Croatia
- University Centre Varazdin, University North, Varazdin, Croatia
| | - Andreea Mirica
- Department of Statistics and Econometrics, Bucharest University of Economic Studies, Bucharest, Romania
| | - Babak Moazen
- Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany
- Institute of Addiction Research (ISFF), Frankfurt University of Applied Sciences, Frankfurt, Germany
| | - Osama Mohamad
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA
| | - Yousef Mohammad
- Internal Medicine Department, King Saud University, Riyadh, Saudi Arabia
| | | | | | - Salahuddin Mohammed
- Department of Biomolecular Sciences, University of Mississippi, Oxford, MS, USA
- Department of Pharmacy, Mizan-Tepi University, Mizan, Ethiopia
| | - Shafiu Mohammed
- Health Systems and Policy Research Unit, Ahmadu Bello University, Zaria, Nigeria
- Department of Health Care Management, Technical University of Berlin, Berlin, Germany
| | - Ali H Mokdad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Masoud Moradi
- Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Paula Moraga
- Computer, Electrical, and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Sumaira Mubarik
- Department of Epidemiology and Biostatistics, Wuhan University, Wuhan, China
| | - Getaneh Baye B Mulu
- Department of Pediatrics and Child Health, Debre Berhan University, Debre Berhan, Ethiopia
| | - Lillian Mwanri
- College of Medicine and Public Health, Flinders University, Adeaide, SA, Australia
| | - Ahamarshan Jayaraman Nagarajan
- Research and Analytics Department, Initiative for Financing Health and Human Development, Chennai, India
- Department of Research and Analytics, Bioinsilico Technologies, Chennai, India
| | - Mukhammad David Naimzada
- Laboratory of Public Health Indicators Analysis and Health Digitalization, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Experimental Surgery and Oncology Laboratory, Kursk State Medical University, Kursk, Russia
| | - Muhammad Naveed
- Department of Biotechnology, University of Central Punjab, Lahore, Pakistan
| | - Javad Nazari
- Department of Pediatrics, Arak University of Medical Sciences, Arak, Iran
| | - Rawlance Ndejjo
- Department of Disease Control and Environmental Health, Makerere University, Kampala, Uganda
| | - Ionut Negoi
- Department of General Surgery, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Department of General Surgery, Emergency Hospital of Bucharest, Bucharest, Romania
| | - Frida N Ngalesoni
- Ministry of Health, Community Development, Gender, Elderly and Children, Dar es Salaam, Tanzania
| | | | | | - Cuong Tat Nguyen
- Institute for Global Health Innovations, Duy Tan University, Hanoi, Vietnam
| | | | - Chukwudi A Nnaji
- South African Medical Research Council, Cape Town, South Africa
- School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Jean Jacques Noubiap
- Centre for Heart Rhythm Disorders, University of Adelaide, Adelaide, SA, Australia
| | - Virginia Nuñez-Samudio
- Unit of Microbiology and Public Health, Institute of Medical Sciences, Las Tablas, Panama
- Department of Public Health, Ministry of Health, Herrera, Panama
| | - Vincent Ebuka Nwatah
- Department of Pediatrics, National Hospital, Abuja, Nigeria
- Department of International Public Health, University of Liverpool, Liverpool, UK
| | - Bogdan Oancea
- Administrative and Economic Sciences Department, University of Bucharest, Bucharest, Romania
| | - Oluwakemi Ololade Odukoya
- Department of Community Health and Primary Care, University of Lagos, Idi Araba, Nigeria
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA
| | - Andrew T Olagunju
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- Department of Psychiatry, University of Lagos, Lagos, Nigeria
| | | | | | | | - Ahmed Omar Bali
- Diplomacy and Public Relations Department, University of Human Development, Sulaymaniyah, Iraq
| | - Obinna E Onwujekwe
- Department of Pharmacology and Therapeutics, University of Nigeria Nsukka, Enugu, Nigeria
| | | | - Nikita Otstavnov
- Laboratory of Public Health Indicators Analysis and Health Digitalization, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Stanislav S Otstavnov
- Laboratory of Public Health Indicators Analysis and Health Digitalization, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Department of Project Management, National Research University Higher School of Economics, Moscow, Russia
| | - Mayowa O Owolabi
- Department of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Medicine, University College Hospital, Ibadan, Ibadan, Nigeria
| | - P A Mahesh
- Department of Respiratory Medicine, Jagadguru Sri Shivarathreeswara Academy of Health Education and Research, Mysore, India
| | - Jagadish Rao Padubidri
- Department of Forensic Medicine and Toxicology, Manipal Academy of Higher Education, Manipal, India
| | - Adrian Pana
- Department of Statistics and Econometrics, Bucharest University of Economic Studies, Bucharest, Romania
- Department of Health Metrics, Center for Health Outcomes & Evaluation, Bucharest, Romania
| | - Ashok Pandey
- Research Department, Nepal Health Research Council, Kathmandu, Nepal
- Research Department, Public Health Research Society Nepal, Kathmandu, Nepal
| | | | | | - George C Patton
- Department of Pediatrics, University of Melbourne, Melbourne, VIC, Australia
- Population Health Theme, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Shrikant Pawar
- Department of Genetics, Yale University, New Haven, CT, USA
| | - Emmanuel K Peprah
- School of Global Public Health, New York University, New York, NY, USA
| | - Maarten J Postma
- University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- School of Economics and Business, University of Groningen, Groningen, Netherlands
| | - Liliana Preotescu
- National Institute of Infectious Diseases, Bucuresti, Romania
- Department of Infectious Diseases, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Zahiruddin Quazi Syed
- Department of Community Medicine, Datta Meghe Institute of Medical Sciences, Wardha, India
| | - Navid Rabiee
- School of Engineering, Macquarie University, Sydney, NSW, Australia
- Pohang University of Science and Technology, Pohang, South Korea
| | - Amir Radfar
- College of Medicine, University of Central Florida, Orlando, FL, USA
| | - Alireza Rafiei
- Department of Immunology, Mazandaran University of Medical Sciences, Sari, Iran
- Molecular and Cell Biology Research Center, Mazandaran University of Medical Sciences, Sari, Iran
| | - Fakher Rahim
- Metabolomics and Genomics Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Vafa Rahimi-Movaghar
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Amir Masoud Rahmani
- Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, Taiwan
| | - Kiana Ramezanzadeh
- Department of Pharmacology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Juwel Rana
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Research and Innovation Division, South Asian Institute for Social Transformation (SAIST), Dhaka, Bangladesh
| | - Chhabi Lal Ranabhat
- Research Department, Policy Research Institute, Kathmandu, Nepal
- Health and Public Policy Department, Global Center for Research and Development, Kathmandu, Nepal
| | - Sowmya J Rao
- Department of Oral Pathology, Sharavathi Dental College and Hospital, Shimogga, India
| | - David Laith Rawaf
- WHO Collaborating Centre for Public Health Education and Training, Imperial College London, London, UK
- University College London Hospitals, London, UK
| | - Salman Rawaf
- Department of Primary Care and Public Health, Imperial College London, London, UK
- Academic Public Health England, Public Health England, London, UK
| | | | | | - Nima Rezaei
- Research Center for Immunodeficiencies, Tehran University of Medical Sciences, Tehran, Iran
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Aziz Rezapour
- Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Mavra A Riaz
- Faculty of Business and Management, Universiti Sultan Zainal Abidin (Sultan Zainal Abidin University), Kuala Terengganu, Malaysia
| | - Ana Isabel Ribeiro
- Epidemiology Research Unit (EPIUnit), University of Porto, Porto, Portugal
| | - Jennifer M Ross
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Enrico Rubagotti
- African Genome Center, Mohammed VI Polytechnic University (UM6P), Ben Guerir, Morocco
- Centro de Investigaciones en Anomalías Congénitas y Enfermedades Raras (Center for Research in Congenital Anomalies and Rare Diseases), Universidad ICESI (ICESI University), Cali, Colombia
| | - Susan Fred Rumisha
- Malaria Atlas Project, Telethon Kids Institute, Perth, Australia
- Department of Health Statistics, National Institute for Medical Research, Dar es Salaam, Tanzania
| | | | - Sahar Saeedi Moghaddam
- Non-communicable Diseases Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Rajesh Sagar
- Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India
| | | | - Maitreyi Sahu
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Marwa Rashad Salem
- Public Health and Community Medicine Department, Cairo University, Giza, Egypt
| | - Hossein Samadi Kafil
- Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Abdallah M Samy
- Department of Entomology, Ain Shams University, Cairo, Egypt
| | - Benn Sartorius
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Brijesh Sathian
- Geriatric and Long Term Care Department, Hamad Medical Corporation, Doha, Qatar
- Faculty of Health & Social Sciences, Bournemouth University, Bournemouth, UK
| | - Abdul-Aziz Seidu
- Department of Population and Health, University of Cape Coast, Cape Coast, Ghana
- College of Public Health, Medical and Veterinary Sciences, James Cook University, QLD, Townsville, Australia
| | - Amira A Shaheen
- Public Health Division, An-Najah National University, Nablus, Palestine
| | | | - Morteza Shamsizadeh
- Faculty of Caring Science, Work Life, and Social Welfare, University of Borås, Borås, Sweden
| | | | - Jae Il Shin
- College of Medicine, Yonsei University, Seoul, South Korea
| | - Roman Shrestha
- Department of Internal Medicine, Yale University, New Haven, CT, USA
| | - Jasvinder A Singh
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
- Medicine Service, US Department of Veterans Affairs (VA), Birmingham, AL, USA
| | | | - Anna Aleksandrovna Skryabina
- Department of Infectious Diseases and Epidemiology, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Shahin Soltani
- Research Center for Environmental Determinants of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | | | - Takahiro Tabuchi
- Cancer Control Center, Osaka International Cancer Institute, Osaka, Japan
| | | | - Nuno Taveira
- University Institute "Egas Moniz", Monte da Caparica, Portugal
- Research Institute for Medicines, University of Lisbon, Lisbon, Portugal
| | - Fisaha Haile Tesfay
- School of Public Health, Mekelle University, Mekelle, Ethiopia
- Southgate Institute for Health and Society, Flinders University, Adelaide, SA, Australia
| | - Rekha Thapar
- Department of Community Medicine, Manipal Academy of Higher Education, Mangalore, India
| | - Marcos Roberto Tovani-Palone
- Department of Pathology and Legal Medicine, University of São Paulo, Ribeirão Preto, Brazil
- Modestum LTD, London, UK
| | | | - Chukwuma David Umeokonkwo
- Department of Community Medicine, Alex Ekwueme Federal University Teaching Hospital Abakaliki, Abakaliki, Nigeria
| | | | | | - Francesco S Violante
- Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
- Occupational Health Unit, Sant'Orsola Malpighi Hospital, Bologna, Italy
| | - Bay Vo
- Faculty of Information Technology, HUTECH University, Ho Chi Minh City, Vietnam
| | - Giang Thu Vu
- Center of Excellence in Behavioral Medicine, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
| | - Yohannes Dibaba Wado
- Population Dynamics and Sexual and Reproductive Health, African Population and Health Research Center, Nairobi, Kenya
| | - Yasir Waheed
- Foundation University Medical College, Foundation University Islamabad, Islamabad, Pakistan
| | - Richard G Wamai
- Department of Cultures, Societies and Global Studies, Northeastern University, Boston, MA, USA
- School of Public Health, University of Nairobi, Nairobi, Kenya
| | - Yanzhong Wang
- School of Population Health and Environmental Sciences, King's College London, London, UK
| | - Paul Ward
- Centre for Health Policy Research, Torrens University Australia, Adelaide, SA, Australia
| | | | - Katherine Wilson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Sanni Yaya
- School of International Development and Global Studies, University of Ottawa, Ottawa, ON, Canada
- The George Institute for Global Health, University of Oxford, Oxford, UK
| | - Paul Yip
- Centre for Suicide Research and Prevention, University of Hong Kong, Hong Kong, China
- Department of Social Work and Social Administration, University of Hong Kong, Hong Kong, China
| | - Naohiro Yonemoto
- Department of Neuropsychopharmacology, National Center of Neurology and Psychiatry, Kodaira, Japan
- Department of Public Health, Juntendo University, Tokyo, Japan
| | - Chuanhua Yu
- Department of Epidemiology and Biostatistics, Wuhan University, Wuhan, China
| | - Mikhail Sergeevich Zastrozhin
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Addictology Department, Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - Yunquan Zhang
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, China
| | | | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Laura Dwyer-Lindgren
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
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Gelibo T, Lulseged S, Eshetu F, Abdella S, Melaku Z, Ajiboye S, Demissie M, Solmo C, Ahmed J, Getaneh Y, Kaydos-Daniels SC, Abate E. Spatial distribution and determinants of HIV prevalence among adults in urban Ethiopia: Findings from the Ethiopia Population-based HIV Impact Assessment Survey (2017–2018). PLoS One 2022; 17:e0271221. [PMID: 35819961 PMCID: PMC9491827 DOI: 10.1371/journal.pone.0271221] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 06/24/2022] [Indexed: 11/19/2022] Open
Abstract
The design and evaluation of national HIV programs often rely on aggregated
national data, which may obscure localized HIV epidemics. In Ethiopia, even
though the national adult HIV prevalence has decreased, little information is
available about local areas and subpopulations. To inform HIV prevention efforts
for specific populations, we identified geographic locations and drivers of HIV
transmission. We used data from adults aged 15–64 years who participated in the
Ethiopian Population-based HIV Impact Assessment survey (October 2017–April
2018). Location-related information for the survey clusters was obtained from
the 2007 Ethiopia population census. Spatial autocorrelation of HIV prevalence
data were analyzed via a Global Moran’s I test. Geographically weighted
regression analysis was used to show the relationship of covariates. The finding
indicated that uncircumcised men in certain hotspot towns and divorced or
widowed individuals in hotspot woredas/towns might have contributed to the
average increase in HIV prevalence in the hotspot areas. Hotspot analysis
findings indicated that, localized, context-specific intervention efforts
tailored to at-risk populations, such as divorced or widowed women or
uncircumcised men, could decrease HIV transmission and prevalence in urban
Ethiopia.
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Affiliation(s)
- Terefe Gelibo
- ICAP in Ethiopia, Mailman School of Public Health, Columbia University,
Addis Ababa, Ethiopia
- * E-mail:
| | - Sileshi Lulseged
- ICAP in Ethiopia, Mailman School of Public Health, Columbia University,
Addis Ababa, Ethiopia
| | - Frehywot Eshetu
- Division of Global HIV & TB (DGHT), United States Centers for Disease
Control and Prevention (CDC), Addis Ababa, Ethiopia
| | - Saro Abdella
- TB/HIV Directorate, Ethiopia Public Health Institute (EPHI), Addis Ababa,
Ethiopia
| | - Zenebe Melaku
- ICAP in Ethiopia, Mailman School of Public Health, Columbia University,
Addis Ababa, Ethiopia
| | - Solape Ajiboye
- Division of Global HIV & TB (DGHT), United States Centers for Disease
Control and Prevention (CDC), Atlanta, GA, United States of
America
| | - Minilik Demissie
- TB/HIV Directorate, Ethiopia Public Health Institute (EPHI), Addis Ababa,
Ethiopia
| | - Chelsea Solmo
- ICAP at Columbia University, New York, New York, United States of
America
| | - Jelaludin Ahmed
- Division of Global HIV & TB (DGHT), United States Centers for Disease
Control and Prevention (CDC), Addis Ababa, Ethiopia
| | - Yimam Getaneh
- TB/HIV Directorate, Ethiopia Public Health Institute (EPHI), Addis Ababa,
Ethiopia
| | - Susan C. Kaydos-Daniels
- Division of Global HIV & TB (DGHT), United States Centers for Disease
Control and Prevention (CDC), Addis Ababa, Ethiopia
| | - Ebba Abate
- TB/HIV Directorate, Ethiopia Public Health Institute (EPHI), Addis Ababa,
Ethiopia
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Mapping HIV prevalence in Nigeria using small area estimates to develop a targeted HIV intervention strategy. PLoS One 2022; 17:e0268892. [PMID: 35675346 PMCID: PMC9176772 DOI: 10.1371/journal.pone.0268892] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 05/10/2022] [Indexed: 11/25/2022] Open
Abstract
Objective Although geographically specific data can help target HIV prevention and treatment strategies, Nigeria relies on national- and state-level estimates for policymaking and intervention planning. We calculated sub-state estimates along the HIV continuum of care in Nigeria. Design Using data from the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) (July–December 2018), we conducted a geospatial analysis estimating three key programmatic indicators: prevalence of HIV infection among adults (aged 15–64 years); antiretroviral therapy (ART) coverage among adults living with HIV; and viral load suppression (VLS) rate among adults living with HIV. Methods We used an ensemble modeling method called stacked generalization to analyze available covariates and a geostatistical model to incorporate the output from stacking as well as spatial autocorrelation in the modeled outcomes. Separate models were fitted for each indicator. Finally, we produced raster estimates of each indicator on an approximately 5×5-km grid and estimates at the sub-state/local government area (LGA) and state level. Results Estimates for all three indicators varied both within and between states. While state-level HIV prevalence ranged from 0.3% (95% uncertainty interval [UI]: 0.3%–0.5%]) to 4.3% (95% UI: 3.7%–4.9%), LGA prevalence ranged from 0.2% (95% UI: 0.1%–0.5%) to 8.5% (95% UI: 5.8%–12.2%). Although the range in ART coverage did not substantially differ at state level (25.6%–76.9%) and LGA level (21.9%–81.9%), the mean absolute difference in ART coverage between LGAs within states was 16.7 percentage points (range, 3.5–38.5 percentage points). States with large differences in ART coverage between LGAs also showed large differences in VLS—regardless of level of effective treatment coverage—indicating that state-level geographic targeting may be insufficient to address coverage gaps. Conclusion Geospatial analysis across the HIV continuum of care can effectively highlight sub-state variation and identify areas that require further attention in order to achieve epidemic control. By generating local estimates, governments, donors, and other implementing partners will be better positioned to conduct targeted interventions and prioritize resource distribution.
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Gutreuter S. Comparative performance of multiple-list estimators of key population size. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000155. [PMID: 35928219 PMCID: PMC9345571 DOI: 10.1371/journal.pgph.0000155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 12/16/2021] [Indexed: 06/15/2023]
Abstract
Estimates of the sizes of key populations (KPs) affected by HIV, including men who have sex with men, female sex workers and people who inject drugs, are required for targeting epidemic control efforts where they are most needed. Unfortunately, different estimators often produce discrepant results, and an objective basis for choice is lacking. This simulation study provides the first comparison of information-theoretic selection of loglinear models (LLM-AIC), Bayesian model averaging of loglinear models (LLM-BMA) and Bayesian nonparametric latent-class modeling (BLCM) for estimation of population size from multiple lists. Four hundred random samples from populations of size 1,000, 10,000 and 20,000, each including five encounter opportunities, were independently simulated using each of 30 data-generating models obtained from combinations of six patterns of variation in encounter probabilities and five expected per-list encounter probabilities, producing a total of 36,000 samples. Population size was estimated for each combination of sample and sequentially cumulative sets of 2-5 lists using LLM-AIC, LLM-BMA and BLCM. LLM-BMA and BLCM were quite robust and performed comparably in terms of root mean-squared error and bias, and outperformed LLM-AIC. All estimation methods produced uncertainty intervals which failed to achieve the nominal coverage, but LLM-BMA, as implemented in the dga R package produced the best balance of accuracy and interval coverage. The results also indicate that two-list estimation is unnecessarily vulnerable, and it is better to estimate the sizes of KPs based on at least three lists.
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Affiliation(s)
- Steve Gutreuter
- Division of Global HIV and TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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Nduva GM, Otieno F, Kimani J, McKinnon LR, Cholette F, Sandstrom P, Graham SM, Price MA, Smith AD, Bailey RC, Hassan AS, Esbjörnsson J, Sanders EJ. Phylogeographic Assessment Reveals Geographic Sources of HIV-1 Dissemination Among Men Who Have Sex With Men in Kenya. Front Microbiol 2022; 13:843330. [PMID: 35356525 PMCID: PMC8959701 DOI: 10.3389/fmicb.2022.843330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Accepted: 01/19/2022] [Indexed: 12/14/2022] Open
Abstract
HIV-1 transmission dynamics involving men who have sex with men (MSM) in Africa are not well understood. We investigated the rates of HIV-1 transmission between MSM across three regions in Kenya: Coast, Nairobi, and Nyanza. We analyzed 372 HIV-1 partial pol sequences sampled during 2006-2019 from MSM in Coast (N = 178, 47.9%), Nairobi (N = 137, 36.8%), and Nyanza (N = 57, 15.3%) provinces in Kenya. Maximum-likelihood (ML) phylogenetics and Bayesian inference were used to determine HIV-1 clusters, evolutionary dynamics, and virus migration rates between geographic regions. HIV-1 sub-subtype A1 (72.0%) was most common followed by subtype D (11.0%), unique recombinant forms (8.9%), subtype C (5.9%), CRF 21A2D (0.8%), subtype G (0.8%), CRF 16A2D (0.3%), and subtype B (0.3%). Forty-six clusters (size range 2-20 sequences) were found-half (50.0%) of which had evidence of extensive HIV-1 mixing among different provinces. Data revealed an exponential increase in infections among MSM during the early-to-mid 2000s and stable or decreasing transmission dynamics in recent years (2017-2019). Phylogeographic inference showed significant (Bayes factor, BF > 3) HIV-1 dissemination from Coast to Nairobi and Nyanza provinces, and from Nairobi to Nyanza province. Strengthening HIV-1 prevention programs to MSM in geographic locations with higher HIV-1 prevalence among MSM (such as Coast and Nairobi) may reduce HIV-1 incidence among MSM in Kenya.
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Affiliation(s)
- George M. Nduva
- Department of Translational Medicine, Lund University, Lund, Sweden
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | - Joshua Kimani
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
| | - Lyle R. McKinnon
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - Francois Cholette
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
- National Microbiology Laboratory at the JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Paul Sandstrom
- National Microbiology Laboratory at the JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Susan M. Graham
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Matt A. Price
- IAVI, San Francisco, CA, United States
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Adrian D. Smith
- Nuffield Department of Medicine, The University of Oxford, Oxford, United Kingdom
| | - Robert C. Bailey
- Nyanza Reproductive Health Society, Kisumu, Kenya
- Division of Epidemiology and Biostatistics, University of Illinois Chicago, Chicago, IL, United States
| | - Amin S. Hassan
- Department of Translational Medicine, Lund University, Lund, Sweden
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Joakim Esbjörnsson
- Department of Translational Medicine, Lund University, Lund, Sweden
- Nuffield Department of Medicine, The University of Oxford, Oxford, United Kingdom
| | - Eduard J. Sanders
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
- Nuffield Department of Medicine, The University of Oxford, Oxford, United Kingdom
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19
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Nduva GM, Otieno F, Kimani J, Wahome E, McKinnon LR, Cholette F, Majiwa M, Masika M, Mutua G, Anzala O, Graham SM, Gelmon L, Price MA, Smith AD, Bailey RC, Baele G, Lemey P, Hassan AS, Sanders EJ, Esbjörnsson J. Quantifying rates of HIV-1 flow between risk groups and geographic locations in Kenya: A country-wide phylogenetic study. Virus Evol 2022; 8:veac016. [PMID: 35356640 PMCID: PMC8962731 DOI: 10.1093/ve/veac016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/23/2022] [Accepted: 03/01/2022] [Indexed: 12/14/2022] Open
Abstract
In Kenya, HIV-1 key populations including men having sex with men (MSM), people who inject drugs (PWID) and female sex workers (FSW) are thought to significantly contribute to HIV-1 transmission in the wider, mostly heterosexual (HET) HIV-1 transmission network. However, clear data on HIV-1 transmission dynamics within and between these groups are limited. We aimed to empirically quantify rates of HIV-1 flow between key populations and the HET population, as well as between different geographic regions to determine HIV-1 'hotspots' and their contribution to HIV-1 transmission in Kenya. We used maximum-likelihood phylogenetic and Bayesian inference to analyse 4058 HIV-1 pol sequences (representing 0.3 per cent of the epidemic in Kenya) sampled 1986-2019 from individuals of different risk groups and regions in Kenya. We found 89 per cent within-risk group transmission and 11 per cent mixing between risk groups, cyclic HIV-1 exchange between adjoining geographic provinces and strong evidence of HIV-1 dissemination from (i) West-to-East (i.e. higher-to-lower HIV-1 prevalence regions), and (ii) heterosexual-to-key populations. Low HIV-1 prevalence regions and key populations are sinks rather than major sources of HIV-1 transmission in Kenya. Targeting key populations in Kenya needs to occur concurrently with strengthening interventions in the general epidemic.
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Affiliation(s)
- George M Nduva
- Department of Translational Medicine, Lund University, Faculty of Medicine, Lund University, Box 117 SE-221 00 Lund, Sweden
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
| | - Frederick Otieno
- Nyanza Reproductive Health Society, United Mall, P.O. Box 1764, Kisumu, Kenya
| | - Joshua Kimani
- Department of Medical Microbiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
| | - Elizabeth Wahome
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
| | - Lyle R McKinnon
- Department of Medical Microbiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Doris Duke Medical Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Private Bag X7, Congella 4013, South Africa
| | - Francois Cholette
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
- National Microbiology Laboratory at the JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, 745 Logan Avenue, Winnipeg, Canada
| | - Maxwell Majiwa
- Kenya Medical Research Institute/Center for Global Health Research, KEMRI-CGHR, P.O. Box 20778-00202, Kisumu, Kenya
| | - Moses Masika
- Faculty of Health Sciences 3RD Floor Wing B, KAVI Institute of Clinical Research, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya
| | - Gaudensia Mutua
- Faculty of Health Sciences 3RD Floor Wing B, KAVI Institute of Clinical Research, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya
| | - Omu Anzala
- Faculty of Health Sciences 3RD Floor Wing B, KAVI Institute of Clinical Research, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya
| | - Susan M Graham
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
- Department of Epidemiology, University of Washington, Office of the Chair, UW Box # 351619, Seattle, DC, USA
| | - Larry Gelmon
- Department of Medical Microbiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
| | - Matt A Price
- IAVI Global Headquarters, 125 Broad Street, 9th Floor, New York, NY 10004, USA
- Department of Epidemiology and Biostatistics, University of California, Mission Hall: Global Health & Clinical Sciences Building, 550 16th Street, 2nd Floor, San Francisco, CA 94158-2549, USA
| | - Adrian D Smith
- Nuffield Department of Medicine, The University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK
| | - Robert C Bailey
- Nyanza Reproductive Health Society, United Mall, P.O. Box 1764, Kisumu, Kenya
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago, 1603 W Taylor St, Chicago, IL 60612, USA
| | - Guy Baele
- KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Evolutionary and Computational Virology, Rega-Herestraat 49-box 1040, Leuven 3000, Belgium
| | - Philippe Lemey
- KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Evolutionary and Computational Virology, Rega-Herestraat 49-box 1040, Leuven 3000, Belgium
| | - Amin S Hassan
- Department of Translational Medicine, Lund University, Faculty of Medicine, Lund University, Box 117 SE-221 00 Lund, Sweden
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
| | - Eduard J Sanders
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
- Nuffield Department of Medicine, The University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK
| | - Joakim Esbjörnsson
- Department of Translational Medicine, Lund University, Faculty of Medicine, Lund University, Box 117 SE-221 00 Lund, Sweden
- Nuffield Department of Medicine, The University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK
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20
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HIV risk factors among adolescent and young adults: A geospatial–temporal analysis of Mozambique AIDS indicator survey data. Spat Spatiotemporal Epidemiol 2022; 41:100499. [DOI: 10.1016/j.sste.2022.100499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 01/12/2022] [Accepted: 03/02/2022] [Indexed: 11/22/2022]
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21
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Mootz JJ, Odejimi OA, Bhattacharya A, Kann B, Ettelbrick J, Mello M, Wainberg ML, Khoshnood K. Transactional sex work and HIV among women in conflict-affected Northeastern Uganda: a population-based study. Confl Health 2022; 16:8. [PMID: 35216637 PMCID: PMC8876753 DOI: 10.1186/s13031-022-00441-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 02/10/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Armed conflict and the HIV pandemic are significant global health issues. Evidence of the association between armed conflict and HIV infection has been conflicting. Our objective was to examine the role of mediating risk factors, such as engagement in transactional sex work, to elucidate the relation between armed conflict and HIV infection. METHODS We used multistage sampling across three Northeastern Ugandan districts to randomly select 605 women aged 13 to 49 to answer cross-sectional surveys from January to May of 2016. We used multivariate logistic regression model with R 4.0.3 to examine if exposure to armed conflict has an indirect effect on reporting having an HIV-positive serostatus through engagement in transactional sex work. Age and district residence were included as covariates. RESULTS Exposure to armed conflict β = .16, SE = .04, p < .05, OR = 1.17, 95% [CI .08, .23] was significantly associated with reporting a HIV-positive serostatus. For each 1-unit increase in exposure to armed conflict (i.e., additional type of armed conflict exposure), there was a 17% increase in the odds of reporting a HIV-positive serostatus. Engagement in transactional sex work was not associated with reporting a HIV-positive serostatus β = .04, SE = .05, p = .37, 95% [CI - .051, .138]. We found district of residence, age, and interaction effects. CONCLUSIONS Although exposure to armed was associated with reporting an HIV-positive serostatus, this relationship was not mediated by engagement in transactional sex. Further research is needed on risk factors that mediate this relationship. The likelihood of reporting a HIV-positive serostatus increased with each additional type of exposure to armed conflict. Thus, screening for exposure to multiple traumatic stressors should occur in HIV prevention settings. Healthcare services that are trauma-informed and consider mental distress would likely improve HIV outcomes.
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Affiliation(s)
- Jennifer J Mootz
- Department of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, 10032, USA.
- New York State Psychiatric Institute, 1051 Riverside Drive, Kolb 171, New York, NY, 10032, USA.
| | - Omolola A Odejimi
- Educational Psychology, Texas Tech University, 2500 Broadway, Lubbock, TX, 79409, USA
| | | | - Bianca Kann
- Department of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, 10032, USA
- New York State Psychiatric Institute, 1051 Riverside Drive, Kolb 171, New York, NY, 10032, USA
| | - Julia Ettelbrick
- The New School, Eugene Lang College, 72 5th Avenue, New York, NY, 10011, USA
| | - Milena Mello
- Department of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, 10032, USA
- New York State Psychiatric Institute, 1051 Riverside Drive, Kolb 171, New York, NY, 10032, USA
| | - Milton L Wainberg
- Department of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY, 10032, USA
- New York State Psychiatric Institute, 1051 Riverside Drive, Kolb 171, New York, NY, 10032, USA
| | - Kaveh Khoshnood
- School of Public Health, Yale University, 60 College St, New Haven, CT, 06510, USA
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22
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Jia KM, Eilerts H, Edun O, Lam K, Howes A, Thomas ML, Eaton JW. Risk scores for predicting HIV incidence among adult heterosexual populations in sub-Saharan Africa: a systematic review and meta-analysis. J Int AIDS Soc 2022; 25:e25861. [PMID: 35001515 PMCID: PMC8743366 DOI: 10.1002/jia2.25861] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 12/06/2021] [Indexed: 11/24/2022] Open
Abstract
Introduction Several HIV risk scores have been developed to identify individuals for prioritized HIV prevention in sub‐Saharan Africa. We systematically reviewed HIV risk scores to: (1) identify factors that consistently predicted incident HIV infection, (2) review inclusion of community‐level HIV risk in predictive models and (3) examine predictive performance. Methods We searched nine databases from inception until 15 February 2021 for studies developing and/or validating HIV risk scores among the heterosexual adult population in sub‐Saharan Africa. Studies not prospectively observing seroconversion or recruiting only key populations were excluded. Record screening, data extraction and critical appraisal were conducted in duplicate. We used random‐effects meta‐analysis to summarize hazard ratios and the area under the receiver‐operating characteristic curve (AUC‐ROC). Results From 1563 initial search records, we identified 14 risk scores in 13 studies. Seven studies were among sexually active women using contraceptives enrolled in randomized‐controlled trials, three among adolescent girls and young women (AGYW) and three among cohorts enrolling both men and women. Consistently identified HIV prognostic factors among women were younger age (pooled adjusted hazard ratio: 1.62 [95% confidence interval: 1.17, 2.23], compared to above 25), single/not cohabiting with primary partners (2.33 [1.73, 3.13]) and having sexually transmitted infections (STIs) at baseline (HSV‐2: 1.67 [1.34, 2.09]; curable STIs: 1.45 [1.17; 1.79]). Among AGYW, only STIs were consistently associated with higher incidence, but studies were limited (n = 3). Community‐level HIV prevalence or unsuppressed viral load strongly predicted incidence but was only considered in 3 of 11 multi‐site studies. The AUC‐ROC ranged from 0.56 to 0.79 on the model development sets. Only the VOICE score was externally validated by multiple studies, with pooled AUC‐ROC 0.626 [0.588, 0.663] (I2: 64.02%). Conclusions Younger age, non‐cohabiting and recent STIs were consistently identified as predicting future HIV infection. Both community HIV burden and individual factors should be considered to quantify HIV risk. However, HIV risk scores had only low‐to‐moderate discriminatory ability and uncertain generalizability, limiting their programmatic utility. Further evidence on the relative value of specific risk factors, studies populations not restricted to “at‐risk” individuals and data outside South Africa will improve the evidence base for risk differentiation in HIV prevention programmes. PROSPERO Number CRD42021236367
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Affiliation(s)
- Katherine M Jia
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Hallie Eilerts
- Department of Population Health, The London School of Hygiene and Tropical Medicine, London, UK
| | - Olanrewaju Edun
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Kevin Lam
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Adam Howes
- Department of Mathematics, Imperial College London, London, UK
| | - Matthew L Thomas
- Joint Centre for Excellence in Environmental Intelligence, University of Exeter & Met Office, Exeter, UK
| | - Jeffrey W Eaton
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
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23
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Yuan D, Yu B, Liang S, Fei T, Tang H, Kang R, Li Y, Ye L, Jia P, Yang S. HIV-1 genetic transmission networks among people living with HIV/AIDS in Sichuan, China: a genomic and spatial epidemiological analysis. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 18:100318. [PMID: 35024655 PMCID: PMC8669382 DOI: 10.1016/j.lanwpc.2021.100318] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 09/11/2021] [Accepted: 10/15/2021] [Indexed: 12/31/2022]
Abstract
BACKGROUND Spatialized HIV genetic transmission networks can help understand dynamic changes of HIV-1 at the regional level. This study aimed to combine genomic, epidemiological, and spatial data to investigate the patterns of the HIV-1 epidemic at both individual and regional levels among people living with HIV (PLWH) with virological failure of antiretroviral therapy (ART). METHODS We evaluated the transmission patterns of 5,790 PLWH with identified pol sequences of the five main HIV-1 subtypes (B, CRF08_BC, CRF85_BC, CRF07_BC, and CRF01_AE) in Sichuan Province, China. A phylogenetic cluster was defined as a group of sequences with genetically similar HIV strains, with all phylogenetic clusters forming an HIV-1 genetic transmission network for each subtype. Logistic regression was used to identify the potential risk factors for phylogenetic clustering. Spatial analysis was applied to demonstrate the geographic patterns of phylogenetic clustering rates; intensity matrices and flow maps were made to demonstrate the intensity of transmission within and between cities. FINDINGS There were 2,159 (37.3%) of 5,790 PLWH, distributed in 452 phylogenetic clusters. Some individual clinical and behavioral factors were associated with phylogenetic clustering, including a viral load of >50,000 copies/ml (OR=1.16, 95%CI=1.02-1.33), infection of other sexually transmitted diseases (OR=1.38, 95%CI=1.12-1.69), and ≥5 non-marital sexual partners (OR=1.25, 95%CI=1.03-1.51), while >3 years of treatment since the initial ART was associated with less likelihood of phylogenetic clustering (OR=0.82, 95%CI=0.70-0.97). The phylogenetic clustering rates varied regionally and were highest in the central region of Sichuan, especially for subtype CRF08_BC. The significant spatial clusters of high and low phylogenetic clustering rates were detected in the east (Dazhou for B; Zigong and Luzhou for CFR08_BC) and west (Yaan and Ganzi for CRF07_BC), respectively. The proportion of intercity transmission varied across cities from 0.14 (Yibin) and 1.00 (Ganzi). Stronger intercity transmission than average existed between some cities, e.g., between Deyang and Neijiang. CRF07_BC was the most widespread subtype between cities, and CRF85_BC (a novel HIV-1 subtype) showed strong intercity transmission (e.g., between Yibin and Guangan). INTERPRETATION The phylogenetic clustering rates and intercity connections of HIV-1 have varied geographically, possibly due to varying human mobility, traffic convenience, and economic activities. Our findings enhanced the understanding of the dynamics of HIV-1 transmission from individual to city level, and demonstrated a novel cross-disciplinary (epidemiological, genetic, and spatial) approach by which we identified high-risk populations and areas. Our approach could be adapted to other regions for precision public health interventions. FUNDING The National Natural Science Foundation of China, Sichuan Science and Technology Program, Project of Sichuan Provincial Health Committee, Science and Technology Project of Sichuan Provincial Health Committee, Wuhan University 351 Talent Program, 2020, and the International Institute of Spatial Lifecourse Epidemiology (ISLE).
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Affiliation(s)
- Dan Yuan
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Bin Yu
- West China Second University Hospital, Sichuan University, Chengdu, China
| | - Shu Liang
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Teng Fei
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Houlin Tang
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Rui Kang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Yiping Li
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Li Ye
- Center for AIDS/STD Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China
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24
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Ngure K, Mugo NR, Bukusi EA, Kiptinness C, Oware K, Gakuo S, Musinguzi N, Pyra M, Garrison L, Baeten JM, Haberer JE. Pills, Injections, Rings, or Implants? PrEP Formulation Preferences of PrEP-Experienced African Women for HIV Prevention. J Acquir Immune Defic Syndr 2021; 88:e30-e32. [PMID: 34446676 PMCID: PMC8556312 DOI: 10.1097/qai.0000000000002793] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Kenneth Ngure
- Department of Community Health, Jomo Kenyatta University of Agriculture and Technology
- Department of Global Health, University of Washington, Seattle, USA
| | - Nelly R. Mugo
- Department of Global Health, University of Washington, Seattle, USA
- Center for Clinical Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Elizabeth A. Bukusi
- Department of Global Health, University of Washington, Seattle, USA
- Center for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
- Department of Obstetrics and Gynecology, University of Washington, Seattle, USA
| | | | - Kevin Oware
- Center for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Stephen Gakuo
- Center for Clinical Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Nicholas Musinguzi
- Global Health Collaborative, Mbarara University of Science and Technology, Mbarara, Uganda
| | | | - Lindsey Garrison
- Massachusetts General Hospital, Center for Global Health, Boston, MA, USA
| | - Jared M. Baeten
- Department of Global Health, University of Washington, Seattle, USA
- Department of Epidemiology, University of Washington, Seattle, USA
- Department of Medicine, University of Washington, Seattle, USA
- Gilead, Foster City, CA, United States
| | - Jessica E. Haberer
- Massachusetts General Hospital, Center for Global Health, Boston, MA, USA
- Harvard Medical School, Department of Medicine, Boston, MA, USA
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25
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Fraser H, Borquez A, Stone J, Abramovitz D, Brouwer KC, Goodman-Meza D, Hickman M, Patterson TL, Silverman J, Smith L, Strathdee SA, Martin NK, Vickerman P. Overlapping Key Populations and HIV Transmission in Tijuana, Mexico: A Modelling Analysis of Epidemic Drivers. AIDS Behav 2021; 25:3814-3827. [PMID: 34216285 PMCID: PMC8560668 DOI: 10.1007/s10461-021-03361-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/20/2021] [Indexed: 12/18/2022]
Abstract
Tijuana, Mexico, has a concentrated HIV epidemic among overlapping key populations (KPs) including people who inject drugs (PWID), female sex workers (FSW), their male clients, and men who have sex with men (MSM). We developed a dynamic HIV transmission model among these KPs to determine the extent to which their unmet prevention and treatment needs is driving HIV transmission. Over 2020-2029 we estimated the proportion of new infections acquired in each KP, and the proportion due to their unprotected risk behaviours. We estimate that 43.7% and 55.3% of new infections are among MSM and PWID, respectively, with FSW and their clients making-up < 10% of new infections. Projections suggest 93.8% of new infections over 2020-2029 will be due to unprotected sex between MSM or unsafe injecting drug use. Prioritizing interventions addressing sexual and injecting risks among MSM and PWID are critical to controlling HIV in Tijuana.
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Affiliation(s)
- Hannah Fraser
- Oakfield House, Population Health Sciences - Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
| | - Annick Borquez
- School of Medicine, University of California San Diego, San Diego, USA
| | - Jack Stone
- Oakfield House, Population Health Sciences - Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | | | | | - David Goodman-Meza
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Matthew Hickman
- Oakfield House, Population Health Sciences - Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | | | - Jay Silverman
- School of Medicine, University of California San Diego, San Diego, USA
| | - Laramie Smith
- School of Medicine, University of California San Diego, San Diego, USA
| | | | - Natasha K Martin
- Oakfield House, Population Health Sciences - Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
- School of Medicine, University of California San Diego, San Diego, USA
| | - Peter Vickerman
- Oakfield House, Population Health Sciences - Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
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26
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Muttai H, Guyah B, Achia T, Musingila P, Nakhumwa J, Oyoo R, Olweny W, Odeny R, Ohaga S, Agot K, Oruenjo K, Awino B, Joseph RH, Miruka F, Zielinski-Gutierrez E. Mapping geographic clusters of new HIV diagnoses to inform granular-level interventions for HIV epidemic control in western Kenya. BMC Public Health 2021; 21:1926. [PMID: 34688267 PMCID: PMC8542332 DOI: 10.1186/s12889-021-11890-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 09/30/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND As countries make progress towards HIV epidemic control, there is increasing need to identify finer geographic areas to target HIV interventions. We mapped geographic clusters of new HIV diagnoses, and described factors associated with HIV-positive diagnosis, in order to inform targeting of HIV interventions to finer geographic areas and sub-populations. METHODS We analyzed data for clients aged > 15 years who received home-based HIV testing as part of a routine public health program between May 2016 and July 2017 in Siaya County, western Kenya. Geospatial analysis using Kulldorff's spatial scan statistic was used to detect geographic clusters (radius < 5 kilometers) of new HIV diagnoses. Factors associated with new HIV diagnosis were assessed in a spatially-integrated Bayesian hierarchical model. RESULTS Of 268,153 clients with HIV test results, 2906 (1.1%) were diagnosed HIV-positive. We found spatial variation in the distribution of new HIV diagnoses, and identified nine clusters in which the number of new HIV diagnoses was significantly (1.56 to 2.64 times) higher than expected. Sub-populations with significantly higher HIV-positive yield identified in the multivariable spatially-integrated Bayesian model included: clients aged 20-24 years [adjusted relative risk (aRR) 3.45, 95% Bayesian Credible Intervals (CI) 2.85-4.20], 25-35 years (aRR 4.76, 95% CI 3.92-5.81) and > 35 years (aRR 2.44, 95% CI 1.99-3.00); those in polygamous marriage (aRR 1.84, 95% CI 1.55-2.16), or separated/divorced (aRR 3.36, 95% CI 2.72-4.08); and clients who reported having never been tested for HIV (aRR 2.35, 95% CI 2.02-2.72), or having been tested > 12 months ago (aRR 1.53, 95% CI 1.41-1.66). CONCLUSION Our study used routine public health program data to identify granular geographic clusters of higher new HIV diagnoses, and sub-populations with higher HIV-positive yield in the setting of a generalized HIV epidemic. In order to target HIV testing and prevention interventions to finer granular geographic areas for maximal epidemiologic impact, integrating geospatial analysis into routine public health programs can be useful.
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Affiliation(s)
- Hellen Muttai
- Division of Global HIV & TB, United States Centers for Disease Control and Prevention, 00621, Nairobi, Kenya.
| | - Bernard Guyah
- School of Public Health, Maseno University, Kisumu, Kenya
| | - Thomas Achia
- Division of Global HIV & TB, United States Centers for Disease Control and Prevention, 00621, Nairobi, Kenya
| | - Paul Musingila
- Division of Global HIV & TB, United States Centers for Disease Control and Prevention, 00621, Nairobi, Kenya
| | - Jesse Nakhumwa
- Impact Research and Development Organization, Kisumu, Kenya
| | - Rose Oyoo
- Impact Research and Development Organization, Kisumu, Kenya
| | | | | | - Spala Ohaga
- Impact Research and Development Organization, Kisumu, Kenya
| | - Kawango Agot
- Impact Research and Development Organization, Kisumu, Kenya
| | | | - Bob Awino
- Siaya County Department of Health, Siaya, Kenya
| | - Rachael H Joseph
- Division of Global HIV & TB, United States Centers for Disease Control and Prevention, 00621, Nairobi, Kenya
| | - Fredrick Miruka
- Division of Global HIV & TB, United States Centers for Disease Control and Prevention, 00621, Nairobi, Kenya
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27
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Fraser H, Stone J, Wisse E, Sambu V, Mfisi P, Duran IJ, Soriano MA, Walker JG, Makere N, Luhmann N, Kafura W, Nouvellet M, Ragi A, Mundia B, Vickerman P. Modelling the impact of HIV and HCV prevention and treatment interventions for people who inject drugs in Dar es Salaam, Tanzania. J Int AIDS Soc 2021; 24:e25817. [PMID: 34661964 PMCID: PMC8522890 DOI: 10.1002/jia2.25817] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 08/19/2021] [Indexed: 11/25/2022] Open
Abstract
Introduction People who inject drugs (PWID) in Dar es Salaam, Tanzania, have a high prevalence of HIV and hepatitis C virus (HCV). While needle and syringe programmes (NSP), opioid agonist therapy (OAT) and anti‐retroviral therapy (ART) are available in Tanzania, their coverage is sub‐optimal. We assess the impact of existing and scaled up harm reduction (HR) interventions on HIV and HCV transmission among PWID in Dar es Salaam. Methods An HIV and HCV transmission model among PWID in Tanzania was calibrated to data over 2006–2018 on HIV (∼30% and ∼67% prevalence in males and females in 2011) and HCV prevalence (∼16% in 2017), numbers on HR interventions (5254 ever on OAT in 2018, 766–1479 accessing NSP in 2017) and ART coverage (63.1% in 2015). We evaluated the impact of existing interventions in 2019 and impact by 2030 of scaling‐up the coverage of OAT (to 50% of PWID), NSP (75%, both combined termed “full HR”) and ART (81% with 90% virally suppressed) from 2019, reducing sexual HIV transmission by 50%, and/or HCV‐treating 10% of PWID infected with HCV annually. Results The model projects HIV and HCV prevalence of 19.0% (95% credibility interval: 16.4–21.2%) and 41.0% (24.4–49.0%) in 2019, respectively. For HIV, 24.6% (13.6–32.6%) and 70.3% (59.3–77.1%) of incident infections among male and female PWID are sexually transmitted, respectively. Due to their low coverage (22.8% for OAT, 16.3% for NSP in 2019), OAT and NSP averted 20.4% (12.9–24.7%) of HIV infections and 21.7% (17.0–25.2%) of HCV infections in 2019. Existing ART (68.5% coverage by 2019) averted 48.1% (29.7–64.3%) of HIV infections in 2019. Scaling up to full HR will reduce HIV and HCV incidence by 62.6% (52.5–74.0%) and 81.4% (56.7–81.4%), respectively, over 2019–2030; scaled up ART alongside full HR will decrease HIV incidence by 66.8% (55.6–77.5%), increasing to 81.5% (73.7–87.5%) when sexual risk is also reduced. HCV‐treatment alongside full HR will decrease HCV incidence by 92.4% (80.7–95.8%) by 2030. Conclusions Combination interventions, including sexual risk reduction and HCV treatment, are needed to eliminate HCV and HIV among PWID in Tanzania.
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Affiliation(s)
- Hannah Fraser
- Population HealthSciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jack Stone
- Population HealthSciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Veryeh Sambu
- National AIDS Control Programmes, Dar es Salaam, Tanzania
| | - Peter Mfisi
- The Drug Control and Enforcement Authority, Prime Ministers Office, Dar es Salaam, Tanzania
| | | | | | - Josephine G Walker
- Population HealthSciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nobelrich Makere
- Tanzania Council for Social Development (TACOSODE), Dar es Salaam, Tanzania
| | | | - William Kafura
- Tanzania Commission for AIDS (TACAIDS), Dar es Salaam, Tanzania
| | | | - Allan Ragi
- Kenya AIDS NGO Consortium, Nairobi, Kenya
| | | | - Peter Vickerman
- Population HealthSciences, Bristol Medical School, University of Bristol, Bristol, UK
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28
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Zhu Q, JiKe C, Xu C, Liang S, Yu G, Wang J, Xiao L, Liu P, Chen M, Guan P, Liu Z, Jin C. A New Strategy to Quantitatively Identify Hot-Spot Areas in Growth of New HIV Infections for Targeted Interventions. Front Public Health 2021; 9:680867. [PMID: 34322472 PMCID: PMC8310914 DOI: 10.3389/fpubh.2021.680867] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/14/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Previous geographic studies of HIV infection have usually used prevalence data, which cannot indicate the hot-spot areas of current transmission. To develop quantitative analytic measures for accurately identifying hot-spot areas in growth of new HIV infection, we investigated the geographic distribution features of recent HIV infection and long-term HIV infection using data from a whole-population physical examination in four key counties in Liangshan prefecture, which are most severely affected by HIV in China. Methods: Through a whole-population physical examination during November 2017- June 2018 in the four key counties, a total of 5,555 HIV cases were diagnosed and 246 cases were classified as recently infected by laboratory HIV recency tests. The geospatial patterns of recent and long-term HIV infected cases were compared using ordinary least squares regression and Geodetector. Further, geospatial-heterogeneity was quantified and indicated using a residual map to visualize hot-spot areas where new infection is increasing. Results: The geographic location of HIV cases showed an uneven distribution along major roads and clustered at road intersections. The geographic mapping showed that several areas were clustered with more recently infected HIV cases than long-term infected cases. The quantitative analyses showed that the geospatial asymmetry between recent and long-term HIV infection was 0.30 and 0.31 in ordinary least squares regression and Geodetector analysis, respectively. The quantitative analyses found twenty-three townships showing an increase in the number of recent infections. Conclusions: Quantitative analysis of geospatial-heterogeneous areas by comparing between recent and long-term HIV infections allows accurate identification of hot-spot areas where new infections are expanding, which can be used as a potent methodological tool to guide targeted interventions and curb the spread of the epidemic.
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Affiliation(s)
- Qiyu Zhu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.,Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China
| | - Chunnong JiKe
- Liangshan Prefecture Center for Disease Control and Prevention, Xichang, China
| | - Chengdong Xu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Shu Liang
- Sichuan Provincial Center for Disease Control and Prevention, Chengdu, China
| | - Gang Yu
- Liangshan Prefecture Center for Disease Control and Prevention, Xichang, China
| | - Ju Wang
- Liangshan Prefecture Center for Disease Control and Prevention, Xichang, China
| | - Lin Xiao
- Liangshan Prefecture Center for Disease Control and Prevention, Xichang, China
| | - Ping Liu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Meibin Chen
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China
| | - Zhongfu Liu
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Cong Jin
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Abstract
HIV incidence has recently been in decline across some of the most intense epidemics in sub-Saharan Africa due to the scale-up of prevention and transmission-blocking treatments. Understanding whether declines in incidence are being felt equally across age and gender can help prioritize demographic groups where more effort is needed to lower transmission. We found that HIV incidence has declined disproportionately in the youngest men and women in a population with the highest HIV prevalence in the world. Shifts in the age distribution of risk may be the consequence of aging prevalence, prioritized prevention to younger individuals, and delays in age at infection from reduced overall force of infection. Our results highlight the need to expand age targets for HIV prevention. Recent declines in adult HIV-1 incidence have followed the large-scale expansion of antiretroviral therapy and primary HIV prevention across high-burden communities of sub-Saharan Africa. Mathematical modeling suggests that HIV risk will decline disproportionately in younger adult age-groups as interventions scale, concentrating new HIV infections in those >age 25 over time. Yet, no empirical data exist to support these projections. We conducted a population-based cohort study over a 16-y period (2004 to 2019), spanning the early scale-up of antiretroviral therapy and voluntary medical male circumcision, to estimate changes in the age distribution of HIV incidence in a hyperepidemic region of KwaZulu-Natal, South Africa, where adult HIV incidence has recently declined. Median age of HIV seroconversion increased by 5.5 y in men and 3.0 y in women, and the age of peak HIV incidence increased by 5.0 y in men and 2.0 y in women. Incidence declined disproportionately among young men (64% in men 15 to 19, 68% in men 20 to 24, and 46% in men 25 to 29) and young women (44% in women 15 to 19, 24% in women 20 to 24) comparing periods pre- versus post-universal test and treat. Incidence was stable (<20% change) in women aged 30 to 39 and men aged 30 to 34. Age shifts in incidence occurred after 2012 and were observed earlier in men than in women. These results provide direct epidemiological evidence of the changing demographics of HIV risk in sub-Saharan Africa in the era of large-scale treatment and prevention. More attention is needed to address lagging incidence decline among older individuals.
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30
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Mishra S, Silhol R, Knight J, Phaswana‐Mafuya R, Diouf D, Wang L, Schwartz S, Boily M, Baral S. Estimating the epidemic consequences of HIV prevention gaps among key populations. J Int AIDS Soc 2021; 24 Suppl 3:e25739. [PMID: 34189863 PMCID: PMC8242976 DOI: 10.1002/jia2.25739] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 04/22/2021] [Accepted: 04/28/2021] [Indexed: 11/07/2022] Open
Abstract
INTRODUCTION HIV epidemic appraisals are used to characterize heterogeneity and inequities in the context of the HIV pandemic and the response. However, classic measures used in appraisals have been shown to underestimate disproportionate risks of onward transmission, particularly among key populations. In response, a growing number of modelling studies have quantified the consequences of unmet prevention and treatment needs (prevention gaps) among key populations as a transmission population attributable fraction over time (tPAFt ). To aid its interpretation and use by programme implementers and policy makers, we outline and discuss a conceptual framework for understanding and estimating the tPAFt via transmission modelling as a measure of onward transmission risk from HIV prevention gaps; and discuss properties of the tPAFt . DISCUSSION The distribution of onward transmission risks may be defined by who is at disproportionate risk of onward transmission, and under which conditions. The latter reflects prevention gaps, including secondary prevention via treatment: the epidemic consequences of which may be quantified by the tPAFt . Steps to estimating the tPAFt include parameterizing the acquisition and onward transmission risks experienced by the subgroup of interest, defining the most relevant counterfactual scenario, and articulating the time-horizon of analyses and population among whom to estimate the relative difference in cumulative transmissions; such steps could reflect programme-relevant questions about onward transmission risks. Key properties of the tPAFt include larger onward transmission risks over longer time-horizons; seemingly mutually exclusive tPAFt measures summing to greater than 100%; an opportunity to quantify the magnitude of disproportionate onward transmission risks with a per-capita tPAFt ; and that estimates are conditional on what has been achieved so far in reducing prevention gaps and maintaining those conditions moving forward as the status quo. CONCLUSIONS The next generation of HIV epidemic appraisals has the potential to support a more specific HIV response by characterizing heterogeneity in disproportionate risks of onward transmission which are defined and conditioned on the past, current and future prevention gaps across subsets of the population.
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Affiliation(s)
- Sharmistha Mishra
- Department of MedicineUniversity of TorontoTorontoONCanada
- Institute of Medical SciencesUniversity of TorontoTorontoONCanada
- Institute of Health Policy, Management and EvaluationUniversity of TorontoTorontoOnCanada
- Li Ka Shing Knowledge InstituteSt. Michael’s HospitalUnity Health TorontoTorontoONCanada
| | - Romain Silhol
- MRC Centre for Global Infectious Disease AnalysisSchool of Public HealthImperial College LondonLondonUnited Kingdom
| | - Jesse Knight
- Institute of Medical SciencesUniversity of TorontoTorontoONCanada
- Li Ka Shing Knowledge InstituteSt. Michael’s HospitalUnity Health TorontoTorontoONCanada
| | | | | | - Linwei Wang
- Li Ka Shing Knowledge InstituteSt. Michael’s HospitalUnity Health TorontoTorontoONCanada
| | - Sheree Schwartz
- Department of EpidemiologyJohns Hopkins School of Public HealthBaltimoreMDUSA
| | - Marie‐Claude Boily
- MRC Centre for Global Infectious Disease AnalysisSchool of Public HealthImperial College LondonLondonUnited Kingdom
| | - Stefan Baral
- Department of EpidemiologyJohns Hopkins School of Public HealthBaltimoreMDUSA
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Kim H, Tanser F, Tomita A, Vandormael A, Cuadros DF. Beyond HIV prevalence: identifying people living with HIV within underserved areas in South Africa. BMJ Glob Health 2021; 6:bmjgh-2020-004089. [PMID: 33883186 PMCID: PMC8061852 DOI: 10.1136/bmjgh-2020-004089] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 03/10/2021] [Accepted: 03/12/2021] [Indexed: 11/04/2022] Open
Abstract
INTRODUCTION Despite progress towards the Joint United Nations Programme on HIV/AIDS 95-95-95 targets, South Africa is still suffering from one of the largest HIV epidemics globally. In this study, we generated high-resolution HIV prevalence maps and identified people living with HIV (PLHIV) in underserved areas to provide essential information for the optimal allocation of HIV-related services. METHODS The data come from the South Africa Demographic and Health Survey conducted in 2016 and spatial variables from other published literature. We produced high-resolution maps of HIV prevalence and underserved areas, defined as a greater than 30 min travel time to the nearest healthcare facility. Using these maps and the population density, we mapped PLHIV and the PLHIV within underserved areas for 30, 60 and 120 min thresholds. RESULTS There was substantial geographic variation in HIV prevalence, ranging from 1.4% to 24.2%, with a median of 11.5% for men, and from 2.1% to 48.1%, with a median of 20.6% for women. Gauteng province showed the highest density for both HIV prevalence and PLHIV. 80% of all areas in the country were identified as underserved areas (30 min threshold), which contained more than 16% and 20% of the total men and women living with HIV, respectively. KwaZulu-Natal province had the largest number of PLHIV in underserved areas (30 min threshold) and showed less than one healthcare facility per 1000 PLHIV. CONCLUSION Our study showed extensive spatial variation of HIV prevalence and significant numbers of PLHIV in underserved areas in South Africa. Moreover, we identified locations where HIV-related services need to be intensified to reach the ~1.5 million PLHIV in underserved areas, particularly in KwaZulu-Natal province, with less than one healthcare facility per 1000 PLHIV.
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Affiliation(s)
- Hana Kim
- Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, Ohio, USA.,Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, Ohio, USA
| | - Frank Tanser
- Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, UK.,Africa Health Research Institute, KwaZulu-Natal, South Africa.,School of Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.,Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Andrew Tomita
- Centre for Rural Health, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.,KwaZulu-Natal Research Innovation and Sequencing Platform, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Alain Vandormael
- Heidelberg Institute of Global Health (HIGH), Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Diego F Cuadros
- Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, Ohio, USA .,Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, Ohio, USA
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Nduva GM, Nazziwa J, Hassan AS, Sanders EJ, Esbjörnsson J. The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review. Viruses 2021; 13:1174. [PMID: 34205246 PMCID: PMC8235305 DOI: 10.3390/v13061174] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/09/2021] [Accepted: 06/10/2021] [Indexed: 12/19/2022] Open
Abstract
To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.
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Affiliation(s)
- George M. Nduva
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
| | - Jamirah Nazziwa
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
| | - Amin S. Hassan
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
| | - Eduard J. Sanders
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, The University of Oxford, Oxford OX1 2JD, UK
| | - Joakim Esbjörnsson
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, The University of Oxford, Oxford OX1 2JD, UK
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Wand H, Morris N, Reddy T. Temporal and spatial monitoring of HIV prevalence and incidence rates using geospatial models: Results from South African women. Spat Spatiotemporal Epidemiol 2021; 37:100413. [PMID: 33980413 DOI: 10.1016/j.sste.2021.100413] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 12/15/2020] [Accepted: 02/01/2021] [Indexed: 11/18/2022]
Abstract
Generalized additive models (GAMs) were used to predict non-linear distributions of HIV prevalence and incidence based on semiparametric methods. The GAMs also provide smooth intensity maps by projecting the predicted HIV prevalence (or incidence) into the contour maps. Two sets of geo-coded data sources were used: (1) population-based cross-sectional data from 10,928 women who participated in four HIV behavioral surveys (2002-2017), (2) clinic-based longitudinal data from 7,557 women who resided in KwaZulu-Natal (2002-2016). Model estimated degrees of freedoms were 15.84,12.17,7.64 and 15.08 (2002-2012), indicating substantial spatial variations in HIV prevalence overtime. At localized-level these HIV incidence ranged from 15 to 18 per 100 person-year and scattered across the relatively homogeneous area within less than 100 km radius. These significant quantitative evidence were further supported by continuous-scale intensity maps. Our findings provided empirical and visual evidence for the changing face of the epidemic in South Africa using geospatial methods.
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Affiliation(s)
- Handan Wand
- Kirby Institute, University of New South Wales, Kensington, 2052, New South Wales, Australia.
| | - Natashia Morris
- Biostatistics Unit: GIS, South African Medical Research Council, Durban, 4091, KwaZulu-Natal, South Africa.
| | - Tarylee Reddy
- Biostatistics Unit, South African Medical Research Council, Durban, Kwazulu-Natal, South Africa.
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Sartorius B, VanderHeide JD, Yang M, Goosmann EA, Hon J, Haeuser E, Cork MA, Perkins S, Jahagirdar D, Schaeffer LE, Serfes AL, LeGrand KE, Abbastabar H, Abebo ZH, Abosetugn AE, Abu-Gharbieh E, Accrombessi MMK, Adebayo OM, Adegbosin AE, Adekanmbi V, Adetokunboh OO, Adeyinka DA, Ahinkorah BO, Ahmadi K, Ahmed MB, Akalu Y, Akinyemi OO, Akinyemi RO, Aklilu A, Akunna CJ, Alahdab F, Al-Aly Z, Alam N, Alamneh AA, Alanzi TM, Alemu BW, Alhassan RK, Ali T, Alipour V, Amini S, Ancuceanu R, Ansari F, Anteneh ZA, Anvari D, Anwer R, Appiah SCY, Arabloo J, Asemahagn MA, Asghari Jafarabadi M, Asmare WN, Atnafu DD, Atout MMW, Atreya A, Ausloos M, Awedew AF, Ayala Quintanilla BP, Ayanore MA, Aynalem YA, Ayza MA, Azari S, Azene ZN, Babar ZUD, Baig AA, Balakrishnan S, Banach M, Bärnighausen TW, Basu S, Bayati M, Bedi N, Bekuma TT, Bezabhe WMM, Bhagavathula AS, Bhardwaj P, Bhattacharyya K, Bhutta ZA, Bibi S, Bikbov B, Birhan TA, Bitew ZW, Bockarie MJ, Boloor A, Brady OJ, Bragazzi NL, Briko AN, Briko NI, Burugina Nagaraja S, Butt ZA, Cárdenas R, Carvalho F, Charan J, Chatterjee S, Chattu SK, Chattu VK, Chowdhury MAK, Chu DT, Cook AJ, Cormier NM, Cowden RG, Culquichicon C, Dagnew B, Dahlawi SMA, Damiani G, Daneshpajouhnejad P, Daoud F, Daryani A, das Neves J, Davis Weaver N, Derbew Molla M, Deribe K, Desta AA, Deuba K, Dharmaratne SD, Dhungana GP, Diaz D, Djalalinia S, Doku PN, Dubljanin E, Duko B, Eagan AW, Earl L, Eaton JW, Effiong A, El Sayed Zaki M, El Tantawi M, Elayedath R, El-Jaafary SI, Elsharkawy A, Eskandarieh S, Eyawo O, Ezzikouri S, Fasanmi AO, Fasil A, Fauk NK, Feigin VL, Ferede TY, Fernandes E, Fischer F, Foigt NA, Folayan MO, Foroutan M, Francis JM, Fukumoto T, Gad MM, Geberemariyam BS, Gebregiorgis BG, Gebremichael B, Gesesew HA, Getacher L, Ghadiri K, Ghashghaee A, Gilani SA, Ginindza TG, Glagn M, Golechha M, Gona PN, Gubari MIM, Gugnani HC, Guido D, Guled RA, Hall BJ, Hamidi S, Handiso DW, Hargono A, Hashi A, Hassanipour S, Hassankhani H, Hayat K, Herteliu C, Hidru HDD, Holla R, Hosgood HD, Hossain N, Hosseini M, Hosseinzadeh M, Househ M, Hwang BF, Ibitoye SE, Ilesanmi OS, Ilic IM, Ilic MD, Irvani SSN, Iwu CCD, Iwu CJ, Iyamu IO, Jain V, Jakovljevic M, Jalilian F, Jha RP, Johnson KB, Joshua V, Joukar F, Jozwiak JJ, Kabir A, Kalankesh LR, Kalhor R, Kamath A, Kamyari N, Kanchan T, Karami Matin B, Karch A, Karimi SE, Kasa AS, Kassahun G, Kayode GA, Kazemi Karyani A, Keiyoro PN, Kelkay B, Khalid N, Khan G, Khan J, Khan MN, Khatab K, Khazaei S, Kim YJ, Kisa A, Kisa S, Kochhar S, Kopec JA, Kosen S, Koulmane Laxminarayana SL, Koyanagi A, Krishan K, Kuate Defo B, Kugbey N, Kulkarni V, Kumar M, Kumar N, Kurmi OP, Kusuma D, Kuupiel D, Kyu HH, La Vecchia C, Lal DK, Lam JO, Landires I, Lasrado S, Lazarus JV, Lazzar-Atwood A, Lee PH, Leshargie CT, Li B, Liu X, Lopukhov PD, M. Amin HI, Madi D, Mahasha PW, Majeed A, Maleki A, Maleki S, Mamun AA, Manafi N, Mansournia MA, Martins-Melo FR, Masoumi SZ, Mayala BK, Meharie BG, Meheretu HAA, Meles HG, Melku M, Mendoza W, Mengesha EW, Meretoja TJ, Mersha AM, Mestrovic T, Miller TR, Mirica A, Mirzaei-Alavijeh M, Mohamad O, Mohammad Y, Mohammadian-Hafshejani A, Mohammed JA, Mohammed S, Mohammed S, Mokdad AH, Mokonnon TM, Molokhia M, Moradi M, Moradi Y, Moradzadeh R, Moraga P, Mosser JF, Munro SB, Mustafa G, Muthupandian S, Naderi M, Nagarajan AJ, Naghavi M, Naveed M, Nayak VC, Nazari J, Ndejjo R, Nepal S, Netsere HB, Ngalesoni FN, Nguefack-Tsague G, Ngunjiri JW, Nigatu YT, Nigussie SN, Nnaji CA, Noubiap JJ, Nuñez-Samudio V, Oancea B, Odukoya OO, Ogbo FA, Oladimeji O, Olagunju AT, Olusanya BO, Olusanya JO, Omer MO, Omonisi AEE, Onwujekwe OE, Orisakwe OE, Otstavnov N, Owolabi MO, P A M, Padubidri JR, Pakhale S, Pana A, Pandi-Perumal SR, Patel UK, Pathak M, Patton GC, Pawar S, Peprah EK, Pokhrel KN, Postma MJ, Pottoo FH, Pourjafar H, Pribadi DRA, Quazi Syed Z, Rafiei A, Rahim F, Rahman MHU, Rahmani AM, Ram P, Rana J, Ranabhat CL, Rao S, Rao SJ, Rathi P, Rawaf DL, Rawaf S, Rawassizadeh R, Renjith V, Reta MA, Rezaei N, Rezapour A, Ribeiro AI, Ross JM, Rumisha SF, Sagar R, Sahu M, Sajadi SM, Salem MR, Samy AM, Sathian B, Schutte AE, Seidu AA, Sha F, Shafaat O, Shahbaz M, Shaikh MA, Shaka MF, Sheikh A, Shibuya K, Shin JI, Shivakumar KM, Sidemo NB, Singh JA, Skryabin VY, Skryabina AA, Soheili A, Soltani S, Somefun OD, Sorrie MB, Spurlock EE, Sufiyan MB, Taddele BW, Tadesse EG, Tamir Z, Tamiru AT, Tanser FC, Taveira N, Tehrani-Banihashemi A, Tekalegn Y, Tesfay FH, Tessema B, Tessema ZT, Thakur B, Tolani MA, Topor-Madry R, Torrado M, Tovani-Palone MR, Traini E, Tsai AC, Tsegaye GW, Ullah I, Ullah S, Umeokonkwo CD, Unnikrishnan B, Vardavas C, Violante FS, Vo B, Wado YD, Waheed Y, Wamai RG, Wang Y, Ward P, Werdecker A, Wickramasinghe ND, Wijeratne T, Wiysonge CS, Wondmeneh TG, Yamada T, Yaya S, Yeshaw Y, Yeshitila YG, Yilma MT, Yip P, Yonemoto N, Yosef T, Yusefzadeh H, Zaidi SS, Zaki L, Zamanian M, Zastrozhin MS, Zastrozhina A, Zewdie DT, Zhang Y, Zhang ZJ, Ziapour A, Hay SI, Dwyer-Lindgren L. Subnational mapping of HIV incidence and mortality among individuals aged 15-49 years in sub-Saharan Africa, 2000-18: a modelling study. Lancet HIV 2021; 8:e363-e375. [PMID: 34087097 PMCID: PMC8187986 DOI: 10.1016/s2352-3018(21)00051-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 03/05/2021] [Accepted: 03/09/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. METHODS In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15-49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000-18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. FINDINGS The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1-3·8) in Mauritania to 1585·9 (1369·4-1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7-0·9) in Mauritania to 676·5 (513·6-888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8-8120·3]) cases per 100 000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0-1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81·1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. INTERPRETATION Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas. FUNDING Bill & Melinda Gates Foundation.
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Carrasco MA, Atkins K, Young R, Rosen JG, Grieb SM, Wong VJ, Fleming PJ. The HIV Pandemic Prevention Efforts Can Inform the COVID-19 Pandemic Response in the United States. Am J Public Health 2021; 111:564-567. [PMID: 33689445 PMCID: PMC7958034 DOI: 10.2105/ajph.2021.306158] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/04/2021] [Indexed: 11/04/2022]
Affiliation(s)
- Maria A Carrasco
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
| | - Kaitlyn Atkins
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
| | - Ruth Young
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
| | - Joseph G Rosen
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
| | - Suzanne M Grieb
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
| | - Vincent J Wong
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
| | - Paul J Fleming
- Maria A. Carrasco is with the Office of Population and Reproductive Health at the United States Agency for International Development (USAID), Washington, DC. Kaitlyn Atkins, Ruth Young, and Joseph G. Rosen are with the Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD. Suzanne M. Grieb is with the Johns Hopkins School of Medicine, Center for Child and Community Health Research, Baltimore. Vincent J. Wong is with the Office of HIV/AIDS at USAID. Paul J. Fleming is with the Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor.Note. The views in this publication do not necessarily reflect the views of the USAID, the US President's Emergency Plan for AIDS Relief, or the US government
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Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review. Epidemics 2021; 35:100450. [PMID: 33761447 PMCID: PMC8207450 DOI: 10.1016/j.epidem.2021.100450] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 11/20/2020] [Accepted: 03/10/2021] [Indexed: 02/01/2023] Open
Abstract
Mathematical model capabilities to explore complex systems now enable priority-setting to consider local resource constraints. Common objectives of model-based analyses incorporating constraints are to assess real-world feasibility or allocate resources efficiently. Constraints may be incorporated via (i) model-based estimation; (ii) linkage of mathematical and health system models; or (iii) optimisation. Models can then project constrained intervention effects and costs and resource requirement s for delivering interventions at full scale. 'Health system constraints' should be systematically defined for routine operationalisation in model-based priority-setting.
Priority setting for infectious disease control is increasingly concerned with physical input constraints and other real-world restrictions on implementation and on the decision process. These health system constraints determine the ‘feasibility’ of interventions and hence impact. However, considering them within mathematical models places additional demands on model structure and relies on data availability. This review aims to provide an overview of published methods for considering constraints in mathematical models of infectious disease. We systematically searched the literature to identify studies employing dynamic transmission models to assess interventions in any infectious disease and geographical area that included non-financial constraints to implementation. Information was extracted on the types of constraints considered and how these were identified and characterised, as well as on the model structures and techniques for incorporating the constraints. A total of 36 studies were retained for analysis. While most dynamic transmission models identified were deterministic compartmental models, stochastic models and agent-based simulations were also successfully used for assessing the effects of non-financial constraints on priority setting. Studies aimed to assess reductions in intervention coverage (and programme costs) as a result of constraints preventing successful roll-out and scale-up, and/or to calculate costs and resources needed to relax these constraints and achieve desired coverage levels. We identified three approaches for incorporating constraints within the analyses: (i) estimation within the disease transmission model; (ii) linking disease transmission and health system models; (iii) optimising under constraints (other than the budget). The review highlighted the viability of expanding model-based priority setting to consider health system constraints. We show strengths and limitations in current approaches to identify and quantify locally-relevant constraints, ranging from simple assumptions to structured elicitation and operational models. Overall, there is a clear need for transparency in the way feasibility is defined as a decision criteria for its systematic operationalisation within models.
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van Schalkwyk C, Dorrington RE, Seatlhodi T, Velasquez C, Feizzadeh A, Johnson LF. Modelling of HIV prevention and treatment progress in five South African metropolitan districts. Sci Rep 2021; 11:5652. [PMID: 33707578 PMCID: PMC7952913 DOI: 10.1038/s41598-021-85154-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 02/25/2021] [Indexed: 12/13/2022] Open
Abstract
Globally, large proportions of HIV-positive populations live in cities. The Fast-Track cities project aims to advance progress toward elimination of HIV as a public health threat by accelerating the response in cities across the world. This study applies a well-established HIV transmission model to provide key HIV estimates for the five largest metropolitan districts in South Africa (SA): Cape Town, Ekurhuleni, eThekwini, Johannesburg and Tshwane. We calibrate the model to metro-specific data sources and estimate progress toward the 90-90-90 targets set by UNAIDS (90% of people living with HIV (PLHIV) diagnosed, 90% of those diagnosed on antiretroviral therapy (ART) and viral suppression in 90% of those on ART). We use the model to predict progress towards similarly defined 95-95-95 targets in 2030. In SA, 90.5% of PLHIV were diagnosed in 2018, with metro estimates ranging from 86% in Johannesburg to 92% in eThekwini. However, only 68.4% of HIV-diagnosed individuals nationally were on ART in 2018, with the proportion ranging from 56% in Tshwane to 73% in eThekwini. Fractions of ART users who were virally suppressed ranged from 77% in Ekurhuleni to 91% in eThekwini, compared to 86% in the whole country. All five metros are making good progress to reach diagnosis targets and all (with the exception of Ekurhuleni) are expected to reach viral suppression targets in 2020. However, the metros and South Africa face severe challenges in reaching the 90% ART treatment target.
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Affiliation(s)
- Cari van Schalkwyk
- The South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa.
| | - Rob E Dorrington
- Centre for Actuarial Research, University of Cape Town, Cape Town, South Africa
| | - Thapelo Seatlhodi
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
- National Department of Health, Pretoria, South Africa
| | | | | | - Leigh F Johnson
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
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Masango BZ, Ferrandiz-Mont D, Chiao C. Associations Between Early Circumcision, Sexual and Protective Practices, and HIV Among a National Sample of Male Adults in Eswatini. AIDS Behav 2021; 25:973-982. [PMID: 33025391 DOI: 10.1007/s10461-020-03056-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/30/2020] [Indexed: 10/23/2022]
Abstract
To reduce HIV incidence in countries such as Eswatini (Swaziland), UNAIDS has recommended male circumcision as one possible effective strategy. We analyzed the 2016s Swaziland HIV Incidence Measurement Survey to explore the association between early circumcision and HIV history among 2964 sexually active adult males aged 15 to 64 years old. Early circumcision was defined as circumcision practiced at an age of 15 years old or younger. Results from logistic regression and OLS regression found that male adults with early circumcision are more likely to have multiple sexual partners and to use condoms. Multiple partners and condom use at last sex encounter remained associated with a higher odds of being HIV positive after controlling for all factors. Nevertheless, early circumcision is significantly associated with a lower odds of being HIV positive (AOR 0.53, p < 0.01). These findings suggest that HIV prevention may benefit when early male circumcision is carried out.
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Efficiency, quality, and management practices in health facilities providing outpatient HIV services in Kenya, Nigeria, Rwanda, South Africa and Zambia. Health Care Manag Sci 2021; 24:41-54. [PMID: 33544323 DOI: 10.1007/s10729-020-09541-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 12/16/2020] [Indexed: 11/27/2022]
Abstract
Few studies have assessed the efficiency and quality of HIV services in low-resource settings or considered the factors that determine both performance dimensions. To provide insights on the performance of outpatient HIV prevention units, we used benchmarking methods to identify best-practices in terms of technical efficiency and process quality and uncover management practices with the potential to improve efficiency and quality. We used data collected in 338 facilities in Kenya, Nigeria, Rwanda, South Africa, and Zambia. Data envelopment analysis (DEA) was used to estimate technical efficiency. Process quality was estimated using data from medical vignettes. We mapped the relationship between efficiency and quality scores and studied the managerial determinants of best performance in terms of both efficiency and quality. We also explored the relationship between management factors and efficiency and quality independently. We found levels of both technical efficiency and process quality to be low, though there was substantial variation across countries. One third of facilities were mapped in the best-performing group with above-median efficiency and above-median quality. Several management practices were associated with best performance in terms of both efficiency and quality. When considering efficiency and quality independently, the patterns of associations between management practices and the two performance dimensions were not necessarily the same. One management characteristic was associated with best performance in terms of efficiency and quality and also positively associated with efficiency and quality independently: number of supervision visits to HIV units.
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Mapping subnational HIV mortality in six Latin American countries with incomplete vital registration systems. BMC Med 2021; 19:4. [PMID: 33413343 PMCID: PMC7791645 DOI: 10.1186/s12916-020-01876-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 11/27/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Human immunodeficiency virus (HIV) remains a public health priority in Latin America. While the burden of HIV is historically concentrated in urban areas and high-risk groups, subnational estimates that cover multiple countries and years are missing. This paucity is partially due to incomplete vital registration (VR) systems and statistical challenges related to estimating mortality rates in areas with low numbers of HIV deaths. In this analysis, we address this gap and provide novel estimates of the HIV mortality rate and the number of HIV deaths by age group, sex, and municipality in Brazil, Colombia, Costa Rica, Ecuador, Guatemala, and Mexico. METHODS We performed an ecological study using VR data ranging from 2000 to 2017, dependent on individual country data availability. We modeled HIV mortality using a Bayesian spatially explicit mixed-effects regression model that incorporates prior information on VR completeness. We calibrated our results to the Global Burden of Disease Study 2017. RESULTS All countries displayed over a 40-fold difference in HIV mortality between municipalities with the highest and lowest age-standardized HIV mortality rate in the last year of study for men, and over a 20-fold difference for women. Despite decreases in national HIV mortality in all countries-apart from Ecuador-across the period of study, we found broad variation in relative changes in HIV mortality at the municipality level and increasing relative inequality over time in all countries. In all six countries included in this analysis, 50% or more HIV deaths were concentrated in fewer than 10% of municipalities in the latest year of study. In addition, national age patterns reflected shifts in mortality to older age groups-the median age group among decedents ranged from 30 to 45 years of age at the municipality level in Brazil, Colombia, and Mexico in 2017. CONCLUSIONS Our subnational estimates of HIV mortality revealed significant spatial variation and diverging local trends in HIV mortality over time and by age. This analysis provides a framework for incorporating data and uncertainty from incomplete VR systems and can help guide more geographically precise public health intervention to support HIV-related care and reduce HIV-related deaths.
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Abstract
This paper reviews the current epidemics of human immunodeficiency virus (HIV) infection in China, particularly the globally available prevention strategies developed and implemented. This review focuses on HIV prevention measures in general, such as education, testing, and counseling and in specific responses to transmission modes, such as blood safety, harm reduction for people who inject drugs, and condom promotion to reduce sexual transmission. We also assess newly developed prevention measures, such as prevention treatment, pre-exposure prophylaxis, post-exposure prophylaxis, male circumcision, and promising potential future preventions, including microbicides and vaccines. Based on this assessment, we provide recommendations for their implementation in China. We conclude that there is no magic bullet for HIV prevention, particularly sexual transmission of the disease, but only a combination of these prevention strategies can control the HIV epidemic.
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Challenges in estimating HIV prevalence trends and geographical variation in HIV prevalence using antenatal data: Insights from mathematical modelling. PLoS One 2020; 15:e0242595. [PMID: 33216793 PMCID: PMC7679018 DOI: 10.1371/journal.pone.0242595] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 11/05/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND HIV prevalence data among pregnant women have been critical to estimating HIV trends and geographical patterns of HIV in many African countries. Although antenatal HIV prevalence data are known to be biased representations of HIV prevalence in the general population, mathematical models have made various adjustments to control for known sources of bias, including the effect of HIV on fertility, the age profile of pregnant women and sexual experience. METHODS AND FINDINGS We assessed whether assumptions about antenatal bias affect conclusions about trends and geographical variation in HIV prevalence, using simulated datasets generated by an agent-based model of HIV and fertility in South Africa. Results suggest that even when controlling for age and other previously-considered sources of bias, antenatal bias in South Africa has not been constant over time, and trends in bias differ substantially by age. Differences in the average duration of infection explain much of this variation. We propose an HIV duration-adjusted measure of antenatal bias that is more stable, which yields higher estimates of HIV incidence in recent years and at older ages. Simpler measures of antenatal bias, which are not age-adjusted, yield estimates of HIV prevalence and incidence that are too high in the early stages of the HIV epidemic, and that are less precise. Antenatal bias in South Africa is substantially greater in urban areas than in rural areas. CONCLUSIONS Age-standardized approaches to defining antenatal bias are likely to improve precision in model-based estimates, and further recency adjustments increase estimates of HIV incidence in recent years and at older ages. Incompletely adjusting for changing antenatal bias may explain why previous model estimates overstated the early HIV burden in South Africa. New assays to estimate the fraction of HIV-positive pregnant women who are recently infected could play an important role in better estimating antenatal bias.
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Brief Report: Recent HIV Infection Surveillance in Routine HIV Testing in Nairobi, Kenya: A Feasibility Study. J Acquir Immune Defic Syndr 2020; 84:5-9. [PMID: 32058458 DOI: 10.1097/qai.0000000000002317] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
BACKGROUND Serological tests can distinguish recent (in the prior 12 months) from long-term HIV infection. Integrating recency testing into routine HIV testing services (HTS) can provide important information on transmission clusters and prioritize clients for partner testing. This study assessed the feasibility and use of integrating HIV recency into routine testing. METHODS We conducted a multi-method study at 14 facilities in Kenya, and key informant interviews with health care providers. We abstracted clinical record data, collected specimens, tested specimens for recent infection, returned results to participants, and conducted a follow-up survey for those recently infected. RESULTS From March to October 2018, we enrolled 532 clients who were diagnosed HIV-positive for the first time. Of these, 46 (8.6%) were recently infected. Women aged 15-24 years had 2.9 (95% confidence interval: 1.46 to 5.78) times higher adjusted odds of recent infection compared with 15-24-year-old men and those tested within the past 12 months having 2.55 (95% confidence interval: 0.38 to 4.70) times higher adjusted odds compared with those tested ≥12 months previously. Fourteen of 17 providers interviewed found the integration of recency testing into routine HTS services acceptable and feasible. Among clients who completed the follow-up interview, most (92%) felt that the recency results were useful. CONCLUSIONS Integrating recent infection testing into routine HTS services in Kenya is feasible and largely acceptable to clients and providers. More studies should be done on possible physical and social harms related to returning results, and the best uses of the recent infection data at an individual and population level.
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Pretorius C, Schnure M, Dent J, Glaubius R, Mahiane G, Hamilton M, Reidy M, Matse S, Njeuhmeli E, Castor D, Kripke K. Modelling impact and cost-effectiveness of oral pre-exposure prophylaxis in 13 low-resource countries. J Int AIDS Soc 2020; 23:e25451. [PMID: 32112512 PMCID: PMC7048876 DOI: 10.1002/jia2.25451] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 01/14/2020] [Indexed: 11/07/2022] Open
Abstract
INTRODUCTION Oral pre-exposure prophylaxis (PrEP) provision is a priority intervention for high HIV prevalence settings and populations at substantial risk of HIV acquisition. This mathematical modelling analysis estimated the impact, cost and cost-effectiveness of scaling up oral PrEP in 13 countries. METHODS We projected the impact and cost-effectiveness of oral PrEP between 2018 and 2030 using a combination of the Incidence Patterns Model and the Goals model. We created four PrEP rollout scenarios involving three priority populations-female sex workers (FSWs), serodiscordant couples (SDCs) and adolescent girls and young women (AGYW)-both with and without geographic prioritization. We applied the model to 13 countries (Eswatini, Ethiopia, Haiti, Kenya, Lesotho, Mozambique, Namibia, Nigeria, Tanzania, Uganda, Zambia and Zimbabwe). The base case assumed achievement of the Joint United Nations Programme on HIV/AIDS 90-90-90 antiretroviral therapy targets, 90% male circumcision coverage by 2020 and 90% efficacy and adherence levels for oral PrEP. RESULTS In the scenarios we examined, oral PrEP averted 3% to 8% of HIV infections across the 13 countries between 2018 and 2030. For all but three countries, more than 50% of the HIV infections averted by oral PrEP in the scenarios we examined could be obtained by rollout to FSWs and SDCs alone. For several countries, expanding oral PrEP to include medium-risk AGYW in all regions greatly increased the impact. The efficiency and impact benefits of geographic prioritization of rollout to AGYW varied across countries. Variations in cost-effectiveness across countries reflected differences in HIV incidence and expected variations in unit cost. For most countries, rolling out oral PrEP to FSWs, SDCs and geographically prioritized AGYW was not projected to have a substantial impact on the supply chain for antiretroviral drugs. CONCLUSIONS These modelling results can inform prioritization, target-setting and other decisions related to oral PrEP scale-up within combination prevention programmes. We caution against extensive use given limitations in cost data and implementation approaches. This analysis highlights some of the immediate challenges facing countries-for example, trade-offs between overall impact and cost-effectiveness-and emphasizes the need to improve data availability and risk assessment tools to help countries make informed decisions.
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Affiliation(s)
| | | | - Juan Dent
- The Palladium Group, Washington, DC, USA
| | | | | | | | | | | | - Emmanuel Njeuhmeli
- United States Agency for International Development (USAID), Mbabane, Eswatini
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Avanceña ALV, Hutton DW. Optimization Models for HIV/AIDS Resource Allocation: A Systematic Review. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2020; 23:1509-1521. [PMID: 33127022 DOI: 10.1016/j.jval.2020.08.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/23/2020] [Accepted: 08/07/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVE This study reviews optimization models for human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) resource allocation. METHODS We searched 2 databases for peer-reviewed articles published from January 1985 through August 2019 that describe optimization models for resource allocation in HIV/AIDS. We included models that consider 2 or more competing HIV/AIDS interventions. We extracted data on selected characteristics and identified similarities and differences across models. We also assessed the quality of mathematical disease transmission models based on the best practices identified by a 2010 task force. RESULTS The final qualitative synthesis included 23 articles that used 14 unique optimization models. The articles shared several characteristics, including the use of dynamic transmission modeling to estimate health benefits and the inclusion of specific high-risk groups in the study population. The models explored similar HIV/AIDS interventions that span primary and secondary prevention and antiretroviral treatment. Most articles were focused on sub-Saharan African countries (57%) and the United States (39%). There was notable variation in the types of optimization objectives across the articles; the most common was minimizing HIV incidence or maximizing infections averted (87%). Articles that utilized mathematical modeling of HIV disease and transmission displayed variable quality. CONCLUSIONS This systematic review of the literature identified examples of optimization models that have been applied in different settings, many of which displayed similar features. There were similarities in objective functions across optimization models, but they did not align with global HIV/AIDS goals or targets. Future work should be applied in countries facing the largest declines in HIV/AIDS funding.
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Affiliation(s)
- Anton L V Avanceña
- Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA.
| | - David W Hutton
- Department of Health Management and Policy and Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, USA
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Suraratdecha C, Stuart RM, Edwards M, Moore R, Liu N, Wilson DP, Albalak R. Costs of providing HIV care and optimal allocation of HIV resources in Guyana. PLoS One 2020; 15:e0238499. [PMID: 33119591 PMCID: PMC7595312 DOI: 10.1371/journal.pone.0238499] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 08/18/2020] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Great strides in responding to the HIV epidemic have led to improved access to and uptake of HIV services in Guyana, a lower-middle-income country with a generalized HIV epidemic. Despite efforts to scale up HIV treatment and adopt the test and start strategy, little is known about costs of HIV services across the care cascade. METHODS We collected cost data from the national laboratory and nine selected treatment facilities in five of the country's ten Regions, and estimated the costs associated with HIV testing and services (HTS) and antiretroviral therapy (ART) from a provider perspective from January 1, 2016 to December 31, 2016. We then used the unit costs to construct four resource allocation scenarios. In the first two scenarios, we calculated how close Guyana would currently be to its 2020 targets if the allocation of funding across programs and regions over 2017-2020 had (a) remained unchanged from latest-reported levels, or (b) been optimally distributed to minimize incidence and deaths. In the next two, we estimated the resources that would have been required to meet the 2020 targets if those resources had been distributed (a) according to latest-reported patterns, or (b) optimally to minimize incidence and deaths. RESULTS The mean cost per test was US$15 and the mean cost per person tested positive was US$796. The mean annual cost per of maintaining established adult and pediatric patients on ART were US$428 and US$410, respectively. The mean annual cost of maintaining virally suppressed patients was US$648. Cost variation across sites may suggest opportunities for improvements in efficiency, or may reflect variation in facility type and patient volume. There may also be scope for improvements in allocative efficiency; we estimated a 28% reduction in the total resources required to meet Guyana's 2020 targets if funds had been optimally distributed to minimize infections and deaths. CONCLUSIONS We provide the first estimates of costs along the HIV cascade in the Caribbean and assessed efficiencies using novel context-specific data on the costs associated with diagnostic, treatment, and viral suppression. The findings call for better targeting of services, and efficient service delivery models and resource allocation, while scaling up HIV services to maximize investment impact.
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Affiliation(s)
- Chutima Suraratdecha
- Division of Global HIV and TB, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Robyn M. Stuart
- Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
- Burnet Institute, Melbourne, Australia
- * E-mail:
| | | | | | - Nadia Liu
- Ministry of Public Health, Georgetown, Guyana
| | - David P. Wilson
- Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
- Monash University, Melbourne, Australia
- Kirby Institute, University of New South Wales, Sydney, Australia
- Department of Microbial Pathogenesis, University of Maryland, Baltimore, United States of America
| | - Rachel Albalak
- U.S. Centers for Disease Control and Prevention, Caribbean Region Office, Barbados, Santo Domingo, Dominican Republic
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Tuson M, Yap M, Kok MR, Boruff B, Murray K, Vickery A, Turlach BA, Whyatt D. Overcoming inefficiencies arising due to the impact of the modifiable areal unit problem on single-aggregation disease maps. Int J Health Geogr 2020; 19:40. [PMID: 33010800 PMCID: PMC7532343 DOI: 10.1186/s12942-020-00236-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 09/21/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND In disease mapping, fine-resolution spatial health data are routinely aggregated for various reasons, for example to protect privacy. Usually, such aggregation occurs only once, resulting in 'single-aggregation disease maps' whose representation of the underlying data depends on the chosen set of aggregation units. This dependence is described by the modifiable areal unit problem (MAUP). Despite an extensive literature, in practice, the MAUP is rarely acknowledged, including in disease mapping. Further, despite single-aggregation disease maps being widely relied upon to guide distribution of healthcare resources, potential inefficiencies arising due to the impact of the MAUP on such maps have not previously been investigated. RESULTS We introduce the overlay aggregation method (OAM) for disease mapping. This method avoids dependence on any single set of aggregate-level mapping units through incorporating information from many different sets. We characterise OAM as a novel smoothing technique and show how its use results in potentially dramatic improvements in resource allocation efficiency over single-aggregation maps. We demonstrate these findings in a simulation context and through applying OAM to a real-world dataset: ischaemic stroke hospital admissions in Perth, Western Australia, in 2016. CONCLUSIONS The ongoing, widespread lack of acknowledgement of the MAUP in disease mapping suggests that unawareness of its impact is extensive or that impact is underestimated. Routine implementation of OAM can help avoid resource allocation inefficiencies associated with this phenomenon. Our findings have immediate worldwide implications wherever single-aggregation disease maps are used to guide health policy planning and service delivery.
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Affiliation(s)
- Matthew Tuson
- Medical School, University of Western Australia, Perth, Australia.,Department of Mathematics and Statistics, University of Western Australia, Perth, Australia
| | - Matthew Yap
- Medical School, University of Western Australia, Perth, Australia
| | - Mei Ruu Kok
- Medical School, University of Western Australia, Perth, Australia
| | - Bryan Boruff
- UWA School of Agriculture and Environment, University of Western Australia, Perth, Australia.,Department of Geography, University of Western Australia, Perth, Australia
| | - Kevin Murray
- School of Population and Global Health, University of Western Australia, Perth, Australia
| | - Alistair Vickery
- Medical School, University of Western Australia, Perth, Australia
| | - Berwin A Turlach
- Department of Mathematics and Statistics, University of Western Australia, Perth, Australia
| | - David Whyatt
- Medical School, University of Western Australia, Perth, Australia.
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Zhu Q, Wang Y, Liu J, Duan X, Chen M, Yang J, Yang T, Yang S, Guan P, Jiang Y, Duan S, Wang J, Jin C. Identifying major drivers of incident HIV infection using recent infection testing algorithms (RITAs) to precisely inform targeted prevention. Int J Infect Dis 2020; 101:131-137. [PMID: 32987184 DOI: 10.1016/j.ijid.2020.09.1421] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 09/09/2020] [Accepted: 09/11/2020] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Recent infection testing algorithms (RITAs) incorporating clinical information with the HIV recency assay have been proven to accurately classify recent infection. However, little evidence exists on whether RITAs would help in precisely identifying major drivers of the ongoing HIV epidemic. METHODS HIV recency test results and clinical information were collected from 1152 newly diagnosed HIV cases between 2015 and 2017 in Dehong prefecture of Yunnan province, and the efficacy of four different RITAs in identifying risk factors for new HIV infection was compared. RESULTS RITA 1 uses the recency test only. RITA 2 and RITA 3 combine the recency test with CD4+ T cell count and viral load (VL), respectively. RITA 4 combines both CD4+ T cell count and VL. All RITAs identified the MSM group and young people between 15 and 24 years as risk factors for incident HIV infection. RITA 3 and RITA 4 further identified the Dai ethnic minority as a risk factor, which had not been identified before when only the HIV recency test was used. CONCLUSIONS By comparing different RITAs, we determined that greater accuracy in classifying recent HIV infection could help elucidate major drivers impacting the ongoing epidemic and thus inform targeted interventions.
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Affiliation(s)
- Qiyu Zhu
- National AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Yikui Wang
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China
| | - Jing Liu
- National AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Xing Duan
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China
| | - Meibin Chen
- National AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Jin Yang
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China
| | - Tao Yang
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China
| | - Shijiang Yang
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China
| | - Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Yan Jiang
- National AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Song Duan
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China
| | - Jibao Wang
- Department of AIDS Control and Prevention, Dehong Prefecture Center for Disease Control and Prevention, Mangshi 678400, Yunnan, China.
| | - Cong Jin
- National AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
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Wahome EW, Graham SM, Thiong'o AN, Mohamed K, Oduor T, Gichuru E, Mwambi J, Prins PM, van der Elst E, Sanders PEJ. PrEP uptake and adherence in relation to HIV-1 incidence among Kenyan men who have sex with men. EClinicalMedicine 2020; 26:100541. [PMID: 33089128 PMCID: PMC7565200 DOI: 10.1016/j.eclinm.2020.100541] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/21/2020] [Accepted: 08/21/2020] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Data on HIV-1 incidence following programmatic pre-exposure prophylaxis (PrEP) uptake by men who have sex with men (MSM) are limited in sub-Saharan Africa. METHODS Since June 2017, MSM participating in an ongoing cohort study in Kenya were offered daily PrEP, assessed for PrEP uptake and adherence, and evaluated for HIV-1 acquisition monthly. We determined tenofovir-diphosphate (TFV-DP) concentrations in dried blood spots 6-12 months after PrEP initiation, and tenofovir (TFV) concentrations and genotypic drug resistance in plasma samples when HIV-1 infection occurred. We assessed HIV-1 incidence by reported PrEP use. FINDINGS Of 172 MSM, 170 (98·8%) were eligible for PrEP, 140 (82·4%) started it, and 64 (57·7%) reported PrEP use at end of study. Of nine MSM who acquired HIV-1 [incidence rate: 3·9 (95% confidence interval (CI), 2·0-7·4) per 100 person-years (PY)], five reported PrEP use at the time of HIV-1 acquisition [incidence rate: 3·6 (95% CI, 1·5-8·6) per 100 PY)] and four had stopped or had never started PrEP [incidence rate: 4·3 (95% CI, 1·6-11·3) per 100 PY]. Among 76 MSM who reported PrEP use, 11 (14·5%) had protective TFV-DP concentrations of ≥700 fmol/punch (≥4 tablets a week). Among the five MSM who acquired HIV-1 while reporting PrEP use, only one had detectable but low TFV concentrations in plasma and none had genotypic HIV-1 resistance. INTERPRETATION HIV-1 incidence among MSM with access to programmatic PrEP was high and did not differ by reported PrEP use. Only one in seven MSM taking PrEP had protective tenofovir concentrations and four out of five MSM who acquired HIV-1 while reporting PrEP use had not taken it. Strengthened PrEP adherence support is required among MSM in Kenya. FUNDING This work was supported by the International AIDS Vaccine Initiative (IAVI).
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Affiliation(s)
- Elizabeth W. Wahome
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
- Corresponding author.
| | - Susan M. Graham
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
- Departments of Global Health, Medicine, and Epidemiology, University of Washington, Seattle, Wash, USA
| | - Alexander N. Thiong'o
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
| | - Khamisi Mohamed
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
| | - Tony Oduor
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
| | - Evans Gichuru
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
| | - John Mwambi
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
| | - Prof. Maria Prins
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, the Netherlands
- Department of Infectious Diseases, Amsterdam Infection & Immunity Institute (AI&II), Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Elise van der Elst
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
- Department of Global Health, University of Amsterdam, Amsterdam, the Netherlands
| | - Prof. Eduard J. Sanders
- KEMRI/Wellcome Trust Research Programme Centre for Geographic Medicine Research–Coast, P.O. Box 230-80108, Kilifi, Kenya
- Department of Global Health, University of Amsterdam, Amsterdam, the Netherlands
- Nuffield Department of Medicine, University of Oxford, Headington, UK
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Cork MA, Wilson KF, Perkins S, Collison ML, Deshpande A, Eaton JW, Earl L, Haeuser E, Justman JE, Kinyoki DK, Mayala BK, Mosser JF, Murray CJL, Nkengasong JN, Piot P, Sartorius B, Schaeffer LE, Serfes AL, Sligar A, Steuben KM, Tanser FC, VanderHeide JD, Yang M, Wabiri N, Hay SI, Dwyer-Lindgren L. Mapping male circumcision for HIV prevention efforts in sub-Saharan Africa. BMC Med 2020; 18:189. [PMID: 32631314 PMCID: PMC7339571 DOI: 10.1186/s12916-020-01635-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 05/14/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND HIV remains the largest cause of disease burden among men and women of reproductive age in sub-Saharan Africa. Voluntary medical male circumcision (VMMC) reduces the risk of female-to-male transmission of HIV by 50-60%. The World Health Organization (WHO) and Joint United Nations Programme on HIV/AIDS (UNAIDS) identified 14 priority countries for VMMC campaigns and set a coverage goal of 80% for men ages 15-49. From 2008 to 2017, over 18 million VMMCs were reported in priority countries. Nonetheless, relatively little is known about local variation in male circumcision (MC) prevalence. METHODS We analyzed geo-located MC prevalence data from 109 household surveys using a Bayesian geostatistical modeling framework to estimate adult MC prevalence and the number of circumcised and uncircumcised men aged 15-49 in 38 countries in sub-Saharan Africa at a 5 × 5-km resolution and among first administrative level (typically provinces or states) and second administrative level (typically districts or counties) units. RESULTS We found striking within-country and between-country variation in MC prevalence; most (12 of 14) priority countries had more than a twofold difference between their first administrative level units with the highest and lowest estimated prevalence in 2017. Although estimated national MC prevalence increased in all priority countries with the onset of VMMC campaigns, seven priority countries contained both subnational areas where estimated MC prevalence increased and areas where estimated MC prevalence decreased after the initiation of VMMC campaigns. In 2017, only three priority countries (Ethiopia, Kenya, and Tanzania) were likely to have reached the MC coverage target of 80% at the national level, and no priority country was likely to have reached this goal in all subnational areas. CONCLUSIONS Despite MC prevalence increases in all priority countries since the onset of VMMC campaigns in 2008, MC prevalence remains below the 80% coverage target in most subnational areas and is highly variable. These mapped results provide an actionable tool for understanding local needs and informing VMMC interventions for maximum impact in the continued effort towards ending the HIV epidemic in sub-Saharan Africa.
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Affiliation(s)
- Michael A Cork
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Kate F Wilson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Samantha Perkins
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Michael L Collison
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Aniruddha Deshpande
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jeffrey W Eaton
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Lucas Earl
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Emily Haeuser
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jessica E Justman
- ICAP, Mailman School of Public Health, Columbia University, New York, NY, USA.,Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Damaris K Kinyoki
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | | | - Jonathan F Mosser
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Christopher J L Murray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - John N Nkengasong
- Africa Centres for Disease Control and Prevention, African Union, Addis Ababa, Ethiopia
| | - Peter Piot
- London School of Hygiene & Tropical Medicine, London, UK
| | - Benn Sartorius
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.,London School of Hygiene & Tropical Medicine, London, UK
| | - Lauren E Schaeffer
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Audrey L Serfes
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Amber Sligar
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Krista M Steuben
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Frank C Tanser
- School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.,Africa Health Research Institute, KwaZulu-Natal, South Africa.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa.,Research Department of Infection & Population Health, University College London, London, UK
| | - John D VanderHeide
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Mingyou Yang
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Njeri Wabiri
- HIV/AIDS, STIs & TB Research Programme, Human Sciences Research Council, Pretoria, South Africa
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Laura Dwyer-Lindgren
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. .,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
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