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
基本信息
- 批准号:8724557
- 负责人:
- 金额:$ 41.7万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AddressAtlasesAttentionBiologicalClimateCommunicable DiseasesComplexCoupledCouplingDataData ReportingData SetData SourcesDatabasesDetectionDevelopmentDiseaseDisease OutbreaksDisease modelEpidemiologyEventFutureGeographic LocationsGoalsHealthIncidenceInfectious Disease EpidemiologyInformaticsInformation SystemsInternationalInternetMethodologyModelingOutputPatternPoliciesPopulationPopulation GrowthPopulations at RiskProjections and PredictionsRed CrossResearchSourceStatistical ComputingStatistical MethodsSurveillance MethodsSystemTechnologyUnited States National Aeronautics and Space AdministrationUnited States National Institutes of HealthValidity and ReliabilityWorld Health Organizationbaseburden of illnessclimate changedata miningdesigndisorder riskexperienceinterestinternational centernew technologyspatiotemporalsurveillance datatooltrendweb based interface
项目摘要
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):
全球气候变化的必然性导致了人们对其对传染病风险发生和分布的影响的猜测。这一重要主题以假说驱动的研究形式得到了应有的关注,该研究旨在理清气候和传染病之间的关系,通常侧重于特定人口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。虽然综合办法是雄心勃勃的,但现在已有信息学工具、统计方法和计算能力开始迅速和有效地应对这一挑战。我们建议对气候和疾病风险之间的全球关系进行建模,并使用这些模型来预测气候变化对传染病风险的未来影响。通过将自动化的全球疾病暴发检测的新技术与现有的气候数据相结合,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,以及我们开发的HealthMap.org,这是一个领先的全球传染病监测系统,我们将探索一种信息学方法来调查气候和一些传染病之间的预测关系。我们建议的研究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结果模型,以预测由于气候变化而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。在我们以前为疫情监测寻找非正式来源的努力的基础上,我们将评估这些来源用于大规模长期流行病学模式分析的可靠性。其次,使用这些经过验证的数据,我们将识别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我们在各种气候变化情景下的模型。与全球人口增长预测相结合,这些模型可用于预测由于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国家航空航天局合作伙伴在内的我们的顾问小组的指导下,我们计划以与政策相关的方式制定我们的结果,以便为正在进行的国际监测和影响评估工作提供信息。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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John S. Brownstein其他文献
Erratum to: Digital Drug Safety Surveillance: Monitoring Pharmaceutical Products in Twitter
- DOI:
10.1007/s40264-014-0172-9 - 发表时间:
2014-05-24 - 期刊:
- 影响因子:3.800
- 作者:
Clark C. Freifeld;John S. Brownstein;Christopher M. Menone;Wenjie Bao;Ross Filice;Taha Kass-Hout;Nabarun Dasgupta - 通讯作者:
Nabarun Dasgupta
Geoinference of author affiliations using NLP-based text classification
- DOI:
10.1038/s41598-024-73318-7 - 发表时间:
2024-10-16 - 期刊:
- 影响因子:3.900
- 作者:
Brian Lee;John S. Brownstein;Isaac S. Kohane - 通讯作者:
Isaac S. Kohane
A Pharmacoepidemiological Network Model for Drug Safety Surveillance
- DOI:
10.2165/11596610-000000000-00000 - 发表时间:
2012-05-01 - 期刊:
- 影响因子:3.800
- 作者:
Ben Y. Reis;Karen L. Olson;Lu Tian;Rhonda L. Bohn;John S. Brownstein;Peter J. Park;Mark J. Cziraky;Marcus D. Wilson;Kenneth D. Mandl - 通讯作者:
Kenneth D. Mandl
Vaccine effectiveness against emerging COVID-19 variants using digital health data
使用数字健康数据评估疫苗针对新出现的 COVID-19 变种的有效性
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
T. Varrelman;B. Rader;C. Remmel;Gaurav Tuli;Aimee Han;C. Astley;John S. Brownstein - 通讯作者:
John S. Brownstein
The overlapping global distribution of dengue, chikungunya, Zika and yellow fever
登革热、基孔肯雅热、寨卡病毒和黄热病在全球范围内的重叠分布
- DOI:
10.1038/s41467-025-58609-5 - 发表时间:
2025-04-10 - 期刊:
- 影响因子:15.700
- 作者:
Ahyoung Lim;Freya M. Shearer;Kara Sewalk;David M. Pigott;Joseph Clarke;Azhar Ghouse;Ciara Judge;Hyolim Kang;Jane P. Messina;Moritz U. G. Kraemer;Katy A. M. Gaythorpe;William M. de Souza;Elaine O. Nsoesie;Michael Celone;Nuno Faria;Sadie J. Ryan;Ingrid B. Rabe;Diana P. Rojas;Simon I. Hay;John S. Brownstein;Nick Golding;Oliver J. Brady - 通讯作者:
Oliver J. Brady
John S. Brownstein的其他文献
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{{ truncateString('John S. Brownstein', 18)}}的其他基金
An Approach for Estimating Foodborne Illnesses and Assessing Risk Factors
估计食源性疾病和评估风险因素的方法
- 批准号:
9266489 - 财政年份:2015
- 资助金额:
$ 41.7万 - 项目类别:
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:
8111824 - 财政年份:2010
- 资助金额:
$ 41.7万 - 项目类别:
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:
8318255 - 财政年份:2010
- 资助金额:
$ 41.7万 - 项目类别:
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:
7948679 - 财政年份:2010
- 资助金额:
$ 41.7万 - 项目类别:
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 - 财政年份:2010
- 资助金额:
$ 41.7万 - 项目类别:
HealthMap: Knowledge Management for Emerging Infectious Disease Intelligence
HealthMap:新发传染病情报的知识管理
- 批准号:
8138357 - 财政年份:2009
- 资助金额:
$ 41.7万 - 项目类别:
HealthMap: Knowledge Management for Emerging Infectious Disease Intelligence
HealthMap:新发传染病情报的知识管理
- 批准号:
8325815 - 财政年份:2009
- 资助金额:
$ 41.7万 - 项目类别:
HealthMap: Knowledge Management for Emerging Infectious Disease Intelligence
HealthMap:新发传染病情报的知识管理
- 批准号:
7921043 - 财政年份:2009
- 资助金额:
$ 41.7万 - 项目类别:
HealthMap: Knowledge Management for Emerging Infectious Disease Intelligence
HealthMap:新发传染病情报的知识管理
- 批准号:
7928674 - 财政年份:2009
- 资助金额:
$ 41.7万 - 项目类别:
HealthMap: Knowledge Management for Emerging Infectious Disease Intelligence
HealthMap:新发传染病情报的知识管理
- 批准号:
7692401 - 财政年份:2009
- 资助金额:
$ 41.7万 - 项目类别:
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