Roh Michelle E, Tong Yanwei, Heitmann Gabriella Barratt, Ba El-Hadji Konko Ciré, Ndiaye Jean Louis, Fogelson Ari, Milligan Paul, Seck Amadou, Diallo Abdoulaye, Lo Aminata Colle, Baiocchi Michael, Gosling Roly, Bennett Adam, Hsiang Michelle S, Benjamin-Chung Jade
Institute for Global Health Sciences, University of California, San Francisco (UCSF), San Francisco, CA, USA.
Department of Obstetrics and Gynecology, Oregon Health and Science University, Portland, OR, USA.
medRxiv. 2025 Aug 13:2025.08.09.25333369. doi: 10.1101/2025.08.09.25333369.
Numerous trials have evaluated the effectiveness of mass drug administration (MDA) to rapidly reduce malaria transmission, but it is unknown whether estimated effects generalize to other populations eligible for MDA. A recent cluster-randomized trial in Senegal found that MDA reduced malaria incidence by 55% in areas routinely deploying seasonal malaria chemoprevention (SMC). Here, we used transportability models with machine learning to generalize trial effects to 116 non-trial Communes where SMC is standard-of-care. Accounting for differences in weather, vegetation, and population density between trial and non-trial areas, we estimated significant reductions in incidence of 36%-65% in 74 non-trial Communes, with larger reductions in areas with higher precipitation, denser vegetation, and lower temperatures. We found that MDA was not effective in the post-intervention year in non-trial Communes, supporting the notion that MDA effects are short-lived. Our approach offers a scalable framework for generalizing trial findings to target environmentally-mediated infectious disease interventions.
众多试验评估了大规模药物给药（MDA）迅速减少疟疾传播的有效性，但尚不清楚估计的效果是否适用于其他符合MDA条件的人群。最近在塞内加尔进行的一项整群随机试验发现，在常规开展季节性疟疾化学预防（SMC）的地区，MDA使疟疾发病率降低了55%。在此，我们使用机器学习的可迁移性模型将试验效果推广到116个非试验公社，在这些公社中SMC是标准治疗方法。考虑到试验和非试验地区在天气、植被和人口密度方面的差异，我们估计在74个非试验公社中发病率显著降低了36%-65%，在降水量较高、植被较茂密和气温较低的地区降低幅度更大。我们发现，在非试验公社干预后的年份里，MDA并不有效，这支持了MDA效果是短暂的这一观点。我们的方法提供了一个可扩展的框架，用于将试验结果推广到针对环境介导的传染病干预措施。
