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

项目摘要/摘要 病媒控制措施的广泛部署，如长效杀虫网，已经 导致全球疟疾负担大幅下降。然而，仅靠这些战略还不足以 中断传输并维持涨幅。因此，迫切需要在病媒控制方面进行创新。幼虫来源 管理(LSM)是修改潜在的繁殖生境，以防止未成熟的蚊子 成虫发育成成虫的，通常通过使用杀幼虫剂。然而，LSM是资源密集型的， 因此仅在选定的环境中推荐使用。高效定位和定位的新方法 必须开发按蚊繁殖地，使LSM在更广泛的环境中可行。地理 侧写(GP)最初是作为犯罪学中的一种分析工具开发的，使用的是关联犯罪的地点 缩小搜索范围，寻找可能的嫌疑犯。GP已被成功地应用于许多生物 但就疟疾而言，它只适用于单一的回溯性数据集。不过， 该模型能够根据临床病例的位置有效地识别蚊子滋生地点。我的 长期的职业目标是成为一名独立的调查员，具有应用流行病学和 空间分析，以促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目标干预。然而，为了实现我的职业目标和 为了实现科学目标，我需要在以下方面提供更多的指导和培训：(I)地理信息科学(GISC)，(Ii) 昆虫学监测，以及(3)分子流行病学，所有这些都是在疟疾控制的背景下进行的。我 我将利用这一培训并利用我导师的资源来实现我的科学目标，这 是评估贝叶斯GP模型识别按蚊繁殖地的有效性 传播，乌干达西部高地地区。我的中心假设是，GP将促进 无需大规模野外作业即可确定按蚊繁殖点。我要测试一下这个 通过追求三个具体的研究目的提出假设：(1)建立GP识别的准确性和效率 按蚊繁殖点与现场幼虫监测的比较；(2)证明了 将成虫密度的空间分布添加到GP模型中；以及(3)评估使用 一种新的高通量测序方法排除输入性疟疾病例以提高准确性 GP模型。鉴于我所拥有的大量机构资源，我完全有能力实现这些目标 通过北卡罗来纳大学教堂山分校和伦敦卫生与热带学院 医学，以及国际知名的导师和顾问团队，包括乔纳森博士 Juliano，Sarah Staedke博士和Steven Le Comber博士，他开创了将GP用于流行病学的先河 有问题。这项拟议的研究具有创新性和重大意义，因为其结果将代表第一个前景 利用GP来确定蚊子滋生地点，并可使撒哈拉以南非洲的LSM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.