Spatial Statistics for Disease Ecology

疾病生态学空间统计

• 批准号: 7359119
• 负责人: Lance A Waller
• 金额: $ 33.95万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-01-15 至 2011-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7359119
• 关键词: Address; Africa; Area; Attention; Bacteria; Bacterial Infections; Behavior; Biology; Case Study; Climate; Communicable Diseases; Complex; Computer software; DNA; Data; Data Collection; Depth; Detection; Development; Diagnosis; Disease; Disease Outbreaks; Ecology; Ensure; Environmental Health; Environmental Impact; Environmental Risk Factor; Epidemiology; Evaluation; Genetic; Genetic Drift; Genetic Structures; Ghana; Goals; Government; Guidelines; Health; Health Personnel; Health Professional; Human; Incidence; Infection; Infectious Disease Epidemiology; Interdisciplinary Study; Intervention; Laboratories; Link; Location; Maps; Measurement; Measures; Medical Surveillance; Methodology; Methods; Modeling; Motivation; Mycobacterium ulcerans; Performance; Placement; Population; Prevalence; Prevention strategy; Probability; Public Health; Purpose; Rabies; Raccoons; Range; Rate; Reporting; Research; Research Design; Research Methodology; Research Personnel; Research Project Grants; Rivers; Sampling; Scheme; Series; Skin; Spatial Design; Structure; System; Techniques; Time; Tissue Sample; Training; Ulcer; United States; Vaccinated; Virus; Work; World Health Organization; base; concept; design; improved; infectious disease model; interest; intervention program; model design; outreach; programs; remote sensing; response; statistics; tool; transmission process; vector

DESCRIPTION (provided by applicant): We propose a four-year interdisciplinary research program developing statistical methodology for disease ecology, the study of environmental and ecological impacts on disease incidence and spread. Many infectious diseases involve multiple hosts and vectors, each with unique behaviors, and each impacted by climate and landscape. The proposed research draws from the fields of ecology, conservation biology, environmental health, remote sensing, epidemiology, and global health. Geographic space links these disparate fields of inquiry and we use utilize spatial statistics to achieve our three specific aims: 1) Spatio-temporal inference for the local phylogeography of emerging diseases. We propose methods quantifying landscape impacts on the genetic structure of a virus in the ongoing disease outbreak of raccoon rabies in the eastern United States as motivation and application for methodological development, application and evaluation. Associations of interest involve geographic and genetic bottlenecks, and the impact of intervention programs in stalling disease spread. 2) Spatial inference linking disease incidence and environmental/ecological data from imperfectly measured systems. We propose to develop models linking spatial disease surveillance data to environmental landscapes, vectors, and reservoir hosts. We focus on surveillance data subject to spatially varying levels of quality, e.g., spatially varying probabilities of diagnosis and reporting. We use ongoing field data regarding Buruli ulcer in Ghana, West Africa to motivate and illustrate the proposed methodology. 3) Assess spatial design and performance criteria for the developed techniques. For the proposed techniques to have broad impact, it is essential to measure their performance in the context within which they will be applied. We focus primarily on spatial criteria: e.g., where one needs to collect more information and where methods reduce probability of detection or increase rates of false alarms. The results of this program will allow researchers to measure the impact of landscape features on the spread of an emerging disease allowing more accurate predictions of spread, planning of appropriate responses, and improved design of intervention strategies. The public health data gathered during this study will be used to design models, analytic techniques, and software that will assist ministries of health, non- government organizations, and researchers identify areas in which to focus surveillance, determine placement/enhancement of health treatment facilities, increase laboratory capacity, provide educational outreach activities, and organize trainings for healthcare workers, outreach coordinators, and laboratory personnel.SPATIAL STATISTICS FOR DISEASE ECOLOGY PROJECT NARRATIVE The proposed research project will develop analytic methods for mapping and quantifying the spread of infectious diseases in time and space through a complicated landscape. The project focuses on two diseases: a strain of rabies that is typically found in raccoons (but transmittable to humans) in the eastern United States and Buruli ulcer (a bacterial infection resulting in deep skin wounds) in Ghana, West Africa. The primary goal of the research is to develop accurate measurements of the impact of environmental factors (such as rivers and mountain ranges) on the spread of diseases across a diverse landscape in order to design effective, geographically specific public health responses.

我们提出了一个为期四年的跨学科研究计划，开发疾病生态学的统计方法，研究环境和生态对疾病发病率和传播的影响。许多传染病涉及多种宿主和媒介，每种宿主和媒介都有独特的行为，每种宿主和媒介都受到气候和景观的影响。拟议的研究借鉴了生态学，保护生物学，环境健康，遥感，流行病学和全球健康领域。地理空间将这些不同的调查领域联系起来，我们利用空间统计来实现我们的三个具体目标：1）对新兴疾病的局部地理分布进行时空推断。我们提出的方法量化景观的影响，在美国东部的浣熊狂犬病正在进行的疾病爆发的病毒的遗传结构的方法的开发，应用和评估的动机和应用。利益的关联涉及地理和遗传瓶颈，以及干预计划在阻止疾病传播方面的影响。2)空间推理连接疾病发病率和环境/生态数据从不完善的测量系统。我们建议开发模型，将空间疾病监测数据与环境景观、病媒和水库宿主联系起来。我们专注于受空间变化质量水平影响的监测数据，例如，诊断和报告的空间变化概率。我们使用正在进行的实地数据，在加纳，西非布鲁里溃疡的动机和说明所提出的方法。3)评估所开发技术的空间设计和性能标准。为了使拟议的技术具有广泛的影响，必须在应用这些技术的背景下衡量其性能。我们主要关注空间标准：例如，其中需要收集更多的信息，并且其中方法降低了检测概率或增加了错误警报率。该计划的结果将使研究人员能够衡量景观特征对新出现疾病传播的影响，从而更准确地预测传播，规划适当的应对措施，并改进干预策略的设计。本研究期间收集的公共卫生数据将用于设计模型、分析技术和软件，以帮助卫生部、非政府组织和研究人员确定重点监测的领域，确定健康治疗设施的安置/增强，提高实验室能力，提供教育外展活动，并为医疗保健工作者、外展协调员、疾病生态学的空间统计 项目叙述 拟议的研究项目将开发分析方法，用于绘制和量化传染病在复杂景观中的时间和空间传播。该项目重点关注两种疾病：一种是美国东部浣熊中常见的狂犬病（但可传染给人类），另一种是西非加纳的布鲁里溃疡（一种导致深层皮肤伤口的细菌感染）。该研究的主要目标是准确测量环境因素（如河流和山脉）对疾病在不同景观中传播的影响，以设计有效的、针对特定地理区域的公共卫生对策。