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He S, Dong W, Fairley CK, Li Z, Wei Y, Lai H, Li R, Lu P, Shen M, Wu Z, Zhang L. Optimizing health resource allocation for improving timely HIV diagnosis in China. J Int AIDS Soc 2024; 27:e26221. [PMID: 38444111 PMCID: PMC10935715 DOI: 10.1002/jia2.26221] [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: 05/16/2023] [Accepted: 01/30/2024] [Indexed: 03/07/2024] Open
Abstract
INTRODUCTION The Joint United Nations Programme on HIV/AIDS (UNAIDS) updated the 95-95-95 targets for the HIV endgame in 2030. To achieve the first target in a timely manner, we investigate the optimized strategy of resource allocation to maximize timely HIV diagnosis in 14 populations in China. METHODS We developed a mathematical model by integrating epidemiological, demographical and behavioural data from 12 high-risk and two general populations to evaluate the impact of various resource allocation strategies of HIV testing on HIV incidence in China. We identified the optimized allocation strategy that maximizes the number of HIV diagnoses at an estimated total spending on HIV tests in China and calculated the per-capita cost of new HIV case detection. RESULTS We estimated that 144,795 new HIV cases may occur annually in 14 populations in China, with a total annual spending of US$2.8 billion on HIV testing. The largest proportion of spending was allocated to general males (44.0%), followed by general females (42.6%) and pregnant women (5.1%). Despite this allocation strategy, only 45.5% (65,867/144,795, timely diagnosis rate) of annual new infections were diagnosed within a year of acquisition, with a cost of $42,852 required for each new HIV case detection. By optimizing the allocation of HIV testing resources within the same spending amount, we found that general females received the highest proportion of spending allocation (45.1%), followed by low-risk men who have sex with men (13.9%) and pregnant women (8.4%). In contrast, the proportion of spending allocation for the general males decreased to 0.2%. With this optimized strategy, we estimated that 120,755 (83.4%) of annual new infections would be diagnosed within a year of acquisition, with the cost required for one HIV case detection reduced to $23,364/case. Further spending increases could allow for significant increases in HIV testing among lower-risk populations. CONCLUSIONS Optimizing resource allocation for HIV testing in high-risk populations would improve HIV timely diagnosis rate of new infections and reduce cost per HIV case detection.
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Affiliation(s)
- Shihao He
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
| | - Wei Dong
- National Center for AIDS/STD Control and Prevention (NCAIDS)Chinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Christopher K. Fairley
- Melbourne Sexual Health CentreAlfred HealthMelbourneVictoriaAustralia
- Central Clinical SchoolFaculty of MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Zengbin Li
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
| | - Yudong Wei
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
| | - Hao Lai
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
| | - Rui Li
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
| | - Pengyi Lu
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
| | - Mingwang Shen
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi ProvinceXi'anChina
- The Interdisciplinary Center for Mathematics and Life SciencesSchool of Mathematics and StatisticsXi'an Jiaotong UniversityXi'anChina
- Key Laboratory of Environment and Genes Related to Diseases (Xi'an Jiaotong University)Ministry of EducationXi'anChina
| | - Zunyou Wu
- National Center for AIDS/STD Control and Prevention (NCAIDS)Chinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Lei Zhang
- China‐Australia Joint Research Center for Infectious DiseasesSchool of Public HealthXi'an Jiaotong University Health Science CenterXi'anChina
- Melbourne Sexual Health CentreAlfred HealthMelbourneVictoriaAustralia
- Central Clinical SchoolFaculty of MedicineMonash UniversityMelbourneVictoriaAustralia
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Zhao R, Fairley CK, Cook AR, Phanuphak N, He S, Tieosapjaroen W, Chow EPF, Phillips TR, Jin Tan RK, Wei Y, Shen M, Zhuang G, Ong JJ, Zhang L. Optimising HIV pre-exposure prophylaxis and testing strategies in men who have sex with men in Australia, Thailand, and China: a modelling study and cost-effectiveness analysis. Lancet Glob Health 2024; 12:e243-e256. [PMID: 38245115 DOI: 10.1016/s2214-109x(23)00536-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 11/02/2023] [Accepted: 11/06/2023] [Indexed: 01/22/2024]
Abstract
BACKGROUND Men who have sex with men (MSM) in the Asia-Pacific region have a disproportionately high burden of HIV infection compared with the general population. Although pre-exposure prophylaxis (PrEP) for HIV is highly effective at preventing new HIV infections, the cost-effectiveness of PrEP for MSM in different countries in the Asia-Pacific region with varying PrEP coverage and HIV testing frequencies remains unstudied. We aimed to analyse the economic and health benefits of long-acting injectable cabotegravir (CAB-LA) compared with oral PrEP in high-income countries and low-income and middle-income countries within the Asia-Pacific region. METHODS We developed a decision-analytic Markov model to evaluate the population impact and cost-effectiveness of PrEP scale-up among MSM in Australia, Thailand, and China. We assumed a static cohort of 100 000 MSM aged 18 years or older who were at risk of HIV infection, with a monthly cycle length over a 40-year time period. We evaluated hypothetical scenarios with universal PrEP coverage of 80% among 100 000 suitable MSM in each country. We modelled oral PrEP and CAB-LA for MSM with diverse HIV testing frequency strategies. We adopted the health-care system's perspective with a 3% annual discount rate. We calculated the incremental cost-effectiveness ratio (ICER), measured as additional cost per quality-adjusted life-year (QALY) gained, to compare different strategies with the status quo in each country. All costs were reported in 2021 US$. We also performed one-way, two-way, and probabilistic sensitivity analyses to assess the robustness of our findings. FINDINGS Compared with the status quo in each country, expanding oral PrEP to 80% of suitable MSM would avert 8·1% of new HIV infections in Australia, 14·5% in Thailand, and 26·4% in China in a 40-year period. Expanding oral PrEP use with 6-monthly HIV testing for both PrEP and non-PrEP users was cost-saving for Australia. Similarly, expanding oral PrEP use remained the most cost-effective strategy in both Thailand and China, but optimal testing frequency varied, with annual testing in Thailand (ICER $4707 per QALY gained) and 3-monthly testing in China (ICER $16 926 per QALY gained) for both PrEP and non-PrEP users. We also found that replacing oral PrEP with CAB-LA for MSM could avert more new HIV infections (12·8% in Australia, 27·6% in Thailand, and 32·8% in China), but implementing CAB-LA was not cost-effective due to its high cost. The cost of CAB-LA would need to be reduced by 50-90% and be used as a complementary strategy to oral PrEP to be cost-effective in these countries. INTERPRETATION Expanding oral PrEP use for MSM, with country-specific testing frequency, is cost-effective in Australia, Thailand, and China. Due to the high cost, CAB-LA is currently not affordable as a single-use strategy but might be offered as an additional option to oral PrEP. FUNDING Ministry of Science and Technology of the People's Republic of China, the Australian National Health and Medical Research Council, National Key Research and Development Program of China, and National Natural Science Foundation of China.
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Affiliation(s)
- Rui Zhao
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Christopher K Fairley
- Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Nittaya Phanuphak
- Institute of HIV Research and Innovation, Bangkok, Thailand; Center of Excellence in Transgender Health, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Shiyi He
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Warittha Tieosapjaroen
- Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Eric P F Chow
- Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia; Melbourne School of Population and Global Health, Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
| | - Tiffany R Phillips
- Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Rayner Kay Jin Tan
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore; University of North Carolina Project-China, Guangzhou, China
| | - Yuhang Wei
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Mingwang Shen
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China; Interdisciplinary Center for Mathematics and Life Sciences, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, China
| | - Guihua Zhuang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, China.
| | - Jason J Ong
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China; Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia; Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
| | - Lei Zhang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an Jiaotong University, Xi'an, China; Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia; Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, China.
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Fu J, Dai Z, Wang H, Si M, Chen X, Wu Y, Xiao W, Huang Y, Yu F, Mi G, Su X. Willingness to use long-acting injectable PrEP among HIV-negative/unknown men who have sex with men in mainland China: A cross-sectional online survey. PLoS One 2023; 18:e0293297. [PMID: 37856527 PMCID: PMC10586652 DOI: 10.1371/journal.pone.0293297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 10/09/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Men who have sex with men (MSM) are at high risk of HIV acquisition. Long-acting injectable-pre-exposure prophylaxis (LAI-PrEP), requiring less frequent dosing, is being studied as an alternative method to daily oral HIV PrEP. With the addition of this potential new prevention method, it expands the scope for a wider user choice and is expected to increase the acceptability and uptake of HIV prevention measures. The aim of our study was to explore the willingness to use LAI-PrEP and associated influential factors. METHODS Participants were recruited from December 2020 to March 2021 through banner advertisements on web- and mobile app-based platforms on Blued, a large gay Chinese social media platform. MSM in our cross-sectional study was HIV-negative and currently lived in mainland China. Participants were asked about their willingness to use LAI-PrEP and reasons why they might be or not be willing to use LAI-PrEP. Multivariable logistic regression was used to analyze the factors associated with the willingness to use LAI-PrEP. RESULTS In total, 969 participants met the inclusion criteria and finished the survey. Nearly twenty percent (19.5%) of participants had never tested for HIV; 66.8% of MSM had multiple male partners; and 51.6% of MSM engaged in condomless sex with their partner. About three-fifths (66.3%) of MSM were aware of PrEP, and only 3.9% of MSM had used PrEP before. The willingness to use LAI-PrEP among MSM was 74.0% (95% CI: 71.4%-76.6%). MSM with higher education levels were less likely to show a willingness to use LAI-PrEP (AOR = 0.56, 95%CI: 0.38-0.84). Participants who had a history of HIV test (AOR = 1.68, 95%CI: 1.11-2.55), were willing to use daily oral PrEP (AOR = 10.64, 95%CI:7.43-15.21), had multiple male sexual partners (AOR = 1.33, 95%CI:0.93-1.90), who used rush popper(AOR = 1.49, 95%CI:1.05-2.13), and who were aware of PEP (AOR = 1.66, 95%CI: 1.02-2.70) were more likely to show willingness to use LAI-PrEP. CONCLUSIONS In our study, MSM had quite high awareness but low uptake of PrEP. As LAI-PrEP is expected to be approved for use in China in the future, our study of MSM highlights the need for key population-focused education programs about PrEP and healthy sexual behavior. This study also provides some evidence for LAI-PrEP use among the Chinese MSM population in the future.
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Affiliation(s)
- Jiaqi Fu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhenwei Dai
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hao Wang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Mingyu Si
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xu Chen
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yijin Wu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Weijun Xiao
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yiman Huang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fei Yu
- Danlan Public Welfare, Beijing, China
| | | | - Xiaoyou Su
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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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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Lai H, Li R, Li Z, Zhang B, Li C, Song C, Zhao Q, Huang J, Zhu Q, Liang S, Chen H, Li J, Liao L, Shao Y, Xing H, Ruan Y, Lan G, Zhang L, Shen M. Modelling the impact of treatment adherence on the transmission of HIV drug resistance. J Antimicrob Chemother 2023:dkad186. [PMID: 37311203 DOI: 10.1093/jac/dkad186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 05/30/2023] [Indexed: 06/15/2023] Open
Abstract
INTRODUCTION A lower adherence rate (percentage of individuals taking drugs as prescribed) to ART may increase the risk of emergence and transmission of HIV drug resistance, decrease treatment efficacy, and increase mortality rate. Exploring the impact of ART adherence on the transmission of drug resistance could provide insights in controlling the HIV epidemic. METHODS We proposed a dynamic transmission model incorporating the CD4 cell count-dependent rates of diagnosis, treatment and adherence with transmitted drug resistance (TDR) and acquired drug resistance. This model was calibrated and validated by 2008-2018 HIV/AIDS surveillance data and prevalence of TDR among newly diagnosed treatment-naive individuals from Guangxi, China, respectively. We aimed to identify the impact of adherence on drug resistance and deaths during expanding ART. RESULTS In the base case (ART at 90% adherence and 79% coverage), we projected the cumulative total new infections, new drug-resistant infections, and HIV-related deaths between 2022 and 2050 would be 420 539, 34 751 and 321 671. Increasing coverage to 95% would reduce the above total new infections (deaths) by 18.85% (15.75%). Reducing adherence to below 57.08% (40.84%) would offset these benefits of increasing coverage to 95% in reducing infections (deaths). Every 10% decrease in adherence would need 5.07% (3.62%) increase in coverage to avoid an increase in infections (deaths). Increasing coverage to 95% with 90% (80%) adherence would increase the above drug-resistant infections by 11.66% (32.98%). CONCLUSIONS A decrease in adherence might offset the benefits of ART expansion and exacerbate the transmission of drug resistance. Ensuring treated patients' adherence might be as important as expanding ART to untreated individuals.
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Affiliation(s)
- Hao Lai
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Rui Li
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Zengbin Li
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Baoming Zhang
- College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi 710004, P.R. China
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, Shaanxi 710004, P.R. China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Chao Li
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
| | - Chang Song
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, P.R. China
| | - Quanbi Zhao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, P.R. China
| | - Jinghua Huang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Huanhuan Chen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, P.R. China
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, P.R. China
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, P.R. China
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing 102206, P.R. China
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning 530028, P.R. China
| | - Lei Zhang
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia
- Central Clinical School, Faculty of Medicine, Monash University, Melbourne, Australia
| | - Mingwang Shen
- China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, P.R. China
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Shen M, Xiao Y, Rong L, Zhuang G, Song C, Zhao Q, Huang J, Zhu Q, Liang S, Chen H, Li J, Liao L, Shao Y, Xing H, Ruan Y, Lan G. The impact of attrition on the transmission of HIV and drug resistance. AIDS 2023; 37:1137-1145. [PMID: 36927994 DOI: 10.1097/qad.0000000000003528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
BACKGROUND Attrition due to loss to follow-up or termination of antiretroviral therapy (ART) among HIV-infected patients in care may increase the risk of emergence and transmission of drug resistance (TDR), diminish benefit of treatment, and increase morbidity and mortality. Understanding the impact of attrition on the epidemic is essential to provide interventions for improving retention in care. METHODS We developed a comprehensive HIV transmission dynamics model by considering CD4 + cell count dependent diagnosis, treatment, and attrition involving TDR and acquired drug resistance. The model was calibrated by 11 groups HIV/AIDS surveillance data during 2008-2018 from Guangxi, China, and validated by the prevalence of TDR among diagnosed treatment-naive individuals. We aimed to investigate how attrition would affect the transmission of HIV and drug-resistance when expanding ART. RESULTS In the base case with CD4 + cell count dependent per capita attrition rates 0.025∼0.15 and treatment rates 0.23∼0.42, we projected cumulative total new infections, new drug-resistant infections, and HIV-related deaths over 2022-2030 would be 145 391, 7637, and 51 965, respectively. Increasing treatment rates by 0.1∼0.2 can decrease the above total new infections (deaths) by 1.63∼2.93% (3.52∼6.16%). However, even 0.0114∼0.0220 (0.0352∼0.0695) increase in attrition rates would offset this benefit of decreasing infections (deaths). Increasing treatment rates (attrition rates) by 0.05∼0.1 would increase the above drug-resistant infections by 0.16∼0.30% (22.18∼41.15%). CONCLUSION A minor increase in attrition can offset the benefit of treatment expansion and increase the transmission of HIV drug resistance. Reducing attrition rates for patients already in treatment may be as important as expanding treatment for untreated patients.
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Affiliation(s)
- Mingwang Shen
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi
| | - Yanni Xiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Libin Rong
- Department of Mathematics, University of Florida, Gainesville, Florida, USA
| | - Guihua Zhuang
- China-Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi
| | - Chang Song
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
| | - Quanbi Zhao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
| | - Jinghua Huang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Huanhuan Chen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
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7
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Yun K, Yu J, Liu C, Zhang X. A Cost-effectiveness Analysis of a Mobile Phone-Based Integrated HIV-Prevention Intervention Among Men Who Have Sex With Men in China: Economic Evaluation. J Med Internet Res 2022; 24:e38855. [PMID: 36322123 PMCID: PMC9669883 DOI: 10.2196/38855] [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: 04/20/2022] [Revised: 06/27/2022] [Accepted: 10/01/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Mobile phone-based digital interventions have been shown to be a promising strategy for HIV prevention among men who have sex with men (MSM). OBJECTIVE This study aimed to evaluate the cost-effectiveness of a mobile phone-based digital intervention for HIV prevention among MSM in China from the perspective of a public health provider. METHODS The cost-effectiveness of the mobile phone-based digital intervention was estimated for a hypothetical cohort of 10,000 HIV-negative MSM who were followed for 1 year. A model was developed with China-specific data to project the clinical impact and cost-effectiveness of two mobile phone-based digital strategies for HIV prevention among MSM. The intervention group received an integrated behavioral intervention that included 1) individualized HIV infection risk assessment, 2) recommendation of centers testing for HIV and other STIs, 3) free online order of condoms and HIV and syphilis self-test kits and 4) educational materials about HIV/AIDS. The control group was only given educational materials about HIV/AIDS. Outcomes of interest were the number of HIV infections among MSM averted by the intervention, intervention costs, cost per HIV infection averted by the mobile phone-based digital intervention, and quality-adjusted life-years (QALYs). Univariate and multivariate sensitivity analyses were also conducted to examine the robustness of the results. RESULTS It is estimated that the intervention can prevent 48 MSM from becoming infected with HIV and can save 480 QALYs. The cost of preventing 1 case of HIV infection was US $2599.87, and the cost-utility ratio was less than 0. Sensitivity analysis showed that the cost-effectiveness of the mobile phone-based digital intervention was mainly impacted by the average number of sexual behaviors with each sexual partner. Additionally, the higher the HIV prevalence among MSM, the greater the benefit of the intervention. CONCLUSIONS Mobile phone-based digital interventions are a cost-effective HIV-prevention strategy for MSM and could be considered for promotion and application among high-risk MSM subgroups.
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Affiliation(s)
- Ke Yun
- Department of Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiaming Yu
- Department of Hospital Infection Management, The Fourth Affiliated Hospital of China Medical University, Shenyang, China
| | - Changyang Liu
- Department of Ophthalmology Laboratory, The Fourth Affiliated Hospital of China Medical University, Shenyang, China
| | - Xinxin Zhang
- Department of Ophthalmology Laboratory, The Fourth Affiliated Hospital of China Medical University, Shenyang, China
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8
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Li J, Gilmour S, Wang Y, Gu J, Lau JTF. Time to consider elimination of HIV in China. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 24:100497. [PMID: 35677147 PMCID: PMC9168685 DOI: 10.1016/j.lanwpc.2022.100497] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
- Jinghua Li
- School of Public Health, Sun Yat-sen University, Guangzhou, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Stuart Gilmour
- Graduate School of Public Health, St. Luke's International University, Tokyo, Japan
| | - Yijing Wang
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jing Gu
- School of Public Health, Sun Yat-sen University, Guangzhou, China
- Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
| | - Joseph Tak-fai Lau
- Centre for Health Behaviours Research, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
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