Rodríguez Jorge P, Aleta Alberto, Moreno Yamir
Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC), CSIC-UIB, Palma de Mallorca, Spain.
CA UNED Illes Balears, Palma, Spain.
Sci Data. 2025 Jul 15;12(1):1227. doi: 10.1038/s41597-025-05551-2.
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.
指定谁与谁互动的网络对于流行病传播的数学模型至关重要。在新出现疾病的背景下，这些网络有可能编码多种互动情境，在这些情境中可以引入非药物干预措施，从而能够在众多情境中对不同的干预策略进行适当比较。因此，一个描述人群中互动并在不同层详细说明其情境的多层网络构成了进行此类描述的合适工具。然而，在城市等大规模系统中，尤其是在加强数据保护政策的框架下，这些方法变得具有挑战性。在这项工作中，我们提出了一种构建此类多层网络的方法，并提供了与五个西班牙城市相对应的网络。我们的工作采用了多个可用数据集提供的方法，以创建公民及其互动的逼真数字孪生模型，并提供了一个平台，以便在现实环境中探索不同的大流行情景，从而更好地做好准备。
