Special Economic Zones of High Technological Development in China: Shanghai and Shenzhen

Since 1979, China has experienced dazzling economic progress thanks to economic reforms and Special Economic Zone (SEZ) projects. Disciplined labor processes and government involvement have been key factors in its financial and technological success. Cities such as Shanghai and Shenzhen have become fundamental pillars in scientific and technological development, based on the creation of new energies, robotics, health, telecommunications, biotechnology, genetics, space exploration, artificial intelligence, quantum computing, making the Asian giant a global technological hub. The objective of this research is to analyze the technological impact of Shanghai and Shenzhen, considered as Special Economic Zones of High Technological Development (ZEEADT) because they are fundamental pillars in the continuity of China as the first world economic power. As a result of this efficiency, the Asian country has continued to grow and strengthen even during the economic slowdown caused by COVID-19.

Urban Farming: The Reluctant Utopia

The old conceptual dichotomy between the city and the countryside has often been a historical stumbling block for architects and urban planners. Whilst there have been many attempts to bring the city closer to the natural environment, some on grand scales, more modest experiments have often gleaned better results. Daniele Belleri is a partner at design and innovation office CRA-Carlo Ratti Associati, where he is in charge of all editorial and curatorial projects. He and the practice's founder, architect and engineer Carlo Ratti – who is director of the Senseable City Lab at the Massachusetts Institute of Technology (MIT) – together explore our contemporary options. Copyright © 2023 John Wiley & Sons, Ltd.

The 4Rs approach to COVID-19 emergency management during the post-pandemic period: What lessons can be learned from Shenzhen, China?

The Omicron variant of SARS-CoV-2 (or Omicron) is extremely contagious and has swept the world in a short period. Shenzhen—a new international city in China with a permanent population of 17.56 million and covering nearly 2000 square kilometers—was attacked by Omicron in 2022. However, the pandemic was controlled in a very short time as a result of prompt government reaction that prevented the variant's further spread. The total number of cases in this wave of the pandemic was more than 2600. Shenzhen's successful experience in tackling the Omicron wave deserves in-depth discussion. Proposed by American scholar Robert Heath, the 4Rs model aims to reduce the harm from a crisis through the measures of reduction, readiness, response, and recovery. This article presents the successful experience of Shenzhen's local government and the Shenzhen Third People's Hospital, the only hospital in Shenzhen designated to use the 4Rs emergency management model for the treatment of COVID-19 during the 2022 Omicron wave of the pandemic.

The effectiveness of travel restriction measures in alleviating the COVID-19 epidemic: evidence from Shenzhen, China.

With the expansion of the global novel coronavirus disease (COVID-19) pandemic, unprecedented interventions have been widely implemented in many countries, including China. In view of this scenario, this research aims to explore the effectiveness of population mobility restriction in alleviating epidemic transmission during different stages of the outbreak. Taking Shenzhen, a city with a large immigrant population in China, as a case study, the real-time reproduction number of COVID-19 is estimated by statistical methods to represent the dynamic spatiotemporal transmission pattern of COVID-19. Furthermore, migration data between Shenzhen and other provinces are collected to investigate the impact of nationwide population flow on near-real-time dynamic reproductive numbers. The results show that traffic flow control between populated cities has an inhibitory effect on urban transmission, but this effect is not significant in the late stage of the epidemic spread in China. This finding implies that the government should limit international and domestic population movement starting from the very early stage of the outbreak. This work confirms the effectiveness of travel restriction measures in the face of COVID-19 in China and provides new insight for densely populated cities in imposing intervention measures at various stages of the transmission cycle.

Unlocking private investment as a new determinant of green finance for renewable development in China

The COVID-19 pandemic has pushed up the green finance for renewable energy development. Private investment has been recognized as a dominant driver of the renewable energy industry, an essential and critical step in averting greenhouse gas emissions. Nonetheless, despite the increasing pace, private investment in green finance for renewable development is still restricted to several developed nations, where it is crucial. Prior studies have offered some understanding of the complexities and challenges that investment confronts in this industry, which remains underexplored in the case of China. This study employs the ARDL-PMG model used to examine the public listed companies in Shanghai and Shenzhen during China's 2010–2020 period. This research adds to the body of knowledge by rigorously examining the variables on FDI in renewable energy production in China and how these effects differ depending on the source of investment. Some of these factors include the adoption of national renewable energy legislation, the supply of foreign public money, and the broader economic environment. The findings indicate that worldwide financial assistance, legislative support policies, feed-in tariffs, and economic stability are potent drivers of green finance for developing renewable energy investment in China. Further, this research explains that the impacts of private sector investment and entrepreneurial contextual factors on expenditure vary depending on the source of finance, emphasizing the importance of dissecting investment spreads to fully comprehend private investment decisions in green finance for renewable development. © 2022

Identifying Risk Transmission in Carbon Market With Energy, Commodity and Financial Markets: Evidence From Time-Frequency and Extreme Risk Spillovers

The carbon market is a vital tool to achieve carbon neutrality. This paper uses daily closing price data of Shenzhen carbon trading market, energy, commodity and financial markets from 18 October 2018 to 19 August 2021, examining the transmission of risk/information from the perspective of market volatility spillover and tail risk transmission based on quantile spillover. The stock market crash and COVID-19 have increased the volatility of the system substantially. Next, the increase in trading frequency is accompanied by an increase in total volatility connectivity, and the carbon market transforms into a recipient of systemic shocks. Finally, the results of tail risk transmission reveal that the net effect of carbon reception increases significantly. These findings have implications for policymakers to improve the carbon market and provide important insights for investors to trade in turbulent periods.

Analysis of the Complex Network of the Urban Function under the Lockdown of COVID-19: Evidence from Shenzhen in China

In this paper, the complex network of the urban functions in Shenzhen of China under the lockdown of the corona virus disease 2019 (COVID-19) is studied. The location quotient is used to obtain the dominant urban functions of the districts in Shenzhen before and under the lockdown of COVID-19. By using the conditional probability, the interdependencies between the urban functions are proposed to obtain the complex networks of urban functions and their clusters. The relationships between the urban functions, and the overall and cluster characteristics of the urban functions before and under the lockdown of COVID-19 are analyzed based on the complex networks. The mean degree and mean weighted degree of the primary categories of the urban functions are obtained to discuss the classification characteristics of the urban functions before and under the lockdown of COVID-19. Then, the differences and changes of the urban functions before and under the lockdown of COVID-19 are compared, and the corresponding policy implications under the lockdown of COVID-19 are presented. The results show that under the lockdown of COVID-19, the correlation of the urban functions is stronger than that before the lockdown;the common urban functions are more useful and essential, and finance, fine food and medical treatment are important;public service and government departments have the most positive relationship with other urban functions, and finance service has the highest spatial agglomeration distribution trend;and the cluster characteristics of urban functions are more related to people's livelihood, and the urban functions show incomplete and cannot be operated for long term. [ FROM AUTHOR] Copyright of Mathematics (2227-7390) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Evaluation of work resumption strategies after COVID-19 reopening in the Chinese city of Shenzhen: a mathematical modeling study.

OBJECTIVES: As China is facing a potential second wave of the epidemic, we reviewed and evaluated the intervention measures implemented in a major metropolitan city, Shenzhen, during the early phase of Wuhan lockdown. STUDY DESIGN: Based on the classic SEITR model and combined with population mobility, a compartmental model was constructed to simulate the transmission of COVID-19 and disease progression in the Shenzhen population. METHODS: Based on published epidemiological data on COVID-19 and population mobility data from Baidu Qianxi, we constructed a compartmental model to evaluate the impact of work and traffic resumption on the epidemic in Shenzhen in various scenarios. RESULTS: Imported cases account for most (58.6%) of the early reported cases in Shenzhen. We demonstrated that with strict inflow population control and a high level of mask usage after work resumption, various resumptions resulted in only an insignificant difference in the number of cumulative infections. Shenzhen may experience this second wave of infections approximately two weeks after the traffic resumption if the incidence risk in Hubei is high at the moment of resumption. CONCLUSION: Regardless of the work resumption strategy adopted in Shenzhen, the risk of a resurgence of COVID-19 after its reopening was limited. The strict control of imported cases and extensive use of facial masks play a key role in COVID-19 prevention.

The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China-An Analysis Based on 417 Cases.

The global pandemic of COVID-19 has made it the focus of current attention. At present, the law of COVID-19 spread in cities is not clear. Cities have long been difficult areas for epidemic prevention and control because of the high population density, high mobility of people, and high frequency of contacts. This paper analyzed case information for 417 patients with COVID-19 in Shenzhen, China. The nearest neighbor index method, kernel density method, and the standard deviation ellipse method were used to analyze the spatio-temporal characteristics of the COVID-19 spread in Shenzhen. The factors influencing that spread were then explored using the multiple linear regression method. The results show that: (1) The development of COVID-19 epidemic situation in Shenzhen occurred in three stages. The patients showed significant hysteresis from the onset of symptoms to hospitalization and then to diagnosis. Prior to 27 January, there was a relatively long time interval between the onset of symptoms and hospitalization for COVID-19; the interval decreased thereafter. (2) The epidemic site (the place where the patient stays during the onset of the disease) showed an agglomeration in space. The degree of agglomeration constantly increased across the three time nodes of 31 January, 14 February, and 22 February. The epidemic sites formed a "core area" in terms of spatial distribution and spread along the "northwest-southeast" direction of the city. (3) Economic and social factors significantly impacted the spread of COVID-19, while environmental factors have not played a significant role.

How Shenzhen, China avoided widespread community transmission: a potential model for successful prevention and control of COVID-19.

Shenzhen is a city of 22 million people in south China that serves as a financial and trade center for East Asia. The city has extensive ties to Hubei Province, the first reported epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the world. Initial predictions suggested Shenzhen would experience a high number of COVID-19 cases. These predictions have not materialized. As of 31 March 2020 Shenzhen had only 451 confirmed cases of COVID-19. Contact tracing has shown that no cases were the result of community transmission within the city. While Shenzhen did not implement a citywide lockdown like Wuhan, it did put into place a rapid response system first developed after the severe acute respiratory syndrome (SARS) epidemic in 2003. In the wake of the 2003 SARS outbreak, Shenzhen health authority created a network for surveillance and responding to novel respiratory infections, including pneumonia of unknown causes (PUC). The network rapidly detected mass discussion about PUC and immediately deployed emergency preparedness, quarantine for close contacts of PUC. Five early actions (early detection, early reporting, early diagnosis, early isolation, and early treatment) and four centralized responses (centralized coordination by experts, centralized allocation of resources, centralized placement of patients, and centralized provision of treatment) ensured effective prevention and control. Tripartite working teams comprising community cadres, medical personnel and police were formulated to conduct contact tracing at each neighborhood and residential community. Incorporation of mobile technology, big data, and artificial intelligence into COVID-19 response increased accessibility to health services, reduced misinformation and minimized the impact of fake news. Shenzhen's unique experience in successfully controlling the COVID-19 outbreak may be a useful model for countries and regions currently experiencing rapid spread of the virus.

Estimating the serial interval of the novel coronavirus disease (COVID-19) based on the public surveillance data in Shenzhen, China, from 19 January to 22 February 2020.

The novel coronavirus disease (COVID-19) poses a serious threat to global public health and economics. Serial interval (SI), time between the onset of symptoms of a primary case and a secondary case, is a key epidemiological parameter. We estimated SI of COVID-19 in Shenzhen, China based on 27 records of transmission chains. We adopted three parametric models: Weibull, lognormal and gamma distributions, and an interval-censored likelihood framework. The three models were compared using the corrected Akaike information criterion (AICc). We also fitted the epidemic curve of COVID-19 to the logistic growth model to estimate the reproduction number. Using a Weibull distribution, we estimated the mean SI to be 5.9 days (95% CI: 3.9-9.6) with a standard deviation (SD) of 4.8 days (95% CI: 3.1-10.1). Using a logistic growth model, we estimated the basic reproduction number in Shenzhen to be 2.6 (95% CI: 2.4-2.8). The SI of COVID-19 is relatively shorter than that of SARS and MERS, the other two betacoronavirus diseases, which suggests the iteration of the transmission may be rapid. Thus, it is crucial to isolate close contacts promptly to effectively control the spread of COVID-19.

Response to the COVID-19 epidemic: a report from Shenzhen, China.

The whole world is now facing an unprecedented pandemic with over 1.8 million confirmed cases and more than one hundred thousand deaths. To counter the pandemic, Shenzhen created a central command and control structure based on the only designated hospital- Shenzhen Third People's Hospital which is a large general hospital specialized on infectious diseases in the bay area. The hospital has taken many decisive and effective actions to respond to the epidemic. Here, we will describe and share healthcare experiences from Shenzhen and call for international cooperation and collaboration.

Community Transmission of Severe Acute Respiratory Syndrome Coronavirus 2, Shenzhen, China, 2020.

Since early January 2020, after the outbreak of coronavirus infection in Wuhan, China, ≈365 confirmed cases have been reported in Shenzhen, China. The mode of community and intrafamily transmission is threatening residents in Shenzhen. Strategies to strengthen prevention and interruption of these transmissions should be urgently addressed.