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

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.

Chasing the ghost of infection past: identifying thresholds of change during the COVID-19 infection in Spain

“…To summarise, the patterns of change uncovered by our analyses show that a combination of public awareness, personal hygiene and social distancing can help slow down COVID-19 spread in future outbreaks – such as the one already ongoing in Spain or Israel in September 2020 (see also [29]). These measures should however be accompanied by policies that were not initially implemented but have been successful to contain SARS-CoV-2 and other SARS and MERS outbreaks [51], including wearing face masks [52], digitally-enhanced social distancing measures [53, 54], selective school and university closures [50, 55], active strategies for tracing contacts and selective quarantines [2, 26], as well as performing engineering controls and adapting indoor spaces to enhance ventilation in public buildings [56]. The implementation of these policies should be accompanied by a more effective communication strategy that helps engaging the general public into following measures whose effectiveness can be misperceived due to the long infection-to-detection lags of SARS-CoV-2 infections.…”

Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic

“…The results showed that border blockades and extensive testing had nothing to do with the COVID-19 death rate per million people, but they were significantly conducive to the recovery of the infected, which showed that the government’s prevention and control measures and the speed of the policy had an important impact on the treatment of the infected [ 27 ]. In addition, some scholars have analyzed the impacts of the lockdown policies on the epidemic in China through deep learning models and transmission dynamics models [ 28 , 29 ]. Although there are many related documents, the discontinuity regression model has still not been fully applied in the analysis of the impact of policies on the epidemic.…”

The Fall and Rise of The Contingency Theory of Leadership

“…China as the country of origin of the pandemic for three months was able to handle the pandemic well, it was recorded that at the end of March 2020, China had succeeded in controlling the spread of the pandemic with high-cost lockdown efforts in most of its main cities, especially Wuhan (Zhang et al, 2020) using the style leadership which in the view of some countries can be deemed to violate Human Rights (Kupferschmidt and Cohen, 2020).…”

“…America is starting to see how China is doing very well in dealing with the pandemic and the US federal government is starting to try to change their policy viewpoint by considering the lockdown strategy and indeed, when the initial phase of the pandemic spreads the decision to lockdown was the policy of the central government. Because the best way to prevent the spread is to limit the mobilization of people and keep them away from each other because there was no best treatment at that time and a vaccine was not yet available, and lockdowns are the optimal strategy in dealing with COVID-19 in the early stages of the spread of the pandemic (Zhang et al 2020).…”