Search

This paper examines how the economies of old industrial cities in Northeast China respond to the on-going COVID-19 pandemic crisis. The notion of resistance in regional economic resilience is used to explore what impact factors shape the response to the early stage of the crisis. The analysis reveals significant differences in terms of regional economic impact between COVID-19 and the 2008 financial crisis. We find that large cities are more vulnerable and exposed to the pandemic at its early stage, state agency plays a crucial role in shaping the economic resistance in most cities. Going beyond the existing 2008 financial crisis-induced account on regional economic resilience, this paper argues that regional resistance amid COVID-19 is not merely shaped by economic structural factors but also influenced by state agency in terms of economic restriction and restoration measures. The study suggests that the nature of COVID-19 as a particular context of crisis itself needs to be taken seriously when exploring the determinants and outcomes of regional economic resilience. • This paper in investigates regional economic resilience under COVID-19 by studying the resistance of Northeast China in the first quarter of 2020. • This paper finds that secondary industry structure, overall variety, innovation, specialization, openness and state agency are the main factors shaping regional resistance. • Local state agency on containing COVID-19 plays a key role in shaping regional resistance and recovery. • The study suggests that the crisis nature of COVID-19 itself needs to be taken seriously when exploring the determinants of regional economic resilience. [ABSTRACT FROM AUTHOR]

Large-scale and diffuse population flow amplifies the localized COVID-19 outbreak into a widespread pandemic. Network analysis provides a new methodology to uncover the topology and evolution of the population flow and understand its influence on the early dynamics of COVID-19 transmission. In this paper, we simulated 42 transmission scenarios to show the distribution of the COVID-19 outbreak across China. We predicted some original (Guangzhou, Shanghai, Shenzhen) had higher total aggregate population outflows than Wuhan, indicating larger spread scopes and faster growth rates of COVID-19 outbreak. We built an importation risk model to identify some major cities (Dongguan and Foshan) with the highest total importation risk values and the highest standard deviations, indicating the core transmission chains (Dongguan-Shenzhen, Foshan-Guangzhou). We built the population flow networks to analyze their Spatio-temporal characteristics and identify the influential sub-groups and spreaders. By removing different influential spreaders, we identified Guangzhou can most influence the network's topological characteristics, and some major cities' degree centrality was significantly decreased. Our findings quantified the effectiveness of travel restrictions on delaying the epidemic growth and limiting the spread scope of COVID-19 in China, which helped better derive the geographical COVID-19 transmission related to population flow networks' structural features. • 42 transmission scenarios were simulated to test contribution of different original epicenters to seeding COVID-19 in China. • An importation risk model was built to test contribution of population flow among multiple epicenters to spreading COVID-19. • A population flow network was built to capture evolution of COVID-19 transmission and identify influential spreaders. • This paper quantified the effectiveness of travel restrictions on reducing the numbers of confirmed COVID-19 cases in China. [ABSTRACT FROM AUTHOR]

The COVID-19 global pandemic has posed unprecedented challenges to nations and cities worldwide. Governments have adopted Information and Communication Technologies (ICTs) to rapidly control the spread of a novel coronavirus. As an innovative but controversial ICT-based tool, health QR code plays a vital role by assisting rapid contact tracing. Yet, whether and how citizens accept this policy tool remains an unknown theoretical and empirical question. In this paper, we study the sources that determine citizens' acceptance of health QR code in city governance. Based on a nation-wide online survey covering 28 major provincial-capital cities in China, we find that individual experiences and political identities affect citizens' acceptance of QR code. Even though public opinion regarding this issue is diverse, the government's responses to citizens' requests play a critical role in enhancing their acceptance of using QR code both in the current and future stages. Specifically, as the citizens perceive a higher level of city government responsiveness, they are less worried about privacy leaks and more likely to perceive the effectiveness of health QR code in improving public health, thus resulting in a higher acceptance. The results offer broad policy implications for smart cities and urban governance. • We analyze how city government responsiveness helps improve citizens' acceptance of an ICT-based tool for urban governance. • Government responses signal the benefit of the QR code and demonstrate the government's commitment to protecting privacy. • Our findings suggest a practical measure to cultivate citizens' engagement in the governance of smart cities. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, an exceptional crisis, sparked the introduction of new digital infrastructure to halt the novel coronavirus's spread. This paper explores how such digital infrastructure's impact might reverberate over the long term, by comparing Singapore, Hong Kong, and mainland China's utilization of digital technology in response to the 2003 SARS outbreak, and their responses to the 2020 COVID-19 pandemic. We find that advancements in digital technology since 2003 have boosted governments' surveillance and segregation abilities substantially—most dramatically so in China. Even though some of these new digital interventions are ostensibly designed to be temporary ones to address the needs of the immediate crisis, we argue that the resultant extensions of state power experienced during COVID-19 are likely to have profound long-term effects because they fundamentally affect sociopolitical contexts, institutional capabilities, and digital cultures. We also find that the extent to which governments can extend digital surveillance and segregation abilities during the pandemic is contingent on their respective sociopolitical, institutional, and digital cultural contexts. • COVID-19 pandemic sparked calls for a new digital infrastructure. • We compare 2003 SARS outbreak to COVID-19 pandemic. • New digital technologies increased governments' ability to surveil and segregate. • Their impact on surveillance and segregation will persist post COVID-19. [ABSTRACT FROM AUTHOR]

This paper investigates the imppact of COVID-19 travel restrictions on population flow in the People's Republic of China. We discover an "unreasonable" surge in population flow after the Wuhan travel ban. We further find out that such a sure of population flow is attributed to the "spill-over" effect of the Wuhan travel ban. We utilize a logistic regression model to quantify that the spill-over effect linearly decays with the travel distance to the Pandemic center city. Because of the "spill-over" effect of the travel ban policy, government authorities should design redundancy polity to simultaneously implement a travel ban for the pandemic center city and its neighboring cities to restrain human movement and pandemic transmission. • We discovered the "spill-over" effect of the Wuhan travel ban. • A travel ban policy may stimulate human movement if it's not properly designed • The transportation distance to the COVID-19 pandemic center city negatively linearly determines the "spill-over" effect. • The "spill-over" effects can help city administrators to predicate population flow and make traffic control plans when pandemic outbreaks. [ABSTRACT FROM AUTHOR]

In the face of COVID-19, an emerging infectious disease, in addition to the classic non-pharmaceutical interventions such as isolation, quarantine, social, China also adopted strict mobility restrictions including inter-administrative districts travel restrictions, which severely affect residents' lives and almost completely stopped production activities at cost of a huge economic and social cost. In this paper, we develop the model of Dirk Brockmann and Dirk Helbing (2013) to theoretically explain the impact mechanism of prevention and control measures on the spread of the epidemic. Then, we divide the measures taken in China into two categories: mobility restrictions and other non-pharmacological interventions (O-NPI), and apply econometric approach to empirically test the effects of them. We find that although both of the two measures play a good role in controlling the development of the epidemic, the effect shows significant difference in different regions, and both the two measures had no significant effects in low-risk regions; Further, we prove that measures taken in a low-risk region is mainly against the imported cases, while a high-risk region has to defend against both imported cases and spread from within; The rapid and accurate transmission of information, a higher protection awareness of the public, and a stronger confidence of residents can promote the implementation of the measures. • COVID-19 epidemiological and epidemic control measures -related data of China during the outbreak are collected. • We use real-time data to explore the effect of COVID-19 control measures taken in China. • The public health measures implemented during the COVID-19 outbreak in China are divided into mobility restrictions and O-NPI. • Both of the two kinds of public health measures have no statistically significant effect in the low-risk areas. • We contend that measures should be tailored to the specific local and regional conditions. [ABSTRACT FROM AUTHOR]