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.

描述（由申请人提供）：我们提出了一项为期四年的跨学科研究计划，开发了疾病生态学统计学方法，对环境和生态影响对疾病发病率和传播的影响。许多传染病都涉及多个宿主和向量，每种疾病都有独特的行为，每种行为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的领域。地理空间链接了这些不同的询问领域，我们使用使用空间统计来实现我们的三个特定目的：1）对新兴疾病的局部植物地理学的时空推断。我们提出了量化景观对病毒遗传结构的影响的方法，这是美国东部浣熊狂犬病持续爆发的动力和应用方法论发展，应用和评估的应用。感兴趣的关联涉及地理和遗传瓶颈，以及干预计划在停滞疾病扩散中的影响。 2）将疾病发病率和环境/生态数据连接到不完美测量的系统的空间推理。我们建议开发将空间疾病监视数据与环境景观，向量和水库宿主联系起来的模型。我们专注于以空间不同质量水平的监视数据，例如，诊断和报告的空间上有不同的概率。我们使用有关西非加纳的Buruli溃疡的持续现场数据来激励和说明拟议的方法论。 3）评估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，必须在应用程序的情况下衡量其性能。我们主要关注空间标准：例如，在其中需要收集更多信息以及方法降低检测概率或增加错误警报率的地方。该计划的结果将使研究人员能够衡量景观特征对新兴疾病传播的影响，从而可以更准确地预测传播，适当的反应以及改进的干预策略设计。在本研究中收集的公共卫生数据将用于设计模型，分析技术和软件，这些技术将有助于卫生部，非政府组织和研究人员确定要关注监视的领域，确定适当的健康治疗设施。 ，提高实验室能力，提供教育外展活动，并为医护人员，外展协调员和实验室人员组织培训。 项目叙述 拟议的研究项目将开发用于通过复杂景观在时间和空间中绘制和量化传染病的传播的分析方法。该项目的重点是两种疾病：在美国东部的浣熊（但可传染到人类）中通常发现的狂犬病菌株，以及西非加纳的buruli溃疡（细菌感染导致皮肤深伤）。该研究的主要目的是对环境因素（例如河流和山脉）对疾病在各种景观中传播的影响进行准确的测量，以设计有效的，具有特定地理位置的公共卫生反应。