COVID-19 In Wuhan Research Articles

Effectiveness of seven oral traditional Chinese medicines against mild or moderate COVID-19: An updated systematic review and network meta-analysis

BackgroundSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the outbreak of COVID-19 in Wuhan, China. As a highly infectious epidemic, SARS-CoV-2 rapidly evolves. Presently, COVID-19 coexists with humans, mainly with mild or moderate disease. The latest Guidelines for the Diagnosis and Treatment of COVID-19 (trial version of the 10th Edition) recommend several oral traditional Chinese medicines (TCMs) for treatment. This study aims to evaluate the evidence-based benefits of these TCMs as adjunctive therapies to conventional western medicine (CWM) for patients with mild or moderate COVID-19. MethodsWe conducted a systematic review and meta-analysis adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, utilizing the PRISMA checklist. We searched PubMed, Cochrane Library, Embase, CNKI, and Wan-Fang databases to retrieve randomized controlled trials and retrospective cohort studies of TCM in combination with CWM on the treatment of mild or moderate COVID-19 that were published as of December 25, 2023. A network meta-analysis using the frequency model was employed to evaluate the benefits of different interventions. ResultsA total of 30 eligible studies, enrolling 4144 participants, utilized 7 marketed oral TCMs in China. Compared with CWM alone, the integration of TCMs with CWM can significantly reduce severe conversion rate. This combined approach also enhances the clinical effective rate, shortens the negative conversion time of nucleic acid, and improves both symptoms and blood biochemical markers in patients. The network meta-analysis provided preliminary evidence of the superiority of specific TCMs for various outcomes: Qingfei Paidu for raising the CT improvement rate and clinical effective rate, and shortening the negative conversion time of nucleic acid; Huashi Baidu for reducing severe conversion and improving cough; Xuanfei Baidu for improving fatigue; Jinhua Qinggan for improving fever; Lianhua Qingwen for shortening the recovery time of fatigue and cough; and Shufeng Jiedu for shortening the recovery time of fever. ConclusionsTCM in combination with CWM may be beneficial for patients with mild or moderate COVID-19. Each TCM may have distinct benefits in COVID-19.

Research on the Forecast of Emergency Supplies for Major Public Health Emergencies - An Empirical Study Based on the Distribution of Donated Facial Masks by the Wuhan COVID-19 Epidemic Prevention and Control Headquarters

Research on the Forecast of Emergency Supplies for Major Public Health Emergencies - An Empirical Study Based on the Distribution of Donated Facial Masks by the Wuhan COVID-19 Epidemic Prevention and Control Headquarters

Testing influences of openness, conscientiousness, nationalism, media diversity, social class, and informational echo chambers on support for official responses to COVID-19 in Wuhan in November, 2020.

As the COVID-19 pandemic raged, controversies about governmental responses to the epidemic also emerged in China. Previous studies mainly described the phenomenon of individual differences on support for governmental responses to COVID-19 with less attention to the underlying causal mechanisms. Thus, this study tries to verify the factors influencing public support for official behaviors in COVID-19. A questionnaire survey was drew on in Wuhan city during the COVID-19 outbreak. The quota sampling method was adopted according to the gender and age structure of the population in Wuhan as well as the educational structure of the urban population in China. Through structural equation analysis, this study confirms that personal factors (namely conscientiousness and nationalistic ideology), behavioral factors (namely media diversity and echo chamber acts) exert significantly positive impacts on support for governmental responses. The echo chamber acts play important mediating roles in the relationship between each independent variable and support for governmental responses. The originality of this study is that it constructs a comprehensive model of influencing factors of support for governmental responses with the personal, behavioral, and environmental factors. While contributing insight to political attitude in China, the research results also have significance for promoting public trust and constructing healthy public opinion in China.

A study on post-traumatic stress disorder and post-traumatic growth among patients infected with COVID-19 in Wuhan.

The purpose of this study is to assess the physical and psychological conditions of hospitalized patients who were infected with COVID-19 in Wuhan, China, including post-traumatic stress disorder (PTSD) and post-traumatic growth (PTG) scores and predictors. The test group consisted of 102 hospitalized patients diagnosed with COVID-19 in Wuhan between March 4, 2020 and April 5, 2020, whereas the control group comprised 168 healthy study participants. Relevant information of the study participants was obtained using online questionnaires, covering five aspects-general information, physical state, emotional state, PTSD, and PTG. In Wuhan, 37.3% of COVID-19-diagnosed hospitalized patients exhibited hyper-arousal symptoms of PTSD. This percentage is significantly higher than the 13.1% observed in the healthy population. Furthermore, the prevalence of PTG among the same group of hospitalized patients stood at 77.5%, surpassing the 66.1% rate found within the healthy population. It was determined that inconsistent sleep patterns during the hospitalization phase could be indicative of heightened vulnerability to hyperarousal symptoms of PTSD in COVID-19-diagnosed hospitalized patients. The study determined that inconsistent sleep patterns during hospitalization may be a predisposition factor that makes hospitalized patients diagnosed with covid-19 more susceptible to high arousal symptoms of post-traumatic stress disorder. Conversely, COVID-19-diagnosed hospitalized patients who maintained a tranquil demeanor and exhibited positive emotional perceptions during their hospitalization displayed reduced susceptibility to these PTSD symptoms. Factors such as possession of a bachelor's degree, history of severe acute respiratory syndrome (SARS) infection, and poor sleep patterns were identified as predictors elevating the risk of PTG. Whereas, a sentiment of happiness and consistent positive emotional perception during hospitalization were predictors of PTG. Intriguingly, a direct correlation was established between hyper-arousal symptoms of PTSD and PTG. Although the outbreak of COVID-19 has badly affected the physical and psychological well-being of patients, it has greatly enhanced their PTG.

Traditional bureaucracy and newly-revived leading groups: The Chinese government’s organizational responses to COVID-19

Drawing on instrumental-structural and cultural-value perspectives, this article examines the Chinese government’s organizational responses to COVID-19 in Wuhan. It highlights two stages: cover-up and inaction, and then a draconian national campaign, with the creation of a central Leading Group (LG) as a major landmark. This process involves a layered institutional change, integrating networked LG arrangements into the existing bureaucracy system. Culturally, collective values initially discourage local risky action but later encourage national mobilization. Importantly, under the Party’s leadership, a network of networks has been formed around the CLG, showcasing both Chinese characteristics and post-NPM features.

IFN-γ decreases PD-1 in T lymphocytes from convalescent COVID-19 patients via the AKT/GSK3β signaling pathway

Post-COVID-19 syndrome may be associated with the abnormal immune status. Compared with the unexposed age-matched elder group, PD-1 in the CD8+ T cells from recovered COVID-19 patients was significantly lower. IFN-γ in the plasma of COVID-19 convalescent patients was increased, which inhibited PD-1 expression in CD8+ T cells from COVID-19 convalescent patients. scRNA-seq bioinformatics analysis revealed that AKT/GSK3β may regulate the INF-γ/PD-1 axis in CD8+ T cells from COVID-19 convalescent patients. In parallel, an IFN-γ neutralizing antibody reduced AKT and increased GSK3β in PBMCs. An AKT agonist (SC79) significantly decreased p-GSK3β. Moreover, AKT decreased PD-1 on CD8+ T cells, and GSK3β increased PD-1 on CD8+ T cells according to flow cytometry analysis. Collectively, we demonstrated that recovered COVID-19 patients may develop long COVID. Increased IFN-γ in the plasma of recovered Wuhan COVID-19 patients contributed to PD-1 downregulation on CD8+ T cells by regulating the AKT/GSK3β signaling pathway.

Trailing World Health Assembly Resolution 73.1: Pathway to Quick and Accurate Determination of the Source of Outbreak of COVID-19 in Wuhan, China.

For more than four years now, the objective of determining the source of the outbreak of COVID-19 in Wuhan, China and the route of transmission of the infection to the human population has not been achieved despite existing capacity in molecular epidemiology and World Health Assembly Resolution mandating that objective. This study seeks to ascertain the reasons for failure to achieve that objective and to propose feasible alternative strategies to attain that objective quickly and accurately. Exploratory research was adopted, applying the tools of input-output device, data extraction, management by objective, rational decision approach and the deductive model. Fitting the objective of determining the source of the outbreak of COVID-19 as expected output, the actions of key players in the pandemic response (fitted as processors) were evaluated for consistence or otherwise in transforming data/inputs to achieve the output/objective. The study found that the World Health Assembly (WHA) Resolution 73.1 (9 (6)) mandating the World Health Organization (WHO) to pursue the objective of determining the source of the outbreak of COVID-19 was not diligently and committedly implemented; that the WHO and China have deliberately evaded that objective; that previous and ongoing studies focusing on the circulation of SARS-CoV-2 in other countries and similar themes are diversionary and unnecessary workload that depart from the core objective; and that adopting a five-point alternative strategy will ensure the attainment of the core objective within 14 days, including: (i) re-phrasing of the WHA mandate for specificity; (ii) subjecting all possible pathways of transmission to scrutiny; (iii) adopting “confirmed” genetic sequences of SARS-CoV-2 for subsequent use in molecular epidemiology; (iv) establishing a ‘red circle’ of 2 km radius from the Huanan wet market for top-priority epidemiologic investigation; (v) review of Resolution WHA73.1(9 (6)) at upcoming WHA to expressly prescribe unfettered right of access to the international study team and sanction for non-compliance. The study concludes that determining the source of the outbreak of COVI-19 in Wuhan, China is an important objective that should be accomplished within 14 days considering existing capacity in molecular epidemiology, if avoidable impediments are removed.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Air travel monitoring does not accelerate outbreak detection in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Understanding the implications of under-reporting, vaccine efficiency and social behavior on the post-pandemic spread using physics informed neural networks: A case study of China.

In late 2019, the emergence of COVID-19 in Wuhan, China, led to the implementation of stringent measures forming the zero-COVID policy aimed at eliminating transmission. Zero-COVID policy basically aimed at completely eliminating the transmission of COVID-19. However, the relaxation of this policy in late 2022 reportedly resulted in a rapid surge of COVID-19 cases. The aim of this work is to investigate the factors contributing to this outbreak using a new SEIR-type epidemic model with time-dependent level of immunity. Our model incorporates a time-dependent level of immunity considering vaccine doses administered and time-post-vaccination dependent vaccine efficacy. We find that vaccine efficacy plays a significant role in determining the outbreak size and maximum number of daily infected. Additionally, our model considers under-reporting in daily cases and deaths, revealing their combined effects on the outbreak magnitude. We also introduce a novel Physics Informed Neural Networks (PINNs) approach which is extremely useful in estimating critical parameters and helps in evaluating the predictive capability of our model.

The role of vaccine in COVID-19

The sudden outbreak of COVID-19 in Wuhan, China, has brought sudden harm to people. Under such circumstances, many vaccines have been invented and created, and all kinds of vaccines also carry their own advantages and disadvantages. It is essential for population to understand the working principle and basic production method of each vaccine. At present, there are many vaccines for the novel coronavirus epidemic, but there are three vaccines that mainly occupy the market. Recent study has found that adenovirus vaccine is effective to safe people from the virus, but it can give people some bad symptoms. mRNA vaccines can increase the immune system after a second or multiple doses, especially in people over 40 years-old. In the meantime, recombinant protein COVID-19 vaccine has a strong immune response with stability of the vaccine immunity. In this paper, the most basic principles and the lowest logic of these vaccines are introduced respectively. In addition, these vaccines are combined with some studies on clinical symptoms. This article also analyzes the shortcomings and benefits of these different vaccines, and this review will recommend methods to avoid infection based on the structure of all COVID-19 vaccines and pathogens.

COVID-19 detection and analysis from lung CT images using novel channel boosted CNNs.

In December 2019, the global pandemic COVID-19 in Wuhan, China, affected human life and the worldwide economy. Therefore, an efficient diagnostic system is required to control its spread. However, the automatic diagnostic system poses challenges with a limited amount of labeled data, minor contrast variation, and high structural similarity between infection and background. In this regard, a new two-phase deep convolutional neural network (CNN) based diagnostic system is proposed to detect minute irregularities and analyze COVID-19 infection. In the first phase, a novel SB-STM-BRNet CNN is developed, incorporating a new channel Squeezed and Boosted (SB) and dilated convolutional-based Split-Transform-Merge (STM) block to detect COVID-19 infected lung CT images. The new STM blocks performed multi-path region-smoothing and boundary operations, which helped to learn minor contrast variation and global COVID-19 specific patterns. Furthermore, the diverse boosted channels are achieved using the SB and Transfer Learning concepts in STM blocks to learn texture variation between COVID-19-specific and healthy images. In the second phase, COVID-19 infected images are provided to the novel COVID-CB-RESeg segmentation CNN to identify and analyze COVID-19 infectious regions. The proposed COVID-CB-RESeg methodically employed region-homogeneity and heterogeneity operations in each encoder-decoder block and boosted-decoder using auxiliary channels to simultaneously learn the low illumination and boundaries of the COVID-19 infected region. The proposed diagnostic system yields good performance in terms of accuracy: 98.21 %, F-score: 98.24%, Dice Similarity: 96.40 %, and IOU: 98.85 % for the COVID-19 infected region. The proposed diagnostic system would reduce the burden and strengthen the radiologist's decision for a fast and accurate COVID-19 diagnosis.

Loathsome Hui parasites: Islamophobia, ethnic chauvinism, and popular responses to the 2020 Wuhan coronavirus outbreak

ABSTRACT On 31 January 2020 in the midst of the outbreak of COVID-19 in Wuhan, China the city’s Party Secretary, Ma Guoqiang admitted in a televised interview to feeling “guilty and remorseful,” about the city government’s failures to contain the virus. In response, netizens on Weibo directed visceral abuse at Ma, an ethnic Hui Muslim, about his faith and loyalty to the party. The attacks came just months after the publication of leaked documents from national party officials calling Islam a “virus” and vowing to stop its “contagion.” Using discourse analysis of posts regarding Ma from January and February 2020, this paper examines how online discussion of Ma exemplifies Islamophobic attitudes of netizens and illuminate the exclusory ethnic politics that unfold in the process of national boundary setting in China. These findings will also illuminate how Muslims become scapegoats for crisis in non-Muslim countries, particularly those under authoritarian governance.

The published trend of studies on COVID-19 and diabetes: bibliometric analysis.

Since the COVID-19 pandemic outbreak, diabetes mellitus (DM) has been at the core of the confirmed risk factors for fatal or critical care unit-treated COVID-19 and COVID-19 related complications. Although relevant studies on DM have developed rapidly during the COVID-19 pandemic. However, the aforementioned research results have not been systematically quantified by means of bibliometric analysis. The purpose of this study is to provide a comprehensive analysis of the current status and trends of publications related to DM research during the COVID19 epidemic. A bibliometric analysis was performed using the Web of Science database. In this study, we used citespace, R software and R-Bibliometrix to analyze keywords, most-cited authors, most-cited countries, most-cited global documents, and co-occurrence and co-citation networks. A total of 1688 publications was included in this study. Investigators from the United States contributed the most publications. The United States, China and Europe have the most collaboration with the other countries/regions. A total of 3355 institutions made contributions to this study. Of the top 10 institutions with the most publications, N8 Research Partnership showed the most centrality. Among the top 10 journals, Diabetes Research and Clinical Practice published the most articles. Among authors included, Khunti Kamlesh is rated first with 27 papers and has the highest centrality. The most frequently co-cited article is entitled "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study". The most popular keywords included diabetes, mortality, diabetes, outcome, occurrences, risk, and type 1 diabetes. This bibliometric study provides an overall picture of DM research and research trends during the COVID-19 pandemic and provides a basis for researchers to develop their next research strategies.

Reflections of nurses in the fight against COVID-19 in Hubei: a qualitative study

ObjectivesTo explore the reflections and experiences of nurses who were deployed to the frontline to combat COVID-19 in Wuhan, China. In order to gain insights that can be useful in...

Dynamics of platelet-leukocyte aggregates in patients with coronavirus infection, depending on the duration and severity of the disease

The aim of our work was to trace the dynamics of the subspecies of leukocyte-platelet aggregates in patients with coronavirus disease, depending on the duration and severity of the disease. The study included 83 patients diagnosed with Coronavirus infection and treated at a hospital from June to August 2020 as well as 20 healthy volunteers. The Wuhan COVID-19 strain was identified in all patients. The groups studied were divided according to the duration of the disease and its severity. Analysis of the total number and phenotype of leukocytes, the number of leukocyte-platelet aggregates was performed with the Cytomics FC500 flow cytofluorimeter. Over the first week of COVID infection, the number of neutrophil-platelet coagulants increased. An increase in disease severity to moderate values is characterized by a decrease in the number of eosinophils and lymphocytes, and their cooperation with platelets accompanied with active cooperation of neutrophils and monocytes with blood plates.

Impact of Human Behavior According to Social Distance Rules During Covid-19 (Case Study Bukit Bintang - Kuala Lumpur)

SARS-CoV-2 was linked to COVID-19 in Wuhan, China, in December 2019. After confirmed cases and deaths in numerous countries, WHO proclaimed a global pandemic. During the outbreak, territorial public and private socializing spread the virus quickly with friends, families, and relatives. Hence, this research examines the effectiveness of social distance rules in preventing the spread of COVID-19 in Bukit Bintang, Malaysia, from the perspectives of residents and shopping mall visitors during the recovery Movement Control Order (RMCO period). This study examines space territoriality among Bukit Bintang's foreign workers and mall visitors using qualitative (structured observation) and quantitative (questionnaire) methodologies. Structured observations examine human behavior in uncontrolled (home, neighborhood) and controlled (shopping mall) situations. As part of the quantitative method, a questionnaire survey is utilized to learn about respondents' specific actions, such as personal and public space invasion. This study collects data by purposeful sampling and included 250 people. The study's findings confirm the association between numerous constructs, and indicates that the number of territories people occupy in private and public contexts tends to spread COVID-19 in Bukit Bintang, Malaysia. Social distancing drastically affects COVID-19's spread and number of deaths. According to the study, the virus spreads more when people ignore the social distance rule.

The Rise of Xenophobia and Nationalism in China Since the COVID Pandemic: Insights from Discourse Analysis

Since the successful containment of COVID-19 in Wuhan in late March 2020, China had implemented a nationwide highly stringent and restrictive zero-COVID policy to manage the pandemic until the sudden swift away from it in early December 2022. How did the Chinese Communist Party discursively construct it as a ‘normal’ and legitimate policy? Using interpretivism and poststructuralist political theory, this paper examines how Chinese political elites constructed a discourse of danger for the COVID pandemic, with the dominant discursive narratives full of xenophobic and nationalist languages. The discourse framed ‘foreigners’ as ‘threats’ to Chinese people’s health, advocated that China should rely on home-made vaccines and medicines and, more importantly, argued that the Chinese Communist rule demonstrates ‘institutional superiority’ over Western governance. This xenophobic and nationalist discourse has lingered on after the dismantling of the zero-COVID policy. There are grounds for us to concern whether China is seeking self-reliance rather than integrating itself with the world. A Chinese decoupling from the world—a nationalist self-reliance policy similar with that in the Mao era—is not unthinkable.

Assessing the impact of the COVID-19 pandemic on the performance of the Vietnam stock exchange: An empirical analysis

The emergence of COVID-19 in Wuhan, China, in December 2019 led to a global crisis with profound implications for public health and the global economy. This study investigates the ramifications of the pandemic on the Vietnam Stock Exchange, recognizing its interconnectedness with global financial markets. Despite the considerable speculation surrounding the pandemic's influence on economic and financial systems worldwide, limited empirical research has been conducted on its specific impact on the Vietnam Stock Exchange. Employing historical data spanning from January 30, 2020, to April 27, 2022, sourced from a secondary dataset, this research empirically explores the performance of the Vietnam Stock Exchange during the COVID-19 pandemic period compared to a normal period. The findings reveal a significant decline in stock returns and heightened volatility during the pandemic, signaling adverse effects on the exchange's performance. Furthermore, the study applies Quadratic GARCH (QGARCH) and Exponential GARCH (EGARCH) models, incorporating a dummy variable, to scrutinize stock returns. The results corroborate the pandemic's negative impact on stock returns in Vietnam. This research underscores the importance of implementing strategic political and economic policies, including maintaining a stable political environment, promoting indigenous enterprises, diversifying the economy, and adopting a flexible exchange rate regime. These measures are recommended to enhance the resilience of the financial market and attract new investors to the Ho Chi Minh Stock Exchange.

IMPLEMENTASI KEBIJAKAN PENANGGULANGAN PANDEMI COVID-19 TAHUN 2021 DI KELURAHAN WUNGU KECAMATAN WUNGU KABUPATEN MADIUN, PROVINSI JAWA TIMUR

The Covid-19 pandemic is a problem that highlights the attention of many people in various parts of the world. Since it was first noticed from patients infected with Covid-19 in Wuhan, Hubei Province, China on December 8, 2019, the virus has now spread to 216 countries. This pandemic has not only threatened human health, but has also affected the world economic downturn. The most affected sectors are aviation, transportation, hotels and restaurants. This uncertain situation will further aggravate global financial stability. The Village Government is at the forefront of tackling this pandemic. This research uses descriptive qualitative research methods. In accordance with the formulation of the problem and the purpose of this research, the focus in tackling Covid-19 and to measure the success of a policy implementation according to Edward III theory can be measured through four dimensions, namely: Communication, Resources, Disposition and Bureaucratic Structure.
 Keywords: Implementation, Countermeasures, Pandemic Covid-19

A real-world data validation of the value of early-stage SIR modelling to public health

Performance of Susceptible-Infected-Recovered (SIR) model in the early stage of a novel epidemic may be hindered by data availability. Additionally, the traditional SIR model may oversimplify the disease progress, and knowledge about the virus and transmission is limited early in the epidemic, resulting in a greater uncertainty of such modelling. We aimed to investigate the impact of model inputs on the early-stage SIR projection using COVID-19 as an illustration to evaluate the application of early infection models. We constructed a modified SIR model using discrete-time Markov chain to simulate daily epidemic dynamics and estimate the number of beds needed in Wuhan in the early stage of COVID-19 epidemic. We compared eight scenarios of SIR projection to the real-world data (RWD) and used root mean square error (RMSE) to assess model performance. According to the National Health Commission, the number of beds occupied in isolation wards and ICUs due to COVID-19 in Wuhan peaked at 37,746. In our model, as the epidemic developed, we observed an increasing daily new case rate, and decreasing daily removal rate and ICU rate. This change in rates contributed to the growth in the needs of bed in both isolation wards and ICUs. Assuming a 50% diagnosis rate and 70% public health efficacy, the model based on parameters estimated using data from the day reaching 3200 to the day reaching 6400 cases returned a lowest RMSE. This model predicted 22,613 beds needed in isolation ward and ICU as on the day of RWD peak. Very early SIR model predictions based on early cumulative case data initially underestimated the number of beds needed, but the RMSEs tended to decline as more updated data were used. Very-early-stage SIR model, although simple but convenient and relatively accurate, is a useful tool to provide decisive information for the public health system and predict the trend of an epidemic of novel infectious disease in the very early stage, thus, avoiding the issue of delay-decision and extra deaths.