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适应干预措施优化疟疾控制:一项基于块聚类随机、序贯多重分配试验的实施研究方案。

Adaptive interventions for optimizing malaria control: an implementation study protocol for a block-cluster randomized, sequential multiple assignment trial.

机构信息

Program in Public Health, University of California, Irvine, CA, USA.

Department of Public Health, Maseno University, Kisumu, Kenya.

出版信息

Trials. 2020 Jul 20;21(1):665. doi: 10.1186/s13063-020-04573-y.

Abstract

BACKGROUND

In the past two decades, the massive scale-up of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) has led to significant reductions in malaria mortality and morbidity. Nonetheless, the malaria burden remains high, and a dozen countries in Africa show a trend of increasing malaria incidence over the past several years. This underscores the need to improve the effectiveness of interventions by optimizing first-line intervention tools and integrating newly approved products into control programs. Because transmission settings and vector ecologies vary from place to place, malaria interventions should be adapted and readapted over time in response to evolving malaria risks. An adaptive approach based on local malaria epidemiology and vector ecology may lead to significant reductions in malaria incidence and transmission risk.

METHODS/DESIGN: This study will use a longitudinal block-cluster sequential multiple assignment randomized trial (SMART) design with longitudinal outcome measures for a period of 3 years to develop an adaptive intervention for malaria control in western Kenya, the first adaptive trial for malaria control. The primary outcome is clinical malaria incidence rate. This will be a two-stage trial with 36 clusters for the initial trial. At the beginning of stage 1, all clusters will be randomized with equal probability to either LLIN, piperonyl butoxide-treated LLIN (PBO Nets), or LLIN + IRS by block randomization based on their respective malaria risks. Intervention effectiveness will be evaluated with 12 months of follow-up monitoring. At the end of the 12-month follow-up, clusters will be assessed for "response" versus "non-response" to PBO Nets or LLIN + IRS based on the change in clinical malaria incidence rate and a pre-defined threshold value of cost-effectiveness set by the Ministry of Health. At the beginning of stage 2, if an intervention was effective in stage 1, then the intervention will be continued. Non-responders to stage 1 PBO Net treatment will be randomized equally to either PBO Nets + LSM (larval source management) or an intervention determined by an enhanced reinforcement learning method. Similarly, non-responders to stage 1 LLIN + IRS treatment will be randomized equally to either LLIN + IRS + LSM or PBO Nets + IRS. There will be an 18-month evaluation follow-up period for stage 2 interventions. We will monitor indoor and outdoor vector abundance using light traps. Clinical malaria will be monitored through active case surveillance. Cost-effectiveness of the interventions will be assessed using Q-learning.

DISCUSSION

This novel adaptive intervention strategy will optimize existing malaria vector control tools while allowing for the integration of new control products and approaches in the future to find the most cost-effective malaria control strategies in different settings. Given the urgent global need for optimization of malaria control tools, this study can have far-reaching implications for malaria control and elimination.

TRIAL REGISTRATION

US National Institutes of Health, study ID NCT04182126 . Registered on 26 November 2019.

摘要

背景

在过去的二十年中,长效杀虫蚊帐(LLINs)和室内滞留喷洒(IRS)的大规模推广导致疟疾死亡率和发病率显著降低。尽管如此,疟疾负担仍然很高,过去几年有十几个非洲国家显示出疟疾发病率上升的趋势。这凸显了需要通过优化一线干预工具和将新批准的产品纳入控制计划来提高干预措施的效果。由于传播环境和媒介生态随地点而变化,因此疟疾干预措施应随着疟疾风险的变化而适应和重新适应。基于当地疟疾流行病学和媒介生态学的适应性方法可能会显著降低疟疾发病率和传播风险。

方法/设计:本研究将采用纵向块-集群序贯多重分配随机试验(SMART)设计,对肯尼亚西部的疟疾控制进行适应性干预,这是第一项针对疟疾控制的适应性试验。主要结局是临床疟疾发病率。这将是一个两阶段试验,初始试验有 36 个集群。在第 1 阶段开始时,所有集群将根据各自的疟疾风险,通过块随机化以相等的概率随机分配到 LLIN、胡椒基丁醚处理的 LLIN(PBO 网)或 LLIN+IRS。干预效果将通过 12 个月的随访监测进行评估。在 12 个月的随访结束时,根据临床疟疾发病率的变化和卫生部设定的成本效益预先确定的阈值,将对集群进行 PBO 网或 LLIN+IRS 的“响应”与“非响应”评估。在第 2 阶段开始时,如果干预措施在第 1 阶段有效,则将继续进行干预。第 1 阶段 PBO 网治疗无反应者将平均随机分配到 PBO 网+LSM(幼虫源管理)或通过增强强化学习方法确定的干预措施。同样,第 1 阶段 LLIN+IRS 治疗无反应者将平均随机分配到 LLIN+IRS+LSM 或 PBO 网+IRS。第 2 阶段干预将有 18 个月的评估随访期。我们将使用诱蚊灯监测室内外媒介丰度。通过主动病例监测监测临床疟疾。使用 Q 学习评估干预措施的成本效益。

讨论

这种新颖的适应性干预策略将优化现有的疟疾媒介控制工具,同时允许未来整合新的控制产品和方法,以在不同环境中找到最具成本效益的疟疾控制策略。鉴于全球对优化疟疾控制工具的迫切需求,这项研究对疟疾控制和消除具有深远意义。

试验注册

美国国立卫生研究院,研究 ID NCT04182126。于 2019 年 11 月 26 日注册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ada4/7372887/6f4de7fb0805/13063_2020_4573_Fig1_HTML.jpg

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