Serial Killers to Mosquitos: The Spatial Targeting of Larval habitats in rural Uganda using geographic Profiling

项目概要/摘要 广泛采用病媒控制措施，如长效驱虫蚊帐， 导致全球疟疾负担显著下降。然而，单靠这些战略还不足以 中断传输并维持增益。因此，迫切需要在病媒控制方面进行创新。幼虫来源 管理（LSM）是修改潜在的繁殖栖息地，以防止未成熟的蚊子 发育成成虫，通常是通过使用杀幼虫剂。然而，当地供应链管理是资源密集型的， 因此仅推荐在选定的环境中使用。有效定位和锁定目标的新方法 必须开发按蚊繁殖地，使最小二乘方法在更广泛的环境中可行。地理 剖析（GP）最初是作为犯罪学中的一种分析工具而开发的，它利用了相关犯罪的位置 缩小嫌疑人的搜索范围GP已成功应用于许多生物学领域， 问题，但在疟疾的情况下，它只适用于一个单一的回顾性数据集。然而，尽管如此， 该模型能根据临床病例的位置有效地识别蚊子滋生地点。我 长期的职业目标是成为一名独立的调查员，拥有应用流行病学的专业知识， 进行空间分析，以增进我们对影响疟疾的地理因素的了解 以最有效的方式进行传播和有针对性的干预。为了实现我的职业目标， 科学目标，我需要额外的指导和培训：（i）地理信息科学（GISc），（ii） 昆虫学监测，和（iii）分子流行病学，所有这些都是在疟疾控制的背景下。我 我将利用这种培训，并利用我的导师的资源来实现我的科学目标， 是评估贝叶斯GP模型的有效性，以确定按蚊繁殖地点在低 乌干达西部高原地区的传播。我的中心假设是，GP将促进 无需大规模现场操作即可确定按蚊繁殖地点。我来测试一下 通过追求三个具体的研究目标：（1）建立GP识别的准确性和效率 按蚊繁殖地与基于现场的幼虫监测的比较;（2）证明 在GP模型中加入成蚊密度的空间分布;（3）评估使用 一种新的、高通量的测序方法，排除输入性疟疾病例，以提高 GP模型。鉴于我拥有大量的机构资源，我完全有能力实现这些目标 通过查佩尔山的北卡罗来纳州大学和伦敦卫生和热带学校 医学，沿着着包括乔纳森博士在内的国际知名导师和顾问团队 Juliano，Sarah Staedke博士和Steven Le精梳机博士，他们率先使用GP进行流行病学研究。 问题该研究具有创新性和重要意义，因为其结果将代表第一个前景。 该研究还表明，使用GP来确定蚊子滋生地，可以使LSM在撒哈拉以南非洲更具成本效益。

PROJECT SUMMARY/ABSTRACT The widespread deployment of vector control measures, such as long-lasting insecticidal nets (LLIN), has resulted in significant declines in the global burden of malaria. Yet, these strategies alone are insufficient to interrupt transmission and sustain gains. Thus, innovations in vector control are urgently needed. Larval source management (LSM) is the modification of potential breeding habitats to prevent immature mosquitos from developing into adults, often through the application of larvicides. LSM is, however, resource intensive and thereby only recommended in select environments. New methods of efficiently locating and targeting Anopheles breeding sites must be developed to make LSM feasible in a wider variety of settings. Geographic profiling (GP) was originally developed as an analytical tool in criminology, using the locations of linked crimes to narrow the search area for likely suspects. GP has been successfully adopted to a number of biological problems, but in the case of malaria, it has only been applied to a single retrospective data set. Nevertheless, the model was able to efficiently identify mosquito breeding sites based on the location of clinical cases. My long-term career goal is to become an independent investigator with expertise in applied epidemiology and spatial analysis in order to advance our understanding of the geographic factors that influence malaria transmission and target interventions in the most effective manner. However, to achieve my career goals and scientific objectives, I need additional mentorship and training in: (i) geographic information science (GISc), (ii) entomological surveillance, and (iii) molecular epidemiology, all specifically in the context of malaria control. I will draw upon this training and leverage the resources of my mentors to achieve my scientific objective, which is to evaluate the effectiveness of a Bayesian GP model to identify Anopheles breeding sites in a low transmission, highland area of Western Uganda. My central hypothesis is that GP will facilitate the identification of Anopheles breeding sites without the need for large scale field operations. I will test this hypothesis by pursuing three specific research aims: (1) establish the accuracy and efficiency of GP to identify Anopheles breeding sites in comparison to field-based larval surveillance; (2) demonstrate the benefit of adding the spatial distribution of adult mosquito densities to the GP model; and (3) evaluate the effect of using a novel, high-throughput sequencing method to exclude imported malaria cases to improve the accuracy of the GP model. I am well positioned to achieve these aims given the vast institutional resources available to me through the University of North Carolina at Chapel Hill and the London School of Hygiene and Tropical Medicine, along with an internationally-renowned team of mentors and advisors, including Dr. Jonathan Juliano, Dr. Sarah Staedke, and Dr. Steven Le Comber, who pioneered the use of GP to epidemiological problems. The proposed research is innovative and significant, as the results will represent the first prospective use of GP to identify mosquito breeding sites, and could make LSM more cost-effective in sub-Saharan Africa.