From 90-90-90 to 95-95-95 and beyond: Optimizing and targeting combination HIV prevention for Zimbabwe and Kwazulu Natal

从 90-90-90 到 95-95-95 及以后：优化并瞄准津巴布韦和夸祖鲁纳塔尔省的艾滋病毒联合预防

• 批准号: 10018459
• 负责人: Ronald Scott Braithwaite
• 金额: $ 61.13万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-20 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10018459
• 关键词: AIDS prevention; Anxiety; Appointment; Caring; Characteristics; Child Care; Collaborations; Contact Tracing; Continuity of Patient Care; Country; Disease; Epidemic; Funding; Goals; HIV; Health Benefit; Health Resources; Healthcare; Heterogeneity; Human immunodeficiency virus test; Incidence; Individual; Inequality; Intervention; Link; Male Circumcision; Mental Depression; Mental Health; Mental disorders; Migrant Workers; Modeling; Morbidity - disease rate; Pathway interactions; Pattern; Persons; Pharmaceutical Preparations; Policies; Population; Prevention; Prevention strategy; Province; Publishing; Randomized Controlled Trials; Readability; Research Personnel; Resource Allocation; Resources; Role; Site; South Africa; Text; Viral; Zimbabwe; alcohol risk; alcohol use disorder; base; demographics; design; financial incentive; high risk population; improved; indexing; mathematical model; mortality; outreach; pandemic disease; sociodemographics; surveillance data; testing services; tool

ABSTRACT/SUMMARY Published surveillance data together with mathematical modeling make it clear that UNAIDS 2030 goals (90% reduction in HIV incidence) are not going to be met with current spending and resource allocation, as well as UNAIDS 2020 goals (90% of infected are detected, 90% of detected are linked to care, and 90% of linked to care are virally suppressed) are not going to be met by 2020. Existing models suggest a tripling in HIV spending (from $12.8 billion to $40 billion per year) would be necessary to meet these goals, together with an optimizing of that spending. Indeed, without optimization, the necessary spending for that goal would likely top $52 billion per year. To achieve UNAIDS 2030 goals it will be necessary to critically assess the role of all available tools and tailor strategies to maximize their impact. However, current mathematical models omit important tools in the arsenal for achieving 2030 goals in resource-limited regions, including: (1) Specific interventions that target the HIV care continuum (in particular specific interventions with randomized controlled-trial evidence include SMS- based text reminders for appointments and/or medications and combination interventions similar to Link4Health [including accelerated medication initiation, SMS-based text reminders, care/information package +/- noncash financial incentive]), (2) targeting interventions to high risk populations (such as those with alcohol use disorders [AUDs] and common mental disorders [CMDs]) that are specifically relevant to a region’s demographics and policy constraints, and (3) alternate timing of the peak of HIV spending (earlier is better because it leads to “getting ahead of the epidemic” but may be less feasible). Accordingly, our proposal incorporates these tools into a mathematical model to evaluate the allocative efficiency of a wide spectrum of combination HIV prevention strategies focusing on the countries of Zimbabwe and South Africa because of their disproportionate burden of HIV morbidity and mortality.

摘要/摘要 已发布的监视数据以及数学建模清楚地表明，UNAID 2030目标（90％ 减少艾滋病毒事件）不会通过当前的支出和资源分配以及 UNAIDS 2020目标（检测到90％的感染，90％的检测到与护理有关 几乎被抑制了护理）到2020年将无法满足。现有模型表明艾滋病毒三倍 满足这些目标是必要的支出（每年128亿美元至400亿美元） 优化该支出。确实，如果没有优化，该目标的必要支出可能会达到顶峰 每年520亿美元。 为了实现UNAIDS 2030目标，有必要批判性地评估所有可用工具的作用和裁缝 最大化其影响的策略。但是，当前的数学模型省略了阿森纳中的重要工具 用于在资源有限的地区实现2030个目标，包括：（1）针对艾滋病毒的特定干预措施 护理连续体（特别是具有随机控制证据的特定干预措施包括SMS- 基于约会和/或药物的基于的文本提醒和组合干预措施类似 link4Health [包括加速药物启动，基于SMS的文本提醒，护理/信息包 +/-非现金经济激励措施]），（2）针对高风险人群的干预措施（例如那些饮酒的人群 使用与地区特别相关的疾病[AUDS]和常见的精神障碍[CMDS]） 人口统计和政策限制，以及（3）艾滋病毒支出高峰的替代时机（早期更好 因为它导致“领先于流行病”，但可能不太可行）。据此，我们的建议 将这些工具纳入数学模型，以评估广泛范围的分配效率 艾滋病毒预防策略的重点是津巴布韦和南非国家 他们对艾滋病毒的发病率和死亡率的伯恩伯恩（Burnen）不成比例。