Burnet Institute, Melbourne, VIC, Australia; Monash University, Melbourne, VIC, Australia.
Burnet Institute, Melbourne, VIC, Australia.
Lancet HIV. 2018 Apr;5(4):e190-e198. doi: 10.1016/S2352-3018(18)30024-9. Epub 2018 Mar 11.
BACKGROUND: To move towards ending AIDS by 2030, HIV resources should be allocated cost-effectively. We used the Optima HIV model to estimate how global HIV resources could be retargeted for greatest epidemiological effect and how many additional new infections could be averted by 2030. METHODS: We collated standard data used in country modelling exercises (including demographic, epidemiological, behavioural, programmatic, and expenditure data) from Jan 1, 2000, to Dec 31, 2015 for 44 countries, capturing 80% of people living with HIV worldwide. These data were used to parameterise separate subnational and national models within the Optima HIV framework. To estimate optimal resource allocation at subnational, national, regional, and global levels, we used an adaptive stochastic descent optimisation algorithm in combination with the epidemic models and cost functions for each programme in each country. Optimal allocation analyses were done with international HIV funds remaining the same to each country and by redistributing these funds between countries. FINDINGS: Without additional funding, if countries were to optimally allocate their HIV resources from 2016 to 2030, we estimate that an additional 7·4 million (uncertainty range 3·9 million-14·0 million) new infections could be averted, representing a 26% (uncertainty range 13-50%) incidence reduction. Redistribution of international funds between countries could avert a further 1·9 million infections, which represents a 33% (uncertainty range 20-58%) incidence reduction overall. To reduce HIV incidence by 90% relative to 2010, we estimate that more than a three-fold increase of current annual funds will be necessary until 2030. The most common priorities for optimal resource reallocation are to scale up treatment and prevention programmes targeting key populations at greatest risk in each setting. Prioritisation of other HIV programmes depends on the epidemiology and cost-effectiveness of service delivery in each setting as well as resource availability. INTERPRETATION: Further reductions in global HIV incidence are possible through improved targeting of international and national HIV resources. FUNDING: World Bank and Australian NHMRC.
背景:为了在 2030 年前实现艾滋病终结目标,艾滋病毒资源的分配需要具有成本效益。我们利用 Optima HIV 模型来评估全球艾滋病毒资源如何重新定位,以取得最大的流行病学效果,以及到 2030 年可以避免多少新增感染。
方法:我们收集了 2000 年 1 月 1 日至 2015 年 12 月 31 日期间用于国家建模的标准数据(包括人口、流行病学、行为、规划和支出数据),涵盖了全球 80%的艾滋病毒感染者。这些数据用于 Optima HIV 框架内的亚国家和国家模型的参数化。为了在亚国家、国家、地区和全球各级估计最佳资源分配,我们使用了自适应随机下降优化算法,结合了每个国家的每个方案的流行病模型和成本函数。我们使用国际艾滋病毒资金保持不变分配给每个国家,以及在国家之间重新分配这些资金,对最佳资源分配进行了分析。
结果:如果各国在 2016 年至 2030 年期间最优地分配艾滋病毒资源,我们估计可以避免另外 740 万(不确定范围为 390 万至 1400 万)新感染,这代表发病率降低 26%(不确定范围为 13%至 50%)。在国家之间重新分配国际资金,还可以避免另外 190 万感染,这代表总体发病率降低 33%(不确定范围为 20%至 58%)。要使 2010 年的艾滋病毒发病率降低 90%,我们估计在 2030 年前,目前每年资金的投入需要增加两倍以上。最优资源重新分配的最常见优先事项是扩大在每个环境中处于最大风险的关键人群的治疗和预防方案。在每个环境中,服务提供的流行病学和成本效益以及资源可用性决定了其他艾滋病毒方案的优先次序。
解释:通过改进国际和国家艾滋病毒资源的定位,全球艾滋病毒发病率的进一步降低是可能的。
资金:世界银行和澳大利亚 NHMRC。
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