论文标题
数字城市和COVID-19的传播：表征西班牙五个城市的非药物干预措施的影响
Digital cities and the spread of COVID-19: characterizing the impact of non-pharmaceutical interventions in five cities in Spain
论文作者
论文摘要
数学建模是实现Covid-19的接近实时准确预测至关重要的。同样，非药物干预措施的设计在包含差异的策略的应用中起着关键作用。但是，对于定量方法来表征每种干预措施的影响，这可能会大大变化，这取决于正在考虑的人群的文化，地区和特定情况，这做出了较少的工作。在这项工作中，我们开发了一个高分辨率，基于数据驱动的代理模型，即在五个西班牙城市的人口中，Covid-19的传播模型。这些人群合成了多个数据源，这些数据源总结了导致潜在联系的主要交互环境。我们模拟了Covid-19在这些城市中的传播，并研究了几种非药物干预措施的效果。我们通过案例研究来说明我们的方法的潜力，并通过被抑制的情况得出了最相关的干预措施的影响。我们的框架构成了模拟不同干预方案进行决策的第一个工具。
Mathematical modeling has been fundamental to achieving near real-time accurate forecasts of the spread of COVID-19. Similarly, the design of non-pharmaceutical interventions has played a key role in the application of policies to contain the spread. However, there is less work done regarding quantitative approaches to characterize the impact of each intervention, which can greatly vary depending on the culture, region, and specific circumstances of the population under consideration. In this work, we develop a high-resolution, data-driven agent-based model of the spread of COVID-19 among the population in five Spanish cities. These populations synthesize multiple data sources that summarize the main interaction environments leading to potential contacts. We simulate the spreading of COVID-19 in these cities and study the effect of several non-pharmaceutical interventions. We illustrate the potential of our approach through a case study and derive the impact of the most relevant interventions through scenarios where they are suppressed. Our framework constitutes a first tool to simulate different intervention scenarios for decision-making.
