Collaborative Research: A comprehensive approach to modeling, learning, analysis and control of epidemic processes over time-varying and multi-layer networks

协作研究：时变多层网络上的流行病过程建模、学习、分析和控制的综合方法

基本信息

批准号：
2032258
负责人：
Philip Pare
金额：
$ 20万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2032258&HistoricalAwards=false
关键词：
Collaborative Research comprehensive approach modeling

项目摘要

Numerous natural and engineered systems consist of underlying networked components over which dynamical processes evolve. Examples include the spread of infectious disease processes over human contact and international travel networks, the propagation of peak traffic phenomenon over the transportation infrastructure, the spread of viruses or worms over computer networks, and sharing and re-sharing of posted articles, tweets, or rumors over social media platforms. Engineered systems are increasingly interconnected over various levels of both local and large-scale networks. Developing a stronger understanding at fundamental and analytical levels of how viral processes evolve across different network structures, the rates at which they spread, how the occurrence of multiple viral types and multiple network layers affect the spread process dynamics, and how these processes can be suppressed and/or mitigated by employing deliberate control policies will greatly impact the health, safety and security of a vast variety of systems around the globe. The spread of COVID-19 has clearly had broad implications for the health of people on all six inhabited continents as well as the world's economy. The research proposed herein will substantially enhance our understanding of epidemics such as COVID-19 and lead to general policy guidelines that will help limit the loss of human life and reduce the economic impacts of the virus. The methods to be developed in this project will be beneficial for battling subsequent epidemic outbreaks, a second wave of COVID-19, and on a broader scale general viral process. Throughout this project the PIs will build on their past experiences to make every effort towards recruiting and mentoring students from under-represented groups, and will establish outreach efforts by including undergraduate and local high school student researchers.Although the dynamics of epidemic processes over networks have been extensively studied for the past 10-15 years, past work has been focused largely on SIS and SIR processes spreading over static networks. In the proposed project, our focus will be on modeling, analysis and control of dynamic epidemic processes over large and possibly time-varying networks, comprised of multiple layers at multiple scales. We will specifically consider data-informed modeling and analysis of SAIRS (susceptible-asymptomatic-infected-recovered-susceptible) processes over time-varying networks; this work will include stability and equilibria analysis of the nonlinear dynamics of networked epidemic process models, network structure identification, estimation of parameters and structure from imperfect and non-random data, and development of realizable control strategies from the agent level to societal levels. The research proposed will draw on and contribute to wide-ranging foundational results in mathematical modeling and analysis of infectious diseases, time-varying nonlinear and linear analysis methods, optimization and control-theoretic policy formulation, network inference and analysis, sequential sampling strategies with stochastic sample constraints, and mean-field games over networks.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.

许多天然和工程系统包括基本的网络组件，在这些组件上发展了动态过程。例子包括传染病过程在人类接触和国际旅行网络上的传播，高峰交通现象在运输基础设施上的传播，病毒或蠕虫在计算机网络上的传播以及分享和重新分享发布的文章，推文，推文或谣言对社交媒体平台。工程系统越来越多地在各个级别的本地和大规模网络上互连。在基本和分析水平上，对病毒过程如何在不同的网络结构中发展，它们传播的速度，多种病毒类型和多种网络层的发生如何影响传播过程动态以及如何通过采用刻意的蓄意控制政策来抑制和/或减轻这些过程将极大地影响全球范围内的健康和安全性，对这些过程的影响会极大地影响和/或减轻这些过程。 Covid-19的传播显然对所有六个居民大陆以及世界经济的人的健康具有广泛的影响。本文提出的研究将大大增强我们对Covid-19等流行病的理解，并导致一般政策指南，这将有助于限制人类生命的丧失并减少病毒的经济影响。该项目中要开发的方法将有助于与随后的流行病爆发，第二波Covid-19和更广泛的一般病毒过程。 Throughout this project the PIs will build on their past experiences to make every effort towards recruiting and mentoring students from under-represented groups, and will establish outreach efforts by including undergraduate and local high school student researchers.Although the dynamics of epidemic processes over networks have been extensively studied for the past 10-15 years, past work has been focused largely on SIS and SIR processes spreading over static networks. 在拟议的项目中，我们的重点将放在大型且可能是随时间变化的网络上对动态流行过程的建模，分析和控制，该过程由多个尺度上的多层组成。我们将特别考虑在随着时间变化的网络上的SAIR（易感性感染反射感染）过程的数据信息建模和分析；这项工作将包括对网络流行过程模型非线性动态的稳定性和平衡分析，网络结构识别，参数估计和从不完美和非随机数据中的参数和结构的估计，以及从代理水平到社会水平的可实现控制策略的发展。提出的研究将借鉴并为广泛的基础成果进行数学建模和分析，对感染性疾病，随时间变化的非线性和线性分析方法，优化和控制理论策略的形成，网络推理和分析，顺序取样，通过对网络进行的均值进行评估，并通过对nsf进行了均值的奖励，并将其序列采样策略进行评估。基金会的智力优点和更广泛的影响评论标准。