Spatial Statistics for Disease Ecology

描述（由申请人提供）：我们提出一个为期四年的跨学科研究项目，发展疾病生态学的统计方法，研究环境和生态对疾病发生和传播的影响。许多传染病涉及多个宿主和媒介，每个宿主和媒介都有独特的行为，并受气候和景观的影响。拟开展的研究涉及生态学、保护生物学、环境卫生、遥感、流行病学和全球卫生等领域。地理空间将这些不同的研究领域联系起来，我们利用空间统计来实现我们的三个具体目标：1)对新发疾病的当地系统地理学进行时空推断。我们提出了在美国东部正在进行的浣熊狂犬病疾病爆发中量化景观对病毒遗传结构的影响的方法，作为方法开发、应用和评估的动机和应用。感兴趣的关联包括地理和遗传瓶颈，以及阻止疾病传播的干预计划的影响。2)不完全测量系统中疾病发病率与环境/生态数据之间的空间关联。我们建议开发将空间疾病监测数据与环境景观、媒介和宿主联系起来的模型。我们关注的是质量水平在空间上存在差异的监测数据，例如，诊断和报告的概率在空间上存在差异。我们使用有关西非加纳布鲁里溃疡的持续现场数据来激励和说明所提出的方法。3)评估已开发技术的空间设计和性能标准。为了使拟议的技术产生广泛的影响，必须在应用这些技术的环境中衡量它们的表现。我们主要关注空间标准：例如，需要收集更多信息的地方，以及降低检测概率或增加误报率的方法。该项目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，制定适当的应对计划，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，以协助卫生部、非政府组织和研究人员确定重点监测的领域，确定卫生治疗设施的安置/增强，提高实验室能力，提供教育推广活动，并为卫生保健工作者、推广协调员和实验室人员组织培训。疾病生态学的空间统计

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.