A Platform for Modeling the Global Impact of Climate Change on Infectious Disease

模拟气候变化对传染病的全球影响的平台

• 批准号: 8387528
• 负责人: John S. Brownstein
• 金额: $ 0.35万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2016-07-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8387528
• 关键词: Address; Atlases; Attention; Biological; Climate; Communicable Diseases; Complex; Coupled; Coupling; Data; Data Reporting; Data Set; Data Sources; Databases; Detection; Development; Disease; Disease Outbreaks; Disease model; Epidemiology; Event; Future; Geographic Locations; Goals; Health; Incidence; Infectious Disease Epidemiology; Informatics; Information Systems; International; Internet; Methodology; Modeling; Output; Pattern; Policies; Population; Population Growth; Populations at Risk; Projections and Predictions; Red Cross; Research; Source; Statistical Computing; Statistical Methods; Surveillance Methods; System; Technology; United States National Aeronautics and Space Administration; United States National Institutes of Health; Validity and Reliability; World Health Organization; base; burden of illness; climate change; data mining; design; disorder risk; experience; interest; international center; new technology; spatiotemporal; surveillance data; tool; trend; web based interface

DESCRIPTION (provided by applicant): The inevitability of global climate change has led to speculation regarding its effects on the incidence and distribution of infectious disease risk. This important topic has received well-deserved attention in the form of hypothesis-driven research aimed at untangling the relationships between climate and infectious disease, usually focusing on one disease in a specific population or geographic region. However, no study has systematically examined the impact of climate change on the global burden of infectious diseases. Though a comprehensive approach is ambitious, informatics tools, statistical methods and computing capacity now exist to begin to address this challenge quickly and efficiently. We propose to model global relationships between climate and disease risk and to use these models to project future effects of climate change on infectious disease risk. By coupling new technologies for automated, global disease outbreak detection with existing climate data we will comprehensively assess climate-disease relationships on a global scale. Leveraging our previous experience in climate-based disease modeling and our development of HealthMap.org, a leading global infectious disease surveillance system, we will explore an informatics approach to investigating the predictive relationships between climate and a number of infectious diseases. The goals of our proposed research are to broadly characterize the global effects of climate on infectious disease risk and burden and to evaluate the resulting models under future climate change scenarios to project changes in global disease risk due to climate change. First, we plan to validate the use of event-based infectious disease surveillance data sources for tracking spatiotemporal trends in global infectious disease risk and burden. Building on our previous efforts in identifying informal sources for outbreak surveillance, we will assess the reliability of these sources for analyses of large-scale, long-term epidemiological patterns. Second, using this validated data, we will identify the diseases most sensitive to climate and build disease-specific predictive spatiotemporal models of relationships between climate and infectious disease risk and burden. Finally, we will leverage existing climate change forecasts to evaluate our models under various climate change scenarios. Coupled with global population growth projections, these models can be used to predict changes in populations at risk as a consequence of climate change. Guided by our advisory group including partners at the WHO, Fogarty International, Red Cross/Red Crescent Climate Center, and NASA, we plan to frame our results in a policy- relevant manner that will inform ongoing international surveillance and impact assessment efforts.

描述（由申请人提供）： 全球气候变化的不可避免性引发了人们对其对传染病风险的发生和分布的影响的猜测。这一重要主题以假设驱动研究的形式受到了应有的关注，旨在理清气候与传染病之间的关系，通常关注特定人群或地理区域的一种疾病。然而，还没有研究系统地研究气候变化对全球传染病负担的影响。尽管全面的方法是雄心勃勃的，但现在的信息学工具、统计方法和计算能力已经可以开始快速有效地应对这一挑战。我们建议对气候与疾病风险之间的全球关系进行建模，并利用这些模型来预测气候变化对传染病风险的未来影响。通过将自动化全球疾病爆发检测新技术与现有气候数据相结合，我们将在全球范围内全面评估气候与疾病的关系。利用我们之前在基于气候的疾病建模方面的经验以及我们开发的 HealthMap.org（全球领先的传染病监测系统），我们将探索一种信息学方法来调查气候与许多传染病之间的预测关系。我们提出的研究的目标是广泛描述气候对传染病风险和负担的全球影响，并评估未来气候变化情景下的最终模型，以预测气候变化导致的全球疾病风险的变化。首先，我们计划验证基于事件的传染病监测数据源的使用，以跟踪全球传染病风险和负担的时空趋势。基于我们之前确定疫情监测非正式来源的努力，我们将评估这些来源用于分析大规模、长期流行病学模式的可靠性。其次，利用这些经过验证的数据，我们将确定对气候最敏感的疾病，并建立气候与传染病风险和负担之间关系的特定疾病预测时空模型。最后，我们将利用现有的气候变化预测来评估各种气候变化情景下的模型。结合全球人口增长预测，这些模型可用于预测因气候变化而面临风险的人口变化。在包括世界卫生组织、福格蒂国际组织、红十字会/红新月会气候中心和美国宇航局合作伙伴在内的咨询小组的指导下，我们计划以与政策相关的方式制定我们的结果，为正在进行的国际监测和影响评估工作提供信息。