Evaluating the effect of city lock-down on controlling COVID-19 propagation through deep learning and network science models. (December 2020)

• Record Type: Journal Article
• Authors: Zhang, Xiaoqi; Ji, Zheng; Zheng, Yanqiao; Ye, Xinyue; Li, Dong
• Is Part Of: Cities. Volume 107(2020)
• Publication Date: 2020-12
• Subjects: COVID-19 -- City lock-down -- Counterfactual analysis -- Deep learning -- Network science -- China; City planning -- Periodicals; Urban policy -- Periodicals; 711.4
• DOI: 10.1016/j.cities.2020.102869
• Languages: English
• ISSNs: 0264-2751

Abstract

Abstract: The special epistemic characteristics of the COVID-19, such as the long incubation period and the infection through asymptomatic cases, put severe challenge to the containment of its outbreak. By the end of March 2020, China has successfully controlled the within- spreading of COVID-19 at a high cost of locking down most of its major cities, including the epicenter, Wuhan. Since the low accuracy of outbreak data before the mid of Feb. 2020 forms a major technical concern on those studies based on statistic inference from the early outbreak. We apply the supervised learning techniques to identify and train NP-Net-SIR model which turns out robust under poor data quality condition. By the trained model parameters, we analyze the connection between population flow and the cross-regional infection connection strength, based on which a set of counterfactual analysis is carried out to study the necessity of lock-down and substitutability between lock-down and the other containment measures. Our findings support the existence of non-lock-down-typed measures that can reach the same containment consequence as the lock-down, and provide useful guideline for the design of a more flexible containment strategy. Highlights: It comprehensively evaluates the effectiveness of the city lock-down for COVID-19. A non-parametric network-based SIR model (NP-Net-SIR) is proposed to study the cross-regional outbreak of COVID-19. A set of counter-factual analysis is carried out to study the necessity of lock-down and substitutability between lock-down and the other containment measures. Our findings provide useful guideline for the design of a more flexible containment strategy.