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

点击翻译按钮获取中文摘要

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.