Collaborative Research: IHBEM: Data-driven multimodal methods for behavior-based epidemiological modeling

合作研究:IHBEM:基于行为的流行病学建模的数据驱动多模式方法

基本信息

  • 批准号:
    2327710
  • 负责人:
  • 金额:
    $ 20万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-10-01 至 2026-09-30
  • 项目状态:
    未结题

项目摘要

In this project, challenges of behavior-based epidemiological modeling are addressed by developing a unified modeling framework that incorporates new methods for incorporating novel data sources, extended epidemiological models, and evaluations of policy interventions. Capturing human behavior is complex and challenging, as new and unexpected behavioral patterns emerge constantly. This is especially evident during epidemics, which are shaped by a wide variety of behaviors and, in turn, accelerate the speed of behavioral changes. For example, the trajectory of the COVID-19 pandemic was greatly shaped by behaviors such as social distancing, mask-wearing, and vaccination, and these behaviors also emerged and changed dramatically over the course of the pandemic in response to changing disease risks, social norms, government decisions, and incentives. The aim of this project is to develop epidemiological models that can make predictions based on real-world behaviors and capture feedback loops between behaviors, epidemics, and government decisions, thus enabling more effective public health decisions.The aims of this project are accomplished by improving mathematical and machine learning methods for dealing with real-world epidemics and introducing novel approaches to the capture of real-world human behavior and integration of behavioral responses into epidemiological models. First, novel methods are proposed to denoise and derive meaning from multimodal, real-world sensors, such as mobile phones and search engine logs, the data from which is often highly imperfect but which provide unique opportunities to capture human behavior. This allows the capture of complex human behaviors in real time. Second, to bridge epidemiological models and real-world behaviors, agent-based models of disease dynamics are coupled with models of human behavior that capture how individuals choose behaviors based on perceived costs and benefits. Such models are computationally complex and require new methods to calibrate and validate on real data to enable realistic forecasting of epidemics. Finally, to evaluate the complex effects of public health decisions on behavior and epidemic outcomes, new scenario modeling tools and causal inference methods are developed to estimate effects of such decisions in the presence of confounders and interference.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在这个项目中,通过开发一个统一的建模框架来解决基于行为的流行病学建模的挑战,该框架结合了纳入新的数据源、扩展的流行病学模型和政策干预评估的新方法。随着新的和意想不到的行为模式不断涌现,捕捉人类行为是复杂和具有挑战性的。这一点在流行病期间尤其明显,流行病由各种各样的行为塑造,反过来又加快了行为变化的速度。例如,新冠肺炎大流行的轨迹在很大程度上受到社交距离、戴口罩和接种疫苗等行为的影响,这些行为也在大流行过程中出现并发生了巨大变化,以应对不断变化的疾病风险、社会规范、政府决策和激励措施。该项目的目标是开发基于真实世界行为进行预测的流行病学模型,并捕捉行为、流行病和政府决策之间的反馈回路,从而实现更有效的公共卫生决策。该项目的目标是通过改进处理真实世界流行病的数学和机器学习方法来实现,并引入新的方法来捕捉真实世界的人类行为并将行为反应整合到流行病学模型中。首先,提出了新的方法来去除噪声,并从多模式、真实世界的传感器中提取意义,例如手机和搜索引擎日志,这些传感器的数据往往非常不完美,但它们提供了捕捉人类行为的独特机会。这使得能够实时捕获复杂的人类行为。其次,为了将流行病学模型和真实世界的行为联系起来,基于代理的疾病动力学模型与人类行为模型结合在一起,捕捉个人如何根据感知的成本和收益选择行为。这种模型在计算上很复杂,需要新的方法来校准和验证真实数据,以便能够对流行病进行现实的预测。最后,为了评估公共卫生决策对行为和流行病结果的复杂影响,开发了新的情景建模工具和因果推理方法,以在存在混杂因素和干扰的情况下估计此类决策的影响。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Madhav Marathe其他文献

Madhav Marathe的其他文献

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{{ truncateString('Madhav Marathe', 18)}}的其他基金

RAPID: Modeling and Analytics for COVID-19 Outbreak Response in India: A multi-institutional, US-India joint collaborative effort
RAPID:印度 COVID-19 疫情应对的建模和分析:美印多机构联合协作
  • 批准号:
    2142997
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology
探险:合作研究:全球普适计算流行病学
  • 批准号:
    1918656
  • 财政年份:
    2020
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks
RAPID:COVID-19 响应支持:构建综合多尺度网络
  • 批准号:
    2027541
  • 财政年份:
    2020
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
RAPID: Collaborative: Transfer Learning Techniques for Better Response to COVID-19 in the US
RAPID:协作:迁移学习技术以更好地应对美国的 COVID-19
  • 批准号:
    2028004
  • 财政年份:
    2020
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Virtual Organization for Computing Research in Pandemic Preparedness and Resilience
流行病防范和恢复力计算研究虚拟组织
  • 批准号:
    2041952
  • 财政年份:
    2020
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
EAGER: SSDIM: Ensembles of Interdependent Critical Infrastructure Networks
EAGER:SSDIM:相互依赖的关键基础设施网络的集合
  • 批准号:
    1927791
  • 财政年份:
    2019
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: Framework: Software: CINES: A Scalable Cyberinfrastructure for Sustained Innovation in Network Engineering and Science
合作研究:框架:软件:CINES:用于网络工程和科学持续创新的可扩展网络基础设施
  • 批准号:
    1835660
  • 财政年份:
    2018
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: Framework: Software: CINES: A Scalable Cyberinfrastructure for Sustained Innovation in Network Engineering and Science
合作研究:框架:软件:CINES:用于网络工程和科学持续创新的可扩展网络基础设施
  • 批准号:
    1916805
  • 财政年份:
    2018
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
EAGER: SSDIM: Ensembles of Interdependent Critical Infrastructure Networks
EAGER:SSDIM:相互依赖的关键基础设施网络的集合
  • 批准号:
    1745207
  • 财政年份:
    2017
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
NetSE: Large: Collaborative Research: Contagion in large socio-communication networks
NetSE:大型:协作研究:大型社会通信网络中的传染
  • 批准号:
    1011769
  • 财政年份:
    2010
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant

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相似海外基金

Collaborative Research: IHBEM: The fear of here: Integrating place-based travel behavior and detection into novel infectious disease models
合作研究:IHBEM:这里的恐惧:将基于地点的旅行行为和检测整合到新型传染病模型中
  • 批准号:
    2327797
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IHBEM: Three-way coupling of water, behavior, and disease in the dynamics of mosquito-borne disease systems
合作研究:IHBEM:蚊媒疾病系统动力学中水、行为和疾病的三向耦合
  • 批准号:
    2327816
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: IHBEM: Multidisciplinary Analysis of Vaccination Games for Equity (MAVEN)
合作研究:IHBEM:疫苗公平博弈的多学科分析 (MAVEN)
  • 批准号:
    2327791
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: IHBEM: Three-way coupling of water, behavior, and disease in the dynamics of mosquito-borne disease systems
合作研究:IHBEM:蚊媒疾病系统动力学中水、行为和疾病的三向耦合
  • 批准号:
    2327814
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IHBEM: Multidisciplinary Analysis of Vaccination Games for Equity (MAVEN)
合作研究:IHBEM:疫苗公平博弈的多学科分析 (MAVEN)
  • 批准号:
    2327790
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Continuing Grant
Collaborative Research: IHBEM: Three-way coupling of water, behavior, and disease in the dynamics of mosquito-borne disease systems
合作研究:IHBEM:蚊媒疾病系统动力学中水、行为和疾病的三向耦合
  • 批准号:
    2327815
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: IHBEM: Data-driven multimodal methods for behavior-based epidemiological modeling
合作研究:IHBEM:基于行为的流行病学建模的数据驱动多模式方法
  • 批准号:
    2327711
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: IHBEM: Three-way coupling of water, behavior, and disease in the dynamics of mosquito-borne disease systems
合作研究:IHBEM:蚊媒疾病系统动力学中水、行为和疾病的三向耦合
  • 批准号:
    2327817
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
Collaborative Research: IHBEM: The fear of here: Integrating place-based travel behavior and detection into novel infectious disease models
合作研究:IHBEM:这里的恐惧:将基于地点的旅行行为和检测整合到新型传染病模型中
  • 批准号:
    2327798
  • 财政年份:
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  • 资助金额:
    $ 20万
  • 项目类别:
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Collaborative Research: IHBEM: Data-driven multimodal methods for behavior-based epidemiological modeling
合作研究:IHBEM:基于行为的流行病学建模的数据驱动多模式方法
  • 批准号:
    2327709
  • 财政年份:
    2023
  • 资助金额:
    $ 20万
  • 项目类别:
    Standard Grant
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