Can mental health services break the cycle perpetuating HIV hotspots in sub-Saharan Africa?

摘要/摘要 撒哈拉以南非洲(SSA)的艾滋病毒发病率正在下降，但一些地区没有走上实现 联合国在可持续发展中设定的年新增感染率为0.1%的“疫情控制”目标 发展目标。常见的精神障碍(CMD)，如抑郁症和焦虑症 在艾滋病毒携带者中流行，干扰终身坚持治疗，并与 危险的性行为。因此，SSA的卫生当局正在认识到CMD的重要性 作为艾滋病毒预防的一个组成部分的筛查和治疗，但尚未确定将这些重点放在哪里 服务。最有可能达不到疫情控制目标的地区被称为艾滋病毒热点。我们 假设存在不同类型的热点：一些是由危险行为驱动的，一些是随机产生的 Chance，以及一些在过去出现并陷入正反馈循环的事件 发病率和流行率。CMD筛查和治疗的最佳作用可能因热点类型而异。 我们建议使用数学建模来预测热点的发生，确定如何分类 按类型分类，并估计针对每种艾滋病毒热点类型的CMD筛查和治疗的最佳作用。下一首, 我们将与两个SSA国家-肯尼亚和赞比亚-的专家合作，制定一个投资案例 将CMD筛查和治疗纳入最佳艾滋病毒应对措施，无论是在全国范围内还是重点放在 艾滋病毒热点地区。最后，我们将使用信息价值方法来确定寻找 根据针对每个热点的目标和定制艾滋病毒反应的好处，对热点进行分类是合理的 热点。我们希望我们的项目能指导卫生部和实施者扩大CMD的规模 在SSA进行治疗的同时，还扩大了对艾滋病毒流行的基本了解，假设 由于基本的数学属性，如分形图和混沌，包含热点。这些假设 在地理空间艾滋病毒数据和方法激增的同时，20年来没有重新进行过审查。我们预计 我们的项目将通过扩大热点定位和通过 促进将慢性萎缩性脑病护理纳入艾滋病毒应对措施。

ABSTRACT/SUMMARY HIV incidence is declining in sub-Saharan Africa (SSA), but some areas are not on track to achieve the “epidemic control” target of <0.1% annual rate of new infections set by the United Nations in the Sustainable Development Goals. Common mental disorders (CMD) such as depression and anxiety are extremely prevalent among people living with HIV, interfere with lifelong adherence to treatment, and are associated with risky sexual behaviors. Accordingly, health authorities in SSA are recognizing the importance of CMD screening and treatment as a component of HIV prevention, but have not yet determined where to focus these services. The areas at greatest risk of missing the epidemic control target are known as HIV hotspots. We hypothesize that there are different types of hotspots: some driven by risky behaviors, some arising by random chance, and some that emerged in the past and have become trapped in a positive feedback loop between incidence and prevalence. The optimal role of CMD screening and treatment may differ by hotspot type. We propose to use mathematical modeling to predict the occurrence of hotspots, determine how to classify them by type, and estimate the optimal role of CMD screening and treatment for each HIV hotspot type. Next, we will work with experts in two SSA countries – Kenya and Zambia – to develop an investment case for incorporating CMD screening and treatment into an optimal HIV response, either nationally or with a focus on HIV hotspots. Finally, we will use a value-of-information approach to determine whether the costs of finding and classifying hotspots are justified by the benefits of targeting and customizing the HIV response to each hotspot. We expect our project to guide Ministries of Health and implementers about scale-up of CMD treatment in SSA while also expanding basic understanding of HIV epidemics, which were hypothesized to contain hotspots due to fundamental mathematical properties such as fractals and chaos. These hypotheses have not been revisited in two decades, while geospatial HIV data and methods have proliferated. We expect that our project will enable more effective HIV prevention in SSA by expanding hotspot targeting and by facilitating the integration of CMD care into the HIV response.