We use a spatial epidemic model with demographic and geographical heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England. Our model emphasizes the role of variability of regional outcomes and heterogeneity across age groups and geographical locations, and provides a framework for assessing the impact of policies targeted towards subpopulations or regions. We define a concept of efficiency for comparative analysis of epidemic control policies and show targeted mitigation policies based on local monitoring to be more efficient than country-level or non-targeted measures. In particular, our results emphasize the importance of shielding vulnerable subpopulations and show that targeted policies based on local monitoring can considerably lower fatality forecasts and, in many cases, prevent the emergence of second waves which may occur under centralized policies.

我们使用具有人口和地理异质性的空间流行病模型来研究英格兰 133 个地区的 COVID-19 的区域动态。我们的模型强调区域结果的可变性以及跨年龄组和地理位置的异质性的作用，并提供了一个评估针对亚人群或区域的政策影响的框架。我们定义了一个效率概念来对流行病控制政策进行比较分析，并表明基于当地监测的针对性缓解政策比国家级或非针对性措施更有效。特别是，我们的结果强调了保护弱势群体的重要性，并表明基于当地监测的有针对性的政策可以大大降低死亡率预测，并且在许多情况下，可以防止在集中政策下可能发生的第二波浪潮的出现。