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Article(id=1321170855934148882, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321170720168726830, articleNumber=null, orderNo=null, doi=10.11847/zgggws1147168, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1739894400000, receivedDateStr=2025-02-19, revisedDate=1743350400000, revisedDateStr=2025-03-31, acceptedDate=1751990400000, acceptedDateStr=2025-07-09, onlineDate=1792921278222, onlineDateStr=2026-10-25, pubDate=1754755200000, pubDateStr=2025-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792921278222, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792921278222, creator=13701087609, updateTime=1792921278222, updator=13701087609, issue=Issue{id=1321170720168726830, tenantId=1146029695717560320, journalId=1319373219989389464, year='2025', volume='41', issue='8', pageStart='897', pageEnd='1024', issueExtLink='null', onlineDate='null', pubDate='1754755200000', pubDateStr='2025-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792921245852, creator='13701087609', updateTime=1792921245852, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=1005, endPage=1012, ext={EN=ArticleExt(id=1321170856257110291, articleId=1321170855934148882, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Research progress on a resource allocation tool for HIV prevention and control Optima HIV: a review, columnId=1320427713148597230, journalTitle=Chinese Journal of Public Health, columnName=Review, runingTitle=null, highlight=null, articleAbstract=

Scientific allocation and optimization of public health resources can promote the efficiency and quality of AIDS prevention and control work. The Optima HIV, a human immunodeficiency virus (HIV) resource allocation analysis tool, provides technical support for HIV resource allocation and optimization by describing the epidemic situation, analyzing the relationship between health inputs and health outputs, and exploring the optimal allocation of HIV prevention and control intervention resources. This article reviews the Optima HIV software from five aspects: research and development background, theoretical framework, tool modules, parameter structure, and global application, to provide a reference for AIDS prevention and control and scientific resource allocation in China.

, authors=Yue HAN1, Qingcheng TAN1, Lili WANG1, Youran ZHANG1, Zhen JIANG2, authorsList=Yue HAN, Qingcheng TAN, Lili WANG, Youran ZHANG, Zhen JIANG, authorCompany=null, correspAuthors=Youran ZHANG, authorNote=null, correspAuthorsNote=
ZHANG Youran, E-mail:
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科学的公共卫生资源配置和优化，可以推动艾滋病防治工作的效率和质量提升。人类免疫缺陷病毒（HIV）资源配置分析工具Optima HIV通过描述疾病流行情况，分析卫生投入与健康产出的关系，探索HIV防治干预资源的最佳配置，在HIV资源配置和优化方面提供技术支持。本文从研发背景、理论框架、工具模块、参数结构及在全球范围内的应用情况5个方面对Optima HIV软件进行综述，为我国的艾滋病防治和科学的资源分配提供参考。

, authors=韩跃1, 谭清成1, 王莉莉1, 张悠然1, *, *, 江震2, authorsList=韩跃, 谭清成, 王莉莉, 张悠然, 江震, authorCompany=null, correspAuthors=张悠然, authorNote=

韩跃（2002—），本科在读，研究方向：艾滋病预防与控制

, correspAuthorsNote=
张悠然，E-mail：
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韩跃（2002—），本科在读，研究方向：艾滋病预防与控制

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韩跃（2002—），本科在读，研究方向：艾滋病预防与控制

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BMC Infectious Diseases, 2018, 18(1): 124., articleTitle=null, refAbstract=null), Reference(id=1321170867904692583, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=27, rfOrder=26, authorNames=null, journalName=null, refType=null, unstructuredReference=Avenir Health. Who we are[EB/OL]. (2025-01-26)[2025-01-26]. https://avenirhealth.org/about.html, articleTitle=null, refAbstract=null), Reference(id=1321170867992772968, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=28, rfOrder=27, authorNames=null, journalName=null, refType=null, unstructuredReference=江震, 张悠然, 王莉莉, 等. 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Baseline data of primary and secondary indicators of Optima HIV

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一级指标二级指标
A 人口规模A1 女性性交易人员（female sex worker, FSW）/人
　A2 嫖客/人
　A3 吸毒人群（people who inject drugs, PWID）/人
　A4 男男性行为者 （men who have sex with men, MSM）/人
　A5 其他关键人群/人
　A6 ≥50岁男性/人
　A7 ≥ 50岁女性/人
　A8 15～49岁男性/人
　A9 15～49岁女性/人
　A10 0～14岁男性/人
　A11 0～14岁女性/人
B HIV 感染率B1 HIV 感染率/%
C 其他流行病学C1 每年死于非HIV相关原因的人数百分比/%
　C2 任何溃疡性性传播疾病（sexually transmitted infections, STIs）的感染率/%
　C3 结核病 感染率/%
D HIV防治D1 每年HIV检测次数/人次
　D2 每年HIV诊断数/人
　D3 每年新增HIV感染的模型估计/人
　D4 HIV 感染率的模型估计/%
　D5 HIV感染者（people living with HIV, PLHIV）数量的模型估计/人
　D6 HIV相关死亡人数 /人
　D7 每年新增ART（antiretroviral therapy）治疗的人数/人
　D8 感染者知道自己感染状况的比例/%
　D9 确诊的感染者寻求服务的比例/%
　D10 寻求服务的人群中最终接受治疗的人数/%
　D11 接受治疗人群的病毒抑制率/%
D12 过去12个月接受HIV检测的人口百分比%
　D13 新诊断的感染者中CD4计数低于200的百分比/%
　D14 接受治疗的人数/人
D15 单位治疗费用/美元
　D16 暴露前后预防覆盖率/%
　D17 接受预防母婴传播（preventing mother to child transmission, PMTCT）女性人数/人
　D18 生育率%
　D19 HIV阳性产妇母乳喂养比例/%
D20 确诊和治疗的平均时间间隔/年
D21 CD4<200的人确诊和治疗的平均时间间隔/年
　D22 AIDS失访率/%
D23 CD4<200的人失访率/%
　D24 接受治疗的感染者失访的百分比/%
　D25 病毒载量监测/拷贝每毫升
E 性行为E1 每人每年与固定伴侣的平均性行为次数/人次
　E2 每人每年与临时伴侣的平均性行为次数/人次
　E3 每人每年与商业伴侣的平均性行为次数/人次
　E4 最近一次与固定伴侣发生性行为时，使用避孕套的人的百分比/%
　E5 最近一次与临时伴侣发生性行为时，使用避孕套的人的百分比/%
　E6 最近一次与商业伙伴发生性行为时，使用避孕套的人的百分比/%
　E7 接受过包皮环切术的男性百分比/%
F 注射行为F1 每人每年平均注射次数/人次
　F2 最近一次注射时共用针头/注射器的人的百分比/%
　F3 接受阿片类药物替代治疗的注射吸毒者人数/人
H 人口转变H1 风险相关人群年度转化的平均年数/年
), ArticleFig(id=1321170863932686664, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, language=CN, label=表1, caption=

Optima HIV基础数据一、二级指标

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一级指标二级指标
A 人口规模A1 女性性交易人员（female sex worker, FSW）/人
　A2 嫖客/人
　A3 吸毒人群（people who inject drugs, PWID）/人
　A4 男男性行为者 （men who have sex with men, MSM）/人
　A5 其他关键人群/人
　A6 ≥50岁男性/人
　A7 ≥ 50岁女性/人
　A8 15～49岁男性/人
　A9 15～49岁女性/人
　A10 0～14岁男性/人
　A11 0～14岁女性/人
B HIV 感染率B1 HIV 感染率/%
C 其他流行病学C1 每年死于非HIV相关原因的人数百分比/%
　C2 任何溃疡性性传播疾病（sexually transmitted infections, STIs）的感染率/%
　C3 结核病 感染率/%
D HIV防治D1 每年HIV检测次数/人次
　D2 每年HIV诊断数/人
　D3 每年新增HIV感染的模型估计/人
　D4 HIV 感染率的模型估计/%
　D5 HIV感染者（people living with HIV, PLHIV）数量的模型估计/人
　D6 HIV相关死亡人数 /人
　D7 每年新增ART（antiretroviral therapy）治疗的人数/人
　D8 感染者知道自己感染状况的比例/%
　D9 确诊的感染者寻求服务的比例/%
　D10 寻求服务的人群中最终接受治疗的人数/%
　D11 接受治疗人群的病毒抑制率/%
D12 过去12个月接受HIV检测的人口百分比%
　D13 新诊断的感染者中CD4计数低于200的百分比/%
　D14 接受治疗的人数/人
D15 单位治疗费用/美元
　D16 暴露前后预防覆盖率/%
　D17 接受预防母婴传播（preventing mother to child transmission, PMTCT）女性人数/人
　D18 生育率%
　D19 HIV阳性产妇母乳喂养比例/%
D20 确诊和治疗的平均时间间隔/年
D21 CD4<200的人确诊和治疗的平均时间间隔/年
　D22 AIDS失访率/%
D23 CD4<200的人失访率/%
　D24 接受治疗的感染者失访的百分比/%
　D25 病毒载量监测/拷贝每毫升
E 性行为E1 每人每年与固定伴侣的平均性行为次数/人次
　E2 每人每年与临时伴侣的平均性行为次数/人次
　E3 每人每年与商业伴侣的平均性行为次数/人次
　E4 最近一次与固定伴侣发生性行为时，使用避孕套的人的百分比/%
　E5 最近一次与临时伴侣发生性行为时，使用避孕套的人的百分比/%
　E6 最近一次与商业伙伴发生性行为时，使用避孕套的人的百分比/%
　E7 接受过包皮环切术的男性百分比/%
F 注射行为F1 每人每年平均注射次数/人次
　F2 最近一次注射时共用针头/注射器的人的百分比/%
　F3 接受阿片类药物替代治疗的注射吸毒者人数/人
H 人口转变H1 风险相关人群年度转化的平均年数/年
), ArticleFig(id=1321170863995601225, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, language=EN, label=Tab.2, caption=

Optima HIV intervention program

, figureFileSmall=null, figureFileBig=null, tableContent=
直接干预间接干预
ART依从性支持（adherence support）
安全套发放（condom promotion and distribution）实验室监测（lab monitoring）
HIV检测（HIV testing services）ART前期溯源（Pre-ART tracing）
FSW干预（FSW programs）社会和行为改变沟通（social and behavior change communication）
MSM干预（MSM programs）卫生基础设施（health infrastructure）
吸毒人群干预（PWID programs）降低HIV风险的救济补助（cash transfers for HIV risk reduction）
预防母婴传播（PMTCT）环境支持（enabling environment）
阿片替代疗法（opiate substitution therapy）人力资源（human resources）
针具交换项目（needle syringe programs）管理（management）
男性包皮环切术（voluntary medical male circumcision）监测和评价（monitoring and evaluation）
暴露前预防（pre-exposure prophylaxis, PrEP）孤儿和弱势照顾（orphans and vulnerable care）
暴露后预防（post-exposure prophylaxis, PEP）社会支持（social protection）
性传播疾病的诊断和治疗（diagnosis and treatment of sexually transmitted infections）其他（other HIV care）
), ArticleFig(id=1321170864066904394, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, language=CN, label=表2, caption=

Optima HIV干预项目

, figureFileSmall=null, figureFileBig=null, tableContent=
直接干预间接干预
ART依从性支持（adherence support）
安全套发放（condom promotion and distribution）实验室监测（lab monitoring）
HIV检测（HIV testing services）ART前期溯源（Pre-ART tracing）
FSW干预（FSW programs）社会和行为改变沟通（social and behavior change communication）
MSM干预（MSM programs）卫生基础设施（health infrastructure）
吸毒人群干预（PWID programs）降低HIV风险的救济补助（cash transfers for HIV risk reduction）
预防母婴传播（PMTCT）环境支持（enabling environment）
阿片替代疗法（opiate substitution therapy）人力资源（human resources）
针具交换项目（needle syringe programs）管理（management）
男性包皮环切术（voluntary medical male circumcision）监测和评价（monitoring and evaluation）
暴露前预防（pre-exposure prophylaxis, PrEP）孤儿和弱势照顾（orphans and vulnerable care）
暴露后预防（post-exposure prophylaxis, PEP）社会支持（social protection）
性传播疾病的诊断和治疗（diagnosis and treatment of sexually transmitted infections）其他（other HIV care）
), ArticleFig(id=1321170864125624651, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, language=EN, label=Tab.3, caption=

Optima HIV output parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
输出参数指标
总体情况预算分配：优化前后，资金在各个干预项目上的变化
干预项目覆盖人数
级联诊疗（条形图）：显示一定时间段，PLHIV在不同情况下，如诊断，治疗等的级联诊疗情况
HIV防治效果（总数、关键人群）HIV相关死亡人数
新增HIV感染人数
PLHIV相关（总数、关键人群）PLHIV人数
AIDS患病人数
确诊的PLHIV人数及百分比
新入组治疗的PLHIV人数及百分比
接受护理服务的PLHIV人数及百分比
接受治疗的PLHIV人数及百分比
病毒抑制的PLHIV人数及百分比
HIV流行水平（总数、关键人群）HIV 感染率/%
HIV新发感染率/每100人
HIV新诊断数/人数
预防母婴传播水平（总数、关键人群）HIV阳性新生儿人数
HIV阳性孕妇人数
接受PMTCT的HIV阳性孕产妇/人数
人群（总数、关键人群）人口规模/人数
与HIV有关的伤残调整生命年/DALYs
), ArticleFig(id=1321170864222093644, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170855934148882, language=CN, label=表3, caption=

Optima HIV输出参数

, figureFileSmall=null, figureFileBig=null, tableContent=
输出参数指标
总体情况预算分配：优化前后，资金在各个干预项目上的变化
干预项目覆盖人数
级联诊疗（条形图）：显示一定时间段，PLHIV在不同情况下，如诊断，治疗等的级联诊疗情况
HIV防治效果（总数、关键人群）HIV相关死亡人数
新增HIV感染人数
PLHIV相关（总数、关键人群）PLHIV人数
AIDS患病人数
确诊的PLHIV人数及百分比
新入组治疗的PLHIV人数及百分比
接受护理服务的PLHIV人数及百分比
接受治疗的PLHIV人数及百分比
病毒抑制的PLHIV人数及百分比
HIV流行水平（总数、关键人群）HIV 感染率/%
HIV新发感染率/每100人
HIV新诊断数/人数
预防母婴传播水平（总数、关键人群）HIV阳性新生儿人数
HIV阳性孕妇人数
接受PMTCT的HIV阳性孕产妇/人数
人群（总数、关键人群）人口规模/人数
与HIV有关的伤残调整生命年/DALYs
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HIV防治资源配置分析工具Optima HIV研究进展
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韩跃 1 , 谭清成 1 , 王莉莉 1 , 张悠然 1, *, * , 江震 2
中国公共卫生 | 综　述 2025,41(8): 1005-1012
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中国公共卫生 |综　述 2025 , 41 (8) : 1005 -1012
HIV防治资源配置分析工具Optima HIV研究进展
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韩跃（2002—），本科在读，研究方向：艾滋病预防与控制

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韩跃（2002—），本科在读，研究方向：艾滋病预防与控制

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韩跃1, 谭清成1, 王莉莉1, 张悠然1, *, * , 江震2
作者信息
  • 1安徽医科大学卫生管理学院，合肥 230032
  • 2中国疾病预防控制中心性病艾滋病预防控制中心，北京 102206
通讯作者:
张悠然，E-mail：
作者简介:

韩跃（2002—），本科在读，研究方向：艾滋病预防与控制

Research progress on a resource allocation tool for HIV prevention and control Optima HIV: a review
Yue HAN1, Qingcheng TAN1, Lili WANG1, Youran ZHANG1 , Zhen JIANG2
Affiliations
  • 1School of Health Management, Anhui Medical University, Hefei 230032, China
  • 2Division of Prevention and Intervention, National Center for AIDS and STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
    • Corresponding Author:
    ZHANG Youran, E-mail:
出版时间: 2025-08-10 doi: 10.11847/zgggws1147168
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摘要
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科学的公共卫生资源配置和优化，可以推动艾滋病防治工作的效率和质量提升。人类免疫缺陷病毒（HIV）资源配置分析工具Optima HIV通过描述疾病流行情况，分析卫生投入与健康产出的关系，探索HIV防治干预资源的最佳配置，在HIV资源配置和优化方面提供技术支持。本文从研发背景、理论框架、工具模块、参数结构及在全球范围内的应用情况5个方面对Optima HIV软件进行综述，为我国的艾滋病防治和科学的资源分配提供参考。

艾滋病  /  人类免疫缺陷病毒  /  成本效果分析  /  Optima HIV  /  资源配置

Scientific allocation and optimization of public health resources can promote the efficiency and quality of AIDS prevention and control work. The Optima HIV, a human immunodeficiency virus (HIV) resource allocation analysis tool, provides technical support for HIV resource allocation and optimization by describing the epidemic situation, analyzing the relationship between health inputs and health outputs, and exploring the optimal allocation of HIV prevention and control intervention resources. This article reviews the Optima HIV software from five aspects: research and development background, theoretical framework, tool modules, parameter structure, and global application, to provide a reference for AIDS prevention and control and scientific resource allocation in China.

AIDS  /  human immunodeficiency virus (HIV)  /  cost-effectiveness analysis  /  Optima HIV  /  resource allocation
韩跃, 谭清成, 王莉莉, 张悠然, 江震. HIV防治资源配置分析工具Optima HIV研究进展. 中国公共卫生, 2025 , 41 (8) : 1005 -1012 . DOI: 10.11847/zgggws1147168
Yue HAN, Qingcheng TAN, Lili WANG, Youran ZHANG, Zhen JIANG. Research progress on a resource allocation tool for HIV prevention and control Optima HIV: a review[J]. Chinese Journal of Public Health, 2025 , 41 (8) : 1005 -1012 . DOI: 10.11847/zgggws1147168
正文
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艾滋病（acquired immune deficiency syndrome，AIDS）给个人、家庭和社会带来了极大的疾病经济负担，面对卫生资源的有限性，如何科学精准地进行资源配置规划从而实现防治效果最大化是艾滋病防治工作中的一个重要问题。2017年，我国政府相继出台了《中国遏制与防治艾滋病“十三五”行动计划》（国办发〔2017〕8号）[1]、《遏制艾滋病传播实施方案（2019—2022年）》（国卫疾控发〔2019〕54号）[2]和《中国遏制与防治艾滋病规划（2024—2030年）》（国办发〔2024〕51号）[3]等文件，明确强调各级政府要根据卫生投入政策，合理安排艾滋病防治经费，提高资金使用效益。当前艾滋病综合防治干预内容和形式多样化，对经费投入的精细化管理需求日益加强，亟需明晰详细的资源配置方法和工具来优化资源配置，进一步提高艾滋病防治效率。本研究介绍人类免疫缺陷病毒（human immunodeficiency virus, HIV）防治领域资源配置分析工具 Optima HIV 的基本理论与方法，为决策者提供HIV防治资源分配的循征决策工具。
1　Optima HIV的背景介绍
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Optima HIV是Optima决策科学联盟在世界银行、全球基金和美国疾病控制与预防中心等全球卫生机构的资助下，密切合作开发和应用的一种免费、开源的量化工具，可以公开在线使用（在线网址：https://optimamodel.com）[4]。Optima HIV模型的前身创建于2004年，2012年推出Optima HIV工具。截止到2023年，它已在全球50多个国家和地区得到应用[5]。Optima HIV的应用和研究结果，为联合国大会、全球防治艾滋病、肺结核和疟疾基金、东南亚国家联盟等国际组织及一些国家和地区的HIV/AIDS 战略规划，提供技术支持和决策参考依据，同时也为改善资金配置效率，提高各国HIV防治健康产出和服务质量，更好地实现HIV防治目标发挥重要作用。
2　Optima HIV的理论框架
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Optima HIV基于传染病舱室理论模型研发，其运行原理是将流行病学、HIV相关行为、卫生支出和干预覆盖等数据整合到数学模型中，描述HIV传播和疾病动态，以及资金投入与健康产出之间的关系，对成本和健康产出进行综合分析，定量分析HIV防治资源的最佳配置。模型以HIV作为目标传染性疾病，计算未感染个体的感染率，即感染力（force-of-infection）是该模型的主要内容。该指标值取决于个体在给定时期内暴露的风险事件的数量和类型（即个体在其所在的人群中或通过与其他人群之间相互接触所发生的暴露事件）以及每个事件的感染概率。其公式为a=1–（1–b）n，其中a是感染力，b是每个事件的传播概率，n是有风险事件的有效数量（即，n表示与HIV感染者可能发生HIV传播的互动事件的平均数量）[6]。
在资源配置中，为充分考虑卫生干预服务的高覆盖可能会产生的饱和效应，对不同干预服务的边际成本以及对HIV流行的影响进行预测，Optima HIV针对每项HIV干预项目，构建两组逻辑曲线：干预成本–干预覆盖关系曲线以及干预覆盖–健康产出关系曲线。干预覆盖–健康产出关系曲线（通常为线性关系）是将覆盖率与临床治疗或高危行为结果建立关联。假设临床治疗或高危行为的所有变化都是由于项目资金的变化引起，这一基本假设有利于简化问题，但也存在与真实世界不符的局限性。在干预覆盖–健康产出的线性逻辑曲线构建基础上，Optima HIV允许用户设定一个/组目标，包括某具体指标改变和预算投入额变化等，然后通过贝叶斯自适应随机下降算法（bayesian adaptive stochastic descent algorithm）来识别大量可能的干预组合中的最佳干预组合[7]。即从基线资源分配开始，针对特定的HIV干预项目随机改变分配。如果这些改变改善了结果，则算法会增加对该干预项目实施的时长。重复此过程，直到无法进一步改善，以此确定最佳的资源分配方式。其基本公式为：$ E_k^{\pm}=f\left[x+\delta(i)\right] $，其中E=f(x)是目标函数，E是要最小化（或最大化）的标量误差（或其他量），x = [x1，x2，...，xn]是n元向量参数，δ(i)是一个n元向量。同时，Optima使用马尔可夫链蒙特卡罗（markov chain monte carlo, MCMC）算法执行自动校准和不确定性计算来拟合流行病学数据。重复该算法，生成一系列的流行转归预测。不同预测结果之间的差异代表了流行病学趋势预测的不确定性。与此同时，如果目标设定项目资金的投入会随着时间变化而变化，那么每个干预项目的最佳资源分配也是随时间变化的。其基本公式为：$ A\left(t\right)=b{{e}^{st}}^{2} $ 其中A是随时间t而变化的项目资金分配，b是既定干预的总预算，而s是一个形态参数，如果s=0，则干预资金额恒定（=b），如果s>0，则随着时间的推移A会增加，反之则减小[8]。
3　Optima HIV工具模块（图1）
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Optima HIV包括人群设定（projects）、参数校准（calibration）、干预集合（programs）、成本效果函数（cost-function）、模拟场景（scenarios）、优化分析（optimization）、地理空间（geospatial） 共7个基本模块[9]。（1）人群设定（projects）模块需要使用者根据当地HIV流行病学趋势和分析需求选择和设定重点人群。（2）参数校准（calibration）模块，需要输入当地HIV 感染率、诊断率、发病率和死亡率的真实历史数据。上述指标及其动态之间的关系由不同人群的人口学、行为学和流行病学特征交互作用来共同决定。（3）干预集合（programs）模块将HIV干预项目分为直接干预和间接干预两种类型。直接干预是指具有明确指向性，明显减少HIV传播、发病率或死亡率的项目措施，如吸毒人群针具交换、MSM人群安全套使用等。间接干预是指对健康没有直接影响或无法明确影响具体目标人群的措施，如人力资源、有利环境、社会保护、监测和评估、与HIV相关的孤儿和弱势儿童干预、其他HIV护理以及其他非针对性干预。（4）成本效果函数（cost-function）模块，需要完善干预项目的详细信息，包括干预项目的总体花费、覆盖水平、单位成本以及效果参数等。（5）情境拟合（scenarios）模块，是在基本数据（表1）不变的情况下，通过对干预项目效果（发病率、 感染率、临床治疗效果和风险行为）、预算投入和覆盖率3种类型参数调整，计算干预项目成本和健康效果的变化值（与基线进行比较）。（6）优化分析（optimization） 模块是指运用数学模型算法（成本–效果函数）确定最有效的资源分配，以实现用户指定的目标。该模块包括两种优化类型：资金优化用于分析实现特定发病率或死亡率目标所需的最低资金额度；结果优化则用于分析指定预算的最大健康效果产出。（7） 地理空间（geospatial） 模块通过预算目标曲线（ budget-objective curves, BOC）算法确定指定金额的预算如何实现跨区域（例如多个国家或一个国家内的多个地区）的最佳分配。具体操作包括3个步骤：a 针对每个区域校准模型，b 确定每个区域在不同预算水平内的最佳分配，以及c 在每个区域中，健康产出最大化的预算水平（例如减少新发感染和/或减少HIV相关死亡），在所有地区固定总预算的前提下，评估每个地区可能的资金优化配置水平，并将资金分配给具有最大边际成本效益的地区[10]。Optima HIV各模块的逻辑框架见图1：
4　Optima HIV 参数结构
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4.1　基础数据（表1）
Optima HIV基础数据包括：A.人口规模；B.HIV 感染率；C.检测与治疗；D.HIV防治相关的可选指标；E.诊疗相关参数；F.性行为；G.注射行为；H.人口转变。具体一二级指标见表1：
4.2　干预项目（表2）
Optima HIV预提供了以下干预项目，使用者可以根据当地实际干预情况进行选择或者另外添加设定。
4.3　输出参数（表3）
Optima HIV提供情境拟合和优化分析两类模块，操作人员可以输出以下参数。针对用户需求，Optima HIV提供图表和Excel表格两种输出形式。其中，图表通常将基准数据和优化后的数据放在同一坐标系进行比较，具有鲜明的色彩和明显的对比效果；Excel则侧重于对数据具体数值的展示。
5　Optima HIV在全球范围内的应用情况
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为推进联合国2030年终结艾滋病流行可持续发展目标的实现，国际社会使用Optima HIV模型开展了多种经济学评价研究。在干预项目评估方面，Ten Brink D C等[11]以2022年为基线，评估在亚洲8个国家的MSM人群中扩大PrEP的成本效益，结果表明在HIV高流行地区实施PrEP可能具有成本效益，降低PrEP药物成本，则PrEP会在更长的时间范围内持续发挥成本效益。Minnery M等[12]通过数据拟合发现，如果优化斯威士兰地区男性包皮环切术 （VMMC）、HIV检测和ART治疗等服务提供模式，可以进一步降低HIV新发感染和节约成本。Stuart R M等[13]展示了南非的约翰内斯堡市在2017—2030年扩大HIV干预覆盖带来的影响，如果将ART治疗人数扩增80%（与2016年基线相比）可以进一步避免新发感染和死亡，如果合理扩大VMMC、安全套分发和FSW外展干预覆盖面，可以进一步减少新发感染（4%～15%），并减少总体治疗投资需求。Marukutira T等[14]证实了向博茨瓦纳的流动人口提供HIV服务可以进一步减少HIV感染率和死亡人数，逐步改善效率，才能在2020年和2030年实现90-90-90和95-95-95的防治目标。Bershteyn A等[15]分别在不同地区使用不同评估工具（南非使用EMOD、马拉维使用Optima，撒哈拉以南非洲低收入和中等收入国家使用Synthesis）测算为维持ART治疗提供的相关服务（如差异化护理、移动医疗、工具支持、跟踪随访等）的成本和效果，结果均表明，这些服务可以进一步增加ART治疗维持率从而降低HIV传播。
在疫情发展趋势预测方面，Jewell B L等[16]运用Goals、Optima HIV、HIV Synthesis、EMOD等多个工具展示了撒哈拉以南非洲地区COVID-19导致的HIV检测、预防和治疗服务中断后发生的额外HIV相关死亡和新发感染，结果表明，与没有中断干预服务相比，如果50%正在接受治疗的HIV感染者的ART药物供应中断6个月，预计将导致一年内与HIV相关的死亡人数增加1.63倍。Stover J等[17]运用Goals、HIV Synthesis、Optima HIV和EMOD共4项工具评估了在COVID-19大流行期间提供自愿男性包皮环切术、HIV诊断检测、病毒载量检测和预防母婴传播4项HIV干预服务的风险和效益，结果表明，HIV干预中断造成的HIV相关死亡风险比额外的COVID-19相关死亡高100倍。Stover J等[18]还运用Optima HIV、AEM、Goals3种工具预测，如果能够在2025年实现司法改革、消除污名和歧视以及性别平等等方面的艾滋病应对目标，则全球新发HIV感染和艾滋病死亡率将降至4.4/10万人和3.9/10万人，到2030年，新的HIV感染和艾滋病相关死亡的数量将减少90%，全球总人口的感染率将在0.15%以下。
在资金分配效率方面，Stuart R M等[19]系统综述了23个国家的Optima建模研究，结果表明HIV资源的最佳分配取决于预算经费以及每个国家流行病学特征、应对措施和目标，总体而言，扩大治疗的覆盖范围能够很大程度地提高资源利用率，减少新发感染和死亡。该团队利用白俄罗斯、秘鲁、多哥和缅甸的数据分析得出结论，如果预算非常有限，最佳的HIV应对措施是专注于资助ART和PMTCT，随着预算增加，再考虑增加其他的HIV干预项目[20]。该研究团队还对苏丹和多哥同期HIV防治项目进行比较，发现在苏丹，2014—2020年HIV防治目标聚焦最大限度减少新发感染，可实现健康效果产出（福利）最大化预算分配原则；在多哥2015—2020年期间主要目标应聚焦最大限度地减少死亡和新感染，同时确保不同亚人群的新发感染数量没有增加，该研究比较了健康福利最大化和帕累托有效配置两种HIV资金配置方式产生的不同影响，认为需要将“避免降低任何个人或亚群体福利”的帕累托效率配置标准纳入HIV资源优化配置的研究范畴，帕累托有效配置可以作为HIV资源配置效率分析的有益补充[21]。Kelly S L等[22]通过对全球范围内的44个国家建模分析发现，2016—2030年，如果各个国家内部优化分配其HIV资源，能够降低26%的新发感染，而如果在国家间重新分配国际资金，可以降低33%的新发感染；如果要实现2030年将HIV发病率降低到2010年的90%，则需要将当前总年度预算增加3倍以上。Kedziora D J等[10]利用Optima的“地理优化功能”评估了乌克兰3个州（米科拉耶夫、波尔塔瓦和日托米尔）的HIV项目资金的分配，以最大限度地减少新发感染人数，结果表明，在优化之前，2016—2030年，预计3个州与HIV相关的伤残调整生命年（DALYs）总数为 244 000人年，如果各州内部资源优化配置，DALYs可以减少至181 000人年，如果允许各州之间重新分配资金（即地理优化），DALYs将进一步减少至173 000人年。
6　Optima HIV的特点和局限性
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6.1　Optima HIV的特点
Optima HIV的主要特点是能够进行资源优化拟合，其数学优化函数可以用于计算不同干预项目的最佳资源分配，以实现HIV战略目标，并根据国家宏观经济环境进行HIV相关的资源配置预测。例如，在固定预算下如何最大限度地减少新发感染、死亡或伤残调整生命年，或如何根据特定目标，实现成本最小化。Optima HIV在选择建模人群和HIV干预项目、输入数据以及输出类型方面具有灵活性，可以对不同年龄组的不同风险群体（例如性交易者、MSM人群、吸毒者等）进行拟合。
国际社会研发了多种可用于支持资源配置的工具，主要用于HIV资源分配效率、HIV项目覆盖率及健康产出、HIV项目成本投入与实现政策承诺关系等的建模，如EMOD-HIV（Epidemiological MODeling software，流行病学建模软件）、AEM（Asian Epidemic Model，亚洲艾滋病流行预测模型）[19]以及Goals（Spectrum子模块）[23]。EMOD-HIV由Intellectual Ventures Laboratory流行病学建模小组的研究人员设计开发，是用于HIV资源配置和规划的定量分析工具[24]。该工具由C++语言开发，基于个体的建模框架（Agent Based Modeling），将性传播个体属性（如性伴侣数量、风险行为模式）等疾病传播网络（network）参数与HIV感染的宿主内生物学机制（intrahost）的属性（如病毒载量动态、耐药性、免疫状态）参数纳入微观 HIV传播模型，评估各项预防和治疗方案的效果[25]。EMOD不支持各项干预项目的单位成本等相关参数的输入和输出，因此，该工具不能像Optima一样，提出“最佳”分配模式或建议如何在预防与护理之间进行特定的资源分配。AEM是根据亚洲主要流行特点,利用已有的HIV相关流行病学和行为学资料对HIV流行和防治进行估算和预测的半经验化过程模型[26]。AEM目前仅包含一个基本的成本计算组件，无法进行完整的成本效益分析，也无法进行资源估算或分配研究。Goals是由Avenir Health[27]开发的一种分区HIV模拟模型，根据影响传播的行为和特征，计算不同风险人群之间的HIV传播情况[28]。该模型旨在帮助规划者了解不同资金状况和覆盖水平对降低HIV发病率和流行率的影响，其在疫情估计模型、数据要求和拟合目标上与Optima较为类似，都需要详细的人口统计、流行病学、行为和治疗数据，并且都被用作HIV战略规划的一部分。然而，Goals中的人群（包括MSM、IDU以及低、中、高危人群）和HIV干预项目（包括避孕套推广、外展干预、男性包皮环切、VCT、ART以及PMTCT）都是固定的[29]。相比之下，Optima允许用户以特定地理区域内的特定亚人群为目标，采用不同的服务提供模式来自定义HIV项目，并指定干预效果[9]。Goals与Optima之间的另一个区别是，Goals需要输入更多、更详细的结构化数据才能在流行病轨迹上给出更稳健和有意义的结果。Optima HIV有两种使用形式，一种是在线版本，其对数据填报要求高，如果缺乏良好的数据，模型难以运行，另一种是基于Python的形式，其参数填报与其他HIV模型有很好的兼容性，该版本适用于精通计算机的研究人员。鉴于上述模型在揭示HIV传播与疾病进展沿用的通用逻辑，开发通用型结构化的参数收集工具，对提升模型拟合的准确性、通用性非常重要。
研究人员无论使用上述哪种软件都需要经过机构调查、专家咨询、文献检索等多种方式，尽可能提高数据完整性、科学性、准确性。确定开展Optima拟合后，首先需要根据Optima HIV的参数指标需求，研制调查表，逐项明确各项指标收集方法和来源，包括但不限于当地实际调查、专家咨询及其他模型拟合结果，然后经过多轮验证，校准Optima相关参数。具体操作可参阅课题组前期相关文章[6]。Optima的灵活性意味着通过减少人口群体的数量和传播模式的数量，可以降低其数据要求，使其与其他更简单的模型保持一致。
6.2　Optima HIV的局限性
首先，Optima HIV聚焦HIV领域内部的资源优化分配，不涉及HIV与其他疾病间的资源分配（例如HIV与结核病）。其次，尽管Optima HIV具有经济分析能力，可以为投资者提供信息，但它不是预算编制工具，干预的实际预算还需结合其他工具；第三，Optima HIV提供的模型优化方案可能与利益相关者期望不相符合；第四，模型拟合可能忽略了不同干预措施之间的潜在关联。因此，在解读模型拟合结果的同时，还需要综合考虑艾滋病防治的多种因素。
7　总　结
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Optima HIV是HIV领域的成本效果分析工具之一，通过现实世界数据的输入，利用数学模型分析流行病学、HIV相关行为、卫生支出和干预覆盖等数据，描述HIV传播和疾病动态、资金投入与健康产出之间的关系，通过对成本和健康产出的定量分析，探索HIV防治干预资源的最佳配置，为解决政策制定者、卫生规划者和项目实施者遇到的实际问题发挥技术支持作用。

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doi: 10.11847/zgggws1147168
  • 接收时间：2025-02-19
  • 首发时间：2026-10-25
  • 出版时间：2025-08-10
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  • 收稿日期：2025-02-19
  • 修回日期：2025-03-31
  • 录用日期：2025-07-09
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    1安徽医科大学卫生管理学院，合肥 230032
    2中国疾病预防控制中心性病艾滋病预防控制中心，北京 102206

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