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

这一探索性和潜在变革性研究的目的是利用复杂网络理论对农村地区流行病的传播进行建模和分析，特别强调研究图形特征和动态，以及它们对流行病传播速度和方向的影响。流行病的社会和经济成本今天可能比以往任何时候都更不容易理解，但仅感染少数动物或人类就可能对国际贸易和政策产生严重影响。此外，很有可能造成更多的牲畜或人员损失，从而造成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州的农村地区。这项研究的首要目标是制定优化的指导方针，管理人员可以使用这些指导方针来建立程序和重新调整资源，以帮助减轻农村地区爆发的影响，由恶意攻击或自然事件所造成。研究小组将展开以下四项研究工作：（1）收集堪萨斯农村的经验数据，并创建底层网络，（2）将底层网络扩展到图族，并研究这些网络的图论度量，以预测它们在流行病期间的行为和动态，（3）建立可在个人电脑上运行的精确和便携式模拟器;（4）制定控制疾病爆发的最佳指导方针。这项研究旨在导致复杂网络理论和分析的科学突破。特别是，将分析网络的家庭，以确定流行病传播的关键结构。新的指标将被提出来定量衡量网络的鲁棒性相对于流行病的传播。此外，还将使用加权和非对称网络生成对感染传播速度的新型分析。这项新的分析应能更准确地预测流行病的传播。这些知识可以被纳入政策/计划，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，社会将受益于更有效的政策，以减少流行病的影响。在所有情况下，人类或动物群体中的疾病流行都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鲁棒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。

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.