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

描述（由申请人提供）： 全球气候变化的不可避免性导致人们猜测其对传染病风险发生率和分布的影响。这一重要主题以假设驱动的研究形式得到了应有的关注，这些研究旨在解开气候与传染病之间的关系，通常侧重于特定人群或地理区域的一种疾病。然而，没有任何研究系统地研究气候变化对全球传染病负担的影响。虽然全面的方法是雄心勃勃的，但信息学工具、统计方法和计算能力现已开始迅速有效地应对这一挑战。我们建议建立气候与疾病风险之间的全球关系模型，并利用这些模型预测未来气候变化对传染病风险的影响。通过将全球疾病暴发自动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。利用我们以前在基于气候的疾病建模方面的经验以及我们对全球领先的传染病监测系统HealthMap.org的开发，我们将探索一种信息学方法来调查气候与一些传染病之间的预测关系。我们拟议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，并在未来气候变化情景下评估由此产生的模型，以预测气候变化导致的全球疾病风险变化。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。在我们以前为确定疫情监测的非正式来源所做努力的基础上，我们将评估这些来源的可靠性，以分析大规模、长期的流行病学模式。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疾病特异性预测时空模型。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。这些模型与全球人口增长预测相结合，可用于预测因气候变化而面临风险的人口的变化。在包括世卫组织、福格蒂国际、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确定我们的结果，这将为正在进行的国际监测和影响评估工作提供信息。

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.