多层网络描述城市系统中的交互：西班牙五座城市的数字孪生
Multilayer networks describing interactions in urban systems: a digital twin of five cities in Spain
AI总结：
本文提出了一种构建多层网络的方法，用于创建西班牙五座城市的数字孪生，以研究不同流行病场景下的干预策略比较。
摘要：
描述谁与谁互动的网络对传染病传播的数学模型至关重要。在新兴疾病背景下，这些网络有潜力编码多种交互情境，其中非药物干预措施可以被引入，从而在各种情境中对不同干预策略进行恰当比较。因此，一个描述人口中交互并详细说明不同层中情境的多层网络构成了此类描述的适当工具。然而，在大型系统如城市中，特别是在数据保护政策加强的框架下，这些方法变得具有挑战性。在本工作中，我们提出了一种构建此类多层网络的方法，并提供了五个西班牙城市对应的网络。我们的工作利用多种可用数据集的信息来创建现实的数字孪生，描述居民及其互动，并提供了一个探索不同流行病场景的平台，以在现实环境中更好地准备。
英文摘要：
Networks specifying who interacts with whom are crucial for mathematical models of epidemic spreading. In the context of emerging diseases, these networks have the potential to encode multiple interaction contexts where non-pharmaceutical interventions can be introduced, allowing for proper comparisons among different intervention strategies in a plethora of contexts. Consequently, a multilayer network describing interactions in a population and detailing their contexts in different layers constitutes an appropriate tool for such descriptions. These approaches however become challenging in large-scale systems such as cities, particularly in a framework where data protection policies are enhanced. In this work, we present a methodology to build such multilayer networks and make those corresponding to five Spanish cities available. Our work uses approaches informed by multiple available datasets to create realistic digital twins of the citizens and their interactions and provides a playground to explore different pandemic scenario in realistic settings for better preparedness.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
