Search

Since the outbreak of COVID-19 (Corona Virus Disease 2019), the Chinese government has taken strict measures to prevent and control the epidemic. Although the spread of the virus has been controlled, people's daily life and work have been affected and restricted to varying degrees. Thus people have different sentiments, these may affect people's implementation and compliance with the policies, thus affecting the effectiveness of epidemic prevention and control. At present, few pieces of literature have analyzed the relationships between people's feelings, policies, and epidemic trends. The object of this paper is to analyze the text content on social media, to find out the impact of the epidemic blockade policy on the public mood and the concerns expressed by the public about policies changes, and the interaction between policies and epidemic states at different stages of the epidemic. In this paper, we collected the posts of two cities where the epidemic occurred at the same time for analysis and comparative study. On the one hand, we revealed the changes in public attention and attitudes in the two regions during the epidemic, the other hand, it also reflects the differences in public sentiment between the two regions, as well as the correlation between emotions and policies and epidemic trends when different policies are adopted under different circumstances. The obtained results have a certain guiding significance for public health departments to formulate reasonable epidemic prevention policies. [ABSTRACT FROM AUTHOR]

The 2019 novel coronavirus disease (COVID-19; previously known as 2019-nCoV) outbreak that originated from Wuhan, Hubei province, China, at the end of 2019 was declared a public health emergency of international concern on Jan 30, 2020, by WHO.[1] As a newly appearing infectious disease, COVID-19 garnered great research interest. 2 E Stoye, China coronavirus: how many papers have been published? 3 CC Du, Ministry of Science and Technology: efforts should not be focused on publishing papers before epidemic prevention and control tasks are completed (in Chinese). http://www.caixin.com/2020-01-30/101509614.html Jan 30, 2020, (in Chinese). [Extracted from the article]

The outbreak of COVID-19 has resulted in an unprecedented attention and response to health surveillance in China, in which the Health Code has made outstanding contributions to digital social governance as well as epidemic control work. As China steps into the post-COVID-19 era, the Health Code will keep upgrading, optimizing and continue to play a role in regular epidemic prevention and control. This paper reviews the background, promoting reasons, significance and controversies of Health Code, so as to provide reference for the relative research and practical applications in the future. [ABSTRACT FROM AUTHOR]

The rate of infectious disease outbreaks has been accelerating over the past two decades, from the SARS epidemic in 2003 to COVID-19 in 2020. Termed by some as the twenty-first century's first pandemic, SARS originated in China and alerted the country to the importance of public health and epidemic response. After SARS, China improved its health infrastructure and reformed its political and legal health governance system. The emergence of COVID-19 from Wuhan in late 2019 put those reforms to the test. This paper analyses China's public health and epidemic response policies from a historical perspective, tracing the evolution of Chinese public health policies after the SARS outbreak in 2003. This paper assesses China's response to COVID-19 and how post-SARS policy reforms, particularly in epidemic response, played out on the ground in Wuhan. What policies worked well? What were the challenges faced? Based on the policy analysis, this paper presents recommendations for how China can improve its epidemic response through strengthened infectious disease surveillance, more transparent political coordination, and expanded public health infrastructure. [ABSTRACT FROM AUTHOR]

At the moment, the shortcomings in the system of responding to crises in the health sector lie in the imperfection of the response order and management mechanisms. The purpose of the paper is to investigate the legal regulation and reflection of public health emergencies in China, as exemplified by the case of 2019 coronavirus. The paper discusses the legal framework for the regulation of emergency situations in public health in China for the period from the end of 2019. The importance of preventing and controlling the epidemic is substantiated, and shortcomings in the work to combat the epidemic are analysed. Particular attention is paid to issues of informing the public and the rule of law in emergency situations in public health. The provisions of the legislation of the People's Republic of China in public health emergencies were also examined. The paper is of practical importance not only for China, but for the entire world in the prevention and control of coronavirus. [ABSTRACT FROM AUTHOR]

Since the existing epidemic models hadn' t considered the influence of environment on the infection of virus, and the classic epidemic model can't well reflect the feature of each individual, this paper developed an environment-aware susceptible- infected-recovered (EA-SIR) model by introducing an individual contact matrix to describe contact between each individual. This model derived environment-aware infection rate, the basic reproduction number and its upper bound. The upper bound of EA-SIR' s basic reproduction number wasn't greater than the classic SIR indicating that virus was difficult to spread in EA-SIR. People' s sense of self-protection helped block the spread of virus, therefore, EA-SIR was suitable for describing the virus spread theoretically. This paper conducted experiments using COVID-19 data of Diamond Princess and four cities in China to evaluate the performance of EA-SIR,and used mean absolute error as evaluation standard. The simulation results show that EA-SIR can better describe the spread of COVID-19. [ABSTRACT FROM AUTHOR]

Introduction: The epidemic of viral respiratory diseases in the last 20 years has affected many people around the world. In these situations, telemedicine may reduce unnecessary contacts and the risk of exposure to infection. This study aimed to review the papers performed to manage viral respiratory disease epidemics using telemedicine. Material and Methods: The PubMed and Scopus databases were searched in May 2020 for this systematic review study. Data were extracted from the final included papers based on the author, country, type of epidemic, telemedicine modality, telecommunication method, objective, participants, clinical outcome, cost, and satisfaction. Descriptive statistics were used to analyze data. Results: From 365 retrieved papers, 18 papers were included. Most of the papers were done in the US and China (67%). Half of the papers were done during the COVID-19 pandemic. Real-time modality was used in 78% of the papers. The telecommunication method in half of the papers was internetbased. Patients’ management and treatment was the main objective of the six papers. In 81% of the teleconsultation papers, the consultation was performed between patients and healthcare providers. The clinical outcome of all papers showed that telemedicine was successful in the management of viral respiratory disease epidemics. Cost and satisfaction outcomes were considered in a few papers. Conclusion: There is considerable evidence to show that telemedicine is a useful and convenient method to manage and control viral respiratory disease epidemics. Therefore, countries should pay special attention to telemedicine to control the current pandemic and future epidemics and use it extensively. [ABSTRACT FROM AUTHOR]

Drawing on a recent online survey combined with city-level data, this paper examines the impact of the COVID-19 on consumers' online food purchase behavior in the short term. To address the potential endogeneity issues, we adopt an instrumental variable (IV) strategy, using the distance from the surveyed city to Wuhan as the instrumental variable. We show that our IV method is effective in minimizing potential bias. It is found that the share of confirmed COVID-19 cases increases the possibility of consumers purchasing food online. This is more likely to be the case for young people having a lower perceived risk of online purchases and living in large cities. Despite some limitations, this paper has policy implications for China and other countries that have been influenced by the COVID-19 epidemic. Specifically, government support and regulation should focus on (i) ensuring the safety of food sold on the internet, (ii) protecting the carrier from becoming infected, and (iii) providing financial support to the poor since they may have difficulties in obtaining access to food living in small cities. Moreover, how to help those who are unable to purchase food online because of their technical skills (e.g., the elderly who are not familiar with smart phones or the internet) also deserves more attention for the government and the public. [ABSTRACT FROM AUTHOR]

This paper investigates a new multi-objective order assignment and scheduling problem for personal protective equipment (PPE) production and distribution during the outbreak of epidemics like COVID-19. The objective is to simultaneously minimize the total cost and maximize the PPE supply timeliness. For the problem, we first develop a bi-objective mixed-integer linear program (MILP). Then an $\epsilon $ -constraint combined with logic-based Benders decomposition method is proposed based on some explored properties. We then extend the proposed model to handle dynamics and randomness. In particular, we design a predictive reactive rescheduling approach to address random order arrivals and manufacturer disruptions. Computational experiments on a real case from China and 100 randomly generated instances are conducted. Results show that the proposed algorithm significantly outperforms an adapted $\epsilon $ -constraint method combined with the proposed MILP and the widely used non-dominated sorting genetic (NSGA-II) in obtaining high-quality Pareto solutions. Note to Practitioners—The unprecedented outbreak of COVID-19 and its rapid spread caught numerous national and local governments unprepared. Healthcare systems faced a vital scarcity of PPEs. The urgency of producing and delivering PPEs increases as the number of infected cases rapidly increases. A key challenge in response to the epidemic is effectively and efficiently matching the demands and needs. Performing practical and efficient order assignment and scheduling for PPE production during the COVID-19 outbreak is critical to curbing the COVID-19 pandemic. This work first proposes a bi-objective mixed-integer linear program for optimal order assignment and scheduling for PPE production. The aim is to achieve an economical and timely PPE production and supply. A novel method that combines the $\epsilon $ -constraint framework and the logic-based Benders decomposition is proposed to yield high-quality Pareto solutions for practical-sized problems. Computational results indicate that the proposed approaches are practical and feasible, which can help decision-makers to perform acceptable order assignment and scheduling decisions. [ABSTRACT FROM AUTHOR]

The global outbreak of COVID-19 has further exposed deficiencies in city logistics based on human and ground roads, such as poor emergency response capacity and high risk of infection during transportation. Metro-based underground logistics system (M-ULS) may be an innovative approach to deal with this city-level disaster due to its efficient operation, contactless and driverless characteristics. However, the market evolution process and the quantitative calculation framework of comprehensive benefits after the application of M-ULS are still unclear, which has become a problem of mutual restriction with the extensive application of M-ULS. This paper attempts to use the system dynamics method, based on the real-world simulation, to analyze the quantitative relationship between the M-ULS implementation and the city logistics performance under epidemic outbreaks. Wuhan city in China was selected as the empirical background, and five simulation scenarios were set under different implementation strategies of M-ULS in response to the epidemic. Six variables were selected to measure city logistics performance and M-ULS operation status, including demand fill-rate, unit delivery time, total deprivation cost, total transportation cost, total number of susceptible people, and utilization rate of M-ULS. The results show that M-ULS is effective in improving the performance of city logistics and responding to the epidemic. The delivery time and transportation cost have a strong impact on the market share of M-ULS. Finally, a set of incentive policies was designed to promote the adoption of M-ULS. The findings not only provide a method for evaluating the overall performance of M-ULS, but also provide a unique perspective for promoting the implementation of M-ULS and responding to the transportation challenges brought by the epidemic. • M-ULS is introduced to break through the plight of city logistics. • A set of effective macro-micro incentive policies are established to promote the implementation of M-ULS. • The delivery time, transportation cost and government subsidies play different roles in the market penetration of M-ULS. • The benefits of M-ULS have been analyzed. [ABSTRACT FROM AUTHOR]

Information and communication technologies occupy a central position in the Covid-19 pandemic. Public response has been deemed extremely important, with social media platforms playing a key role in both institutional and bottom-up information sharing processes. The emerging field of platform studies has shown that platforms increasingly influence how society works; however, such studies often adopt a highly Western-centric approach. By focusing on Twitter and Weibo use in the early stages of the pandemic, the paper presents an exploratory study that comparatively explores the role of the two platforms for both Western and Chinese publics. Our findings indicate that during the Covid-19 outbreak, Weibo worked as a propaganda tool to unite the Chinese people and promote public policies under the control of the government and the guidance of the mainstream media. Twitter functioned more like a public discourse platform open to personal expression, often showing the influence of defined partisan political discourses. We argue that the participatory dynamics characterizing Weibo and Twitter conversations at the outbreak of the pandemic at least partially mirrored the different 'platforms societies' currently developing in China and the West. [ABSTRACT FROM AUTHOR]

Within half a year, COVID-19 spreads to most countries in the world, as well as posed a great threat to the public health of human beings. The implementation of non-pharmaceutical intervention (NPI), including travel ban, proved to be an effective way for controlling the epidemic spreading, e.g., the ban of inter-city transportation stops transporting virus through passengers between cities. However, travel ban could significantly impact many industries, e.g. tourism and logistics, thus jeopardizing the regional economy. This paper focus on assisting the national or regional government to make dynamic decisions on restricting and recovering intercity multi-modal travel services. Our model can characterize impacts of inter-city traffic on the spread of the COVID-19, as well as on the regional economy. By applying a reinforcement learning approach, we develop an online optimization model to identify the modal-specific travel banning strategy that can balance the epidemic control as well as the negative impacts on regional economy. The numerical study based on a network of multiple cities in China shows that the proposed approach can generate better strategies compared with some existing methods. [ABSTRACT FROM AUTHOR]

In this paper, the interaction strategies and the evolutionary game analysis of the actions taken by the government and the public in the early days of the epidemic are incorporated into the natural transmission mechanism model of the epidemic, and then the transmission frequency equations of COVID-19 epidemic is established. According to the cumulative confirmed cases of COVID-19 in the UK and China, the upper limit of the spread of COVID-19 in different evolutionary scenarios is set. Using SPSS to perform logistic curve fitting, the frequency fitting equations of cumulative confirmed cases under different evolution scenarios are obtained respectively. The analysis result shows that the emergency response strategy adopted by the government in the early days of the epidemic can effectively control the spread of the epidemic. Combined with the transmission frequency equation of COVID-19 epidemic, measures taken by the government are analyzed. The influence of each measure on the frequency variable is judged and then the influence on the spread of the epidemic is obtained. Finally, based on the above analysis, the government is advised to adhere to the principles of scientific, initiative and flexibility when facing major epidemics. [ABSTRACT FROM AUTHOR]

It is essential for cross-regional control and treatment of major epidemics to establish a collaborative, efficient, and precise collective response mechanism. Based on the observation of the COVID-19 epidemic, this paper concludes major measures and experience of cross-regional collective response for epidemic control and treatment, compares the difference between localities at home and abroad, and puts forwards major strategies for a cross-regional collective response, hoping to provide policy-making references to improve the modernization level of public health, epidemic prevention, and emergency management in China. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is a new human infectious disease. The etiology for this outbreak is a novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Thus far, related research on COVID-19 is still in preliminary stage. This paper summarized the latest outcomes of corresponding study from Chinese centers and clarified the hematopoietic abnormality caused by SARS-CoV-2 and potential mechanism. Lymphopenia was common in the early stage after the onset of COVID-19. A significant decrease was observed in peripheral CD4+ and CD8+ T lymphocytes. As the illness progressed, neutrophilia emerged in several cases, and patients with severe critical pulmonary conditions showed higher neutrophils than common type. Thrombocytopenia was resulting from the consumption and/or the reduced production of platelets in damaged lungs. Anemia was not observed notably, but the decrease in hemoglobin was frequent. The activation of monocyte-macrophage system aggravates the immune damage of lung and other tissues, which leads to the increase of D-dimer, prothrombin time, and platelet consumption. [ABSTRACT FROM AUTHOR]

We propose a varying coefficient Susceptible-Infected-Removal (vSIR) model that allows changing infection and removal rates for the latest corona virus (COVID-19) outbreak in China. The vSIR model together with proposed estimation procedures allow one to track the reproductivity of the COVID-19 through time and to assess the effectiveness of the control measures implemented since Jan 23 2020 when the city of Wuhan was lockdown followed by an extremely high level of self-isolation in the population. Our study finds that the reproductivity of COVID-19 had been significantly slowed down in the three weeks from January 27th to February 17th with 96.3% and 95.1% reductions in the effective reproduction numbers R among the 30 provinces and 15 Hubei cities, respectively. Predictions to the ending times and the total numbers of infected are made under three scenarios of the removal rates. The paper provides a timely model and associated estimation and prediction methods which may be applied in other countries to track, assess and predict the epidemic of the COVID-19 or other infectious diseases. [ABSTRACT FROM AUTHOR]

During the prevention and control of COVID - 19 epidemic, most universities in China adopted the online teaching with new media technology. Problem - oriented learning (PBL) is an important content to realize student - centered educational activities and an important carrier to develop students' abilities. In this paper, the PBL teaching mode for postgraduate students during the prevention and control of COVID - 19 epidemic is analyzed, which is of guiding significance for the realization of the combined offline and online teaching mode in the future. [ABSTRACT FROM AUTHOR]

In December 2019, a new virus (initially called 'Novel Coronavirus 2019-nCoV' and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China's massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics. [ABSTRACT FROM AUTHOR]

An outbreak of coronavirus disease (COVID-19) in Wuhan, China caused by SARS-CoV-2 has led to a serious epidemic in China and other countries, resulting in worldwide concern. With active efforts of prevention and control, more and more patients are being discharged. However, how to manage these patients normatively is still challenging. This paper reports an asymptomatic discharged patient with COVID-19 who retested positive for SARS-CoV-2, which arouses concern regarding the present discharge standards of COVID-19. [ABSTRACT FROM AUTHOR]

The author offers updates on the efficacy of the physiotherapeutic modalities in patients with COVID-19 disease as of March 2020. Topics mentioned include forced bed rest related to mechanical ventilation and sedation, implementation of verbal instructions and remote supervision to avoid direct contact with patients, and a position paper issued by the Italian Association of Respiratory Physiotherapists offering advice to be considered when treating COVID-19 patients.

The complex dynamics of human mobility, combined with sporadic cases of local outbreaks, make assessing the impact of large-scale social distancing on COVID-19 propagation in China a challenge. In this paper, with the travel big dataset supported by Baidu migration platform, we develop a reactive–diffusion epidemic model on human mobility networks to characterize the spatio-temporal propagation of COVID-19, and a novel time-dependent function is incorporated into the model to describe the effects of human intervention. By applying the system control theory, we discuss both constant and time-varying threshold behavior of proposed model. In the context of population mobility-mediated epidemics in China, we explore the transmission patterns of COVID-19 in city clusters. The results suggest that human intervention significantly inhibits the high correlation between population mobility and infection cases. Furthermore, by simulating different population flow scenarios, we reveal spatial diffusion phenomenon of cases from cities with high infection density to cities with low infection density. Finally, our model exhibits acceptable prediction performance using actual case data. The localized analytical results verify the ability of the PDE model to correctly describe the epidemic propagation and provide new insights for controlling the spread of COVID-19. • A reaction–diffusion epidemic model on human mobility networks is studied. • The constant and time-varying threshold behavior of the model is discussed. • Human intervention inhibits the high correlation between migration and pandemics. • The spatial diffusion of cases among cities is numerically simulated. • The predictive performance of the model is validated by using real case data. [ABSTRACT FROM AUTHOR]

Understanding the processes and mechanisms of the spatial spread of epidemics is essential for making reasonable judgments on the development trends of epidemics and for adopting effective containment measures. Using multi-agent network technology and big data on population migration, this paper constructed a city-based epidemic and mobility model (CEMM) to stimulate the spatiotemporal of COVID-19. Compared with traditional models, this model is characterized by an urban network perspective and emphasizes the important role of intercity population mobility and high-speed transportation networks. The results show that the model could simulate the inter-city spread of COVID-19 at the early stage in China with high precision. Through scenario simulation, the paper quantitatively evaluated the effect of control measures "city lockdown" and "decreasing population mobility" on containing the spatial spread of the COVID-19 epidemic. According to the simulation, the total number of infectious cases in China would have climbed to 138,824 on February 2020, or 4.46 times the real number, if neither of the measures had been implemented. Overall, the containment effect of the lockdown of cities in Hubei was greater than that of decreasing intercity population mobility, and the effect of city lockdowns was more sensitive to timing relative to decreasing population mobility. • A city-based epidemic and mobility model is proposed for simulating the spatial spread of an epidemic between cities. • The effect of "city lockdowns" and "decreasing population mobility" measures were evaluated under ten scenarios. • The effect of decreasing returns to scale and distance decay of population mobility on the epidemic spread were found. [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]