School of Data Science, City University of Hong Kong, Hong Kong 999077, China.
The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100000, China.
Chaos. 2021 Feb;31(2):021101. doi: 10.1063/5.0040560.
The emergence of coronavirus disease 2019 (COVID-19) has infected more than 62 million people worldwide. Control responses varied across countries with different outcomes in terms of epidemic size and social disruption. This study presents an age-specific susceptible-exposed-infected-recovery-death model that considers the unique characteristics of COVID-19 to examine the effectiveness of various non-pharmaceutical interventions (NPIs) in New York City (NYC). Numerical experiments from our model show that the control policies implemented in NYC reduced the number of infections by 72% [interquartile range (IQR) 53-95] and the number of deceased cases by 76% (IQR 58-96) by the end of 2020. Among all the NPIs, social distancing for the entire population and protection for the elderly in public facilities is the most effective control measure in reducing severe infections and deceased cases. School closure policy may not work as effectively as one might expect in terms of reducing the number of deceased cases. Our simulation results provide novel insights into the city-specific implementation of NPIs with minimal social disruption considering the locations and population characteristics.
2019 年冠状病毒病（COVID-19）的出现已在全球范围内感染了超过 6200 万人。各国的控制措施各不相同，在疫情规模和社会混乱方面的结果也有所不同。本研究提出了一个特定年龄的易感-暴露-感染-恢复-死亡模型，该模型考虑了 COVID-19 的独特特征，以检查纽约市（NYC）各种非药物干预（NPI）的有效性。我们模型的数值实验表明，NYC 实施的控制政策将感染人数减少了 72%（IQR 53-95），并将死亡人数减少了 76%（IQR 58-96）到 2020 年底。在所有的 NPI 中，对所有人实行社会隔离和在公共场所对老年人进行保护是减少严重感染和死亡人数的最有效控制措施。学校关闭政策在减少死亡人数方面的效果可能不如预期的那么有效。我们的模拟结果提供了新的见解，即在考虑到地理位置和人口特征的情况下，以最小的社会干扰实现了针对特定城市的 NPI 实施。
