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.

这一提出的探索性和潜在的变革性研究的目标是使用复杂网络理论来建模和分析农村地区的流行病传播，特别强调研究图形特征和动态，以及它们对流行病的速度和方向的影响。今天，人们对流行病的社会和经济代价的了解可能比以往任何时候都少，但仅少数动物或人类的感染就可能对国际贸易和政策产生严重影响。此外，大量牲畜或人口的损失是很可能的，这必然会带来巨大的社会和经济代价。此外，过去可能在海外城市或农村地区有效的检测和预测流行病的方法可能不适用于今天平原各州的农村地区。这项研究的总体目标是制定优化的指导方针，管理人员可以利用这些指导方针建立程序和重新调整资源，以帮助减轻由恶意攻击或自然事件引起的农村地区疫情的影响。研究团队将开始以下四项研究任务：(1)收集堪萨斯州农村地区的经验数据并创建底层网络；(2)将底层网络扩展到图形族，并研究这些网络的图形理论指标，以预测它们在流行病期间的行为和动态；(3)创建在pc上运行的精确便携式模拟器；(4)制定控制疫情的优化指导方针。知识价值。本研究旨在引领复杂网络理论与分析的科学突破。特别是，将分析网络的家庭，以确定流行病传播的关键结构。将提出新的指标来定量测量相对于流行病传播的网络鲁棒性。此外，还将使用加权和不对称网络生成一种新型的感染传播速度分析。这种新的分析在预测流行病的传播方面应该提供更高的准确性。然后可以将这些知识纳入遏制传染病传播的政策/计划中。更广泛的影响。本研究旨在对社会及相关研究产生广泛影响。例如，如果有更有效的政策来减少流行病的影响，社会将受益。澄清一下，在所有情况下，人类或动物群体中的疾病流行可能造成广泛的社会和经济损失。能够拥有一个对这些类型的攻击具有内在健壮性的环境将提供对恶意个人的强大防御以及对自然事件/灾害的保护。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，研究小组将继续指导和招募少数民族和女性进入他们的研究小组，这是一个跨学科的团队。