SGER: Exploratory research on complex network approach to epidemic spreading in rural regions

SGER：农村地区流行病传播复杂网络方法的探索性研究

• 批准号: 0841112
• 负责人: Caterina Scoglio
• 金额: $ 5万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0841112&HistoricalAwards=false
• 关键词: SGER; Exploratory; research; complex; network

The objective of this proposed exploratory and potentially transformative research is to use complex network theory to model and analyze the spread of epidemics in rural regions, with special emphasis on the study of graph characteristics and dynamics, and their impact on the speed and direction of the epidemic. The social and economic costs of epidemics may be less well understood today than ever, yet infection of only a few animals or humans can have serious implications for international trade and policies. Furthermore, the loss of far greater numbers of livestock or people is quite possible, with inherentlyenormous social and economic costs. Moreover, methods for detecting and forecasting epidemics that may have worked in the past in urban or rural overseas regions may not apply to rural regions in the Plains states today.The overarching goal of this research is to develop optimized guidelines that administrators can use to establish procedures and realign resources to help mitigate the effects of an outbreak in rural regions, caused by a malicious attack or by natural occurrences.The research team will start working on the following four research tasks: (1) collect empirical data on rural Kansas and create the underlying networks, (2) extend the underlying network to families of graphs and study the graph-theoretical metrics of those networks to predict their behavior and dynamics during an epidemic, (3) create accurate and portable simulators running on PCs, and (4) develop optimized guidelines to control outbreaks.Intellectual merit. This research is intended to lead to scientific breakthroughs in complex network theory and analysis. In particular, families of networks will be analyzed to determine critical structures for the spread of epidemics. New metrics will be proposed to quantitatively measure the network robustness relative to epidemic spreading. Additionally, a new type of analysis for the rate at which an infection spreads will also be generated using weighted and asymmetric networks. This new analysis should provide greater accuracy in predicting the spread of an epidemic. This knowledge can then be incorporated into policies/plans to curb the spread of an infectious disease.Broader impacts. This research is intended to have a broad impact on society and related research. For example, society will benefit by having more effective policies to decrease the effects of an epidemic. To clarify, in all cases, disease epidemics in human or animal populations may cause extensive social and economic losses. Being able to have an environment that is intrinsically robust to these type of attacks would provide a strong defense against malicious individuals as well as protection against natural events/disasters. Thus, the proposed work will foster interdisciplinary collaboration among rural sociologists and network experts. Finally, the research team will continue to mentor and recruit minorities and females into their research group, which is an interdisciplinary team.

这项提出的探索性和潜在变革性研究的目的是使用复杂的网络理论来对农村地区的流行病进行建模和分析，并特别强调了图形特征和动力学的研究及其对流行病的速度和方向的影响。今天，流行病的社会和经济成本可能比以往任何时候都没有理解，但是只有少数动物或人类的感染才能对国际贸易和政策产生严重影响。此外，由于固有的社会和经济成本，牲畜或人的丧失数量很大。此外，对于过去在城市或农村地区，可能在过去的城市或农村地区进行检测和预测流行病的方法可能不适用于今天的平原州的农村地区。这项研究的超大目标是制定优化的准则，即管理员可以使用该过程来建立程序和重大攻击的攻击，以帮助造成攻击的自然攻击，从而在农村的爆发中造成攻击。四个研究任务：（1）收集有关堪萨斯州农村的经验数据并创建基础网络，（2）将基础网络扩展到图形家族，并研究这些网络的图形理论指标，以预测其在流行病中的行为和动态，（3）在PCS和（4）中创建准确的和便携式的模拟器来控制PCS和（4）最佳指导次数，以促进优化的指南爆发。这项研究旨在导致复杂的网络理论和分析中的科学突破。特别是，将分析网络家族，以确定流行病传播的关键结构。将提出新的指标，以定量测量相对于流行病扩散的网络鲁棒性。此外，还将使用加权和不对称网络生成感染差异的速率的新类型分析。这种新的分析应该在预测流行病的传播方面具有更高的准确性。然后可以将这些知识纳入政策/计划中，以遏制传染病的传播。这项研究旨在对社会和相关研究产生广泛的影响。例如，社会将通过制定更有效的政策来减少流行病的影响，从而受益。为了澄清所有情况下，人类或动物种群中的疾病流行可能会造成广泛的社会和经济损失。能够拥有一种本质上强大的攻击环境，将为恶意人物以及保护自然事件/灾难提供强有力的辩护。因此，拟议的工作将促进农村社会学家和网络专家之间的跨学科合作。最后，研究团队将继续指导和招募少数民族和女性进入其研究小组，这是一个跨学科团队。