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

蚊子的连环杀手：利用地理剖析对乌干达农村幼虫栖息地进行空间定位

基本信息

批准号：
10316216
负责人：
Ross Mathew Boyce
金额：
$ 18.82万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-12-01 至 2023-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10316216
关键词：
15 year old Adopted Adult Africa South of the Sahara Algorithms Animals Anopheles Genus Applications Grants Area Award Behavior Biological Breeding Centers for Disease Control and Prevention (U.S.)Child Clinical Clinical Data Complementarity Determining Regions County Crime Criminology Cross-Sectional Studies Culicidae Data Data Set Detection Employment Entomology Environment Epidemiology Exclusion Genotype Geographic Factor Geography Goals Habitats High-Throughput Nucleotide Sequencing Household Hygiene Individual Infection Information Sciences Insecticide Resistance Insecticides International Interruption Intervention Knowledge Larva Light Link Location London Malaria Maps Measures Mentors Mentorship Methodology Methods Modeling Modification Molecular Molecular Epidemiology North Carolina Outcome Parasitemia Patient Self-Report Plasmodium falciparum Population Positioning Attribute Probability Public Health Recording of previous events Research Research Personnel Residual state Resources Rural Sampling Schools Single Nucleotide Polymorphism Site Source Spatial Distribution Structure Surveys Testing Training Travel Tropical Medicine Uganda Universal Coverage Universities Vectorial capacity analytical tool base burden of illness career cost effective deep sequencing density effectiveness evaluation efficacy evaluation feeding improved indexing innovation malaria transmission novel offender operation prevent programs prospective residence risk stratification spatial epidemiology success tool transmission process vector vector control

项目摘要

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.

项目摘要/摘要矢量控制措施的广泛部署，例如长期杀虫网（LLIN）全球疟疾负担大幅下降。但是，仅这些策略就不足中断传播并维持收益。因此，迫切需要进行矢量控制的创新。幼虫来源管理（LSM）是对潜在繁殖栖息地的修改，以防止未成熟的蚊子经常通过应用幼虫来发展成成年人。但是，LSM是资源密集的，并且因此仅在精选环境中推荐。有效定位和定位的新方法必须开发围绕菌群育种位点，以使LSM在更广泛的环境中可行。地理分析（GP）最初是作为犯罪学的分析工具开发的，使用了链接犯罪的位置缩小搜索区域的可能嫌疑人。 GP已成功地采用了许多生物学问题，但就疟疾而言，它仅应用于单个回顾性数据集。尽管如此，该模型能够根据临床病例的位置有效地识别蚊子育种位点。我的长期职业目标是成为具有应用流行病学专业知识的独立研究者空间分析以促进我们对影响疟疾的地理因素的理解以最有效的方式传输和目标干预措施。但是，要实现我的职业目标和科学目标，我需要其他指导和培训：（i）地理信息科学（GISC），（ii）昆虫学监测和（iii）分子流行病学，尤其是在疟疾控制的背景下。我将借鉴这项培训，并利用我的导师的资源来实现我的科学目标，这是是为了评估贝叶斯GP模型的有效性，以鉴定低的繁殖位点传播，乌干达西部的高地地区。我的中心假设是GP将有助于无需大规模野外操作的蚊帐繁殖地点。我会测试这个通过追求三个特定研究的假设：（1）确定GP的准确性和效率以识别与野外幼虫监测相比，蚊子育种位点；（2）证明了将成年蚊子密度的空间分布添加到GP模型中；（3）评估使用的效果一种新型的高通量测序方法，用于排除进口疟疾病例以提高其准确性 GP模型。鉴于我可用的大量机构资源，我有能力实现这些目标通过北卡罗来纳大学教堂山大学和伦敦卫生学院和热带学院医学，以及包括乔纳森博士在内的国际知名导师和顾问团队朱莉安诺，莎拉·斯泰德（Sarah Staedke）博士和史蒂文·勒·康伯（Steven Le Comber）问题。拟议的研究具有创新性和重要性，因为结果将代表第一个前瞻性使用GP来识别蚊子繁殖地点，并可能使LSM在撒哈拉以南非洲更具成本效益。