Epidemic characteristics analysis of COVID-19 cluster in Huizhou, Guangdong

Objective To analyze the epidemiological characteristics of COVID-19 cluster epidemic in Huizhou from January to February in 2020, and we provide experience and reference for the prevention and control of cluster epidemic. Methods Descriptive epidemiology was used to analyze the clusters of COVID-19 in Huizhou city. Results From January to February in 2020, a total of 19 COVID-19 cluster outbreaks were reported in Huizhou. The most common cluster outbreaks were in Huidong county (8 cases), Boluo county (3 cases) and Huiyang district (3 cases). There were 59 cases involved in 19 outbreaks, among which 46 were confirmed cases, and 13 were asymptomatic infected. The sex ratio of male to female was 0.84: 1, the age was 1-85 years old. The 19 cases of outbreaks were all caused by imported cases, among which 13 cases were imported from Wuhan (68.4%), 3 cases were imported from Hubei province except Wuhan (15.8%), and 3 cases were imported from other provinces and cities (15.8%). There were 13 cases (68.4%) in the first generation, and 6 cases (31.6%) in the second generation. Events exposed place were variety, including 3 (15.8%) simple family exposure, 13 (68.4%) joint exposure, exposure family, 1 (5.26%) of the joint exposure, family exposure, family dinners, 1 (5.26%) of the joint exposure, family exposure, exposure (hotel) exposed in public places, 1 (5.26%) of the collective unit (workplace) exposure. Conclusion All the COVID - 19 cluster outbreaks in Huizhou city were caused by imported cases, most of which occurred in the family and were caused by families living together and eating together. As the number of people returning to work, production and school increases, various prevention and control measures should be implemented in key areas, key populations and key places to prevent the outbreak from rebounding.Copyright © China Tropical Medicine 2021.

Invulnerability analysis for airport weighted networks before and after COVID-19

In order to improve airport network ' s ability to cope with emergencies, topological characteristics of Chinese airport network before and after COVID-19 were analyzed based on complex network theory. And the network was weighted by using node strength, and an invulnerability assessment method was developed after identifying inflection points of loss fitting curves for weighted network characteristics metrics under different attack strategies. The results show that the topological structure of airport weighted network has no significant changes before and after the pandemic, but its connectivity is slightly sparse. And the airport network in China is much more vulnerable under different intentional attack strategies. When attack ratio reaches 8. 6%, inflection point of loss fitting curves will appear, and relative loss of global network efficiency will amount to 24. 39%, while reduction rate of the largest connected subgraph reaches 14. 67%, and relative loss of average degree and average clustering coefficient is up to 76. 87% and 68. 84%, respectively. Moreover, loss of network efficiency and the largest connected subgraph reduction rate accelerates after inflection points, in which stage the network will be paralyzed. © 2022 China Safety Science Journal. All rights reserved.

Expert consensus on diagnosing & treating pediatric surgical diseases during the epidemic period of COVID -19.

Ever since late December 2019, corona virus disease 2019 (COVID -19) has been reported in China. It presents a general trend of a global pandemic. By consulting the relevant Chinese government regulations and the latest publications of COVID -19, more than 20 pediatric surgical specialists from China formulated the Expert Consensus of COVID -19 Prevention and Control Protocol. Suitable for clinical practices, it provides recommendations for children's hospitals and pediatric surgical institutions at domestic and abroad.Copyright © 2020 by the Chinese Medical Association.

Infection control status of novel coronavirus pneumonia and radiation safety at CT workplace.

CT is an important imaging tool for the diagnosis of novel coronavirus pneumonia (COVID-19), therefore, it's necessary to strictly control the disinfection of CT workplace and equipment and biosafety to avoid the place from becoming a potential infection source and to reduce the risk of infection of patients and radiological staff. It is also necessary to reduce the CT scan dose to minimize the radiation hazards on patients under the premise of ensuring the CT image quality and diagnostic efficiency. Based on the survey that novel coronavirus residues after disinfection at some CT workplace in domestic and overseas and the application of low-dose CT scan in diagnosis of COVID-19, as well as the current situation of radiological protection management in emergency hospital, this paper summarizes and proposes suggestions on infection control and radiological protection for CT workplace to strengthen the defense line of COVID-19 prevention and control.Copyright © 2021 by the Chinese Medical Association.

Pathways, manifestations, and mechanisms of nerve injury in patients with COVID-19.

COVID-19 is the latest and most severe epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Besides the respiratory system, the effects of SARS-CoV-2 on central and peripheral nervous systems have been recognized by more and more people. Clinically, patients with COVID-19 have been reported from mild anosmia and hypoesthesia to acute necrotizing hemorrhagic encephalopathy and Guillain-Barre syndrome. In order to facilitate clinicians to recognize the nerve injury of COVID-19 patients and give timely treatment to these patients, this paper reviews the latest research progress on the possible pathways of nerve injury, clinical manifestations and pathogenesis of COVID-19 patients.Copyright © 2020 by the Chinese Medical Association.

Is the mRNA COVID-19 Vaccine Safe in Patients With a Prior History of Myocarditis?

BACKGROUND: Numerous studies have reported myocarditis resulting from messenger RNA (mRNA) coronavirus disease 2019 (COVID-19) vaccination. However, to date, there have been no reports highlighting the safety of mRNA COVID-19 vaccines in children and adults with a prior history of myocarditis, which was the intent of this study. METHODS AND RESULTS: Children and adults cared for at the Cleveland Clinic were identified through the electronic health records, who had a history of myocarditis before the COVID-19 pandemic and had subsequently received at least 2 doses of the mRNA COVID-19 vaccines (n = 34). Only 1 patient in this series had recurrence of myocarditis confirmed by cardiac magnetic resonance imaging after receiving the second dose. He was a White man who had his first episode of myocarditis at age 20 and was 27 years of age at the time of recurrence. He was hospitalized for 2 days with no need for cardiac support or reported arrhythmias and was stable at outpatient follow-up. CONCLUSIONS: In patients with an old history of non-COVID-19 myocarditis, the risk of recurrent myocarditis after receipt of mRNA COVID-19 vaccination is low, and when it occurs it seems to be self-limiting. Our study will be valuable to clinicians while discussing the risk-benefit ratio of vaccinations in patients with a prior history of myocarditis.

Outcomes of a "hospital at home” programme for the supervised home recovery of COVID-19 patients in Singapore

Background: The Singapore General Hospital COVID-19 Virtual Ward is a "hospital at home” (HaH) programme for the supervised home recovery of higher-acuity COVID-19 patients from the hospital and the community. Objective: To describe how an existing HaH programme was redesigned so that COVID-19 patients could be remotely monitored at home and report the outcomes of the first 100 patients in this Virtual Ward. Methods: Patients received an admission package comprising instructions and equipment for home monitoring, and uploaded their parameters into a clinical dashboard via a secure messaging app. Medical staff conducted video or telephone consultations daily. Patients were discharged according to time-based criteria, although some required SARS-CoV-2 PCR testing, which were conducted at home by a third-party medical provider. De-identified data of the first 100 patients were analysed by demographic details, indication for enrolment into the Virtual Ward, and the need for subsequent inpatient readmission. Results: Of the first 100 patients admitted into the Virtual Ward, 58 were female, mean age was 63.1 years old (23–95 years), and 76 were fully vaccinated. There were 77 hospital referrals and 23 community referrals. The number of days of inpatient hospitalisation avoided was 717 days (average of 7.9 days per patient). Three hospital referrals (3.9%) were readmitted, while seven community referrals (30.4%) required subsequent hospitalisation. Conclusion: The Virtual Ward programme demonstrates that selected COVID-19 patient can safely recover at home with remote medical support and monitoring, thereby expanding hospital capacity.

Design of Intelligent Medical Guidance Robot

The contactless service has become an important measure to avoid the spread of COVID-19 since its outbreak in 2020. Combining with the current epidemic situation and the epidemic prevention problems exposed by the present situation of outpatient service in hospitals and the analysis of their causes, this study applied the thinking and method of product design, and put forward an intelligent medical guide service robot design. By analyzing the user's actual outpatient demand, the functional modules of the robot are planned, and the corresponding hospital scene is established by using the open source simulation software Webots, which simulates the navigation function of the robot. The purpose of this study is to reduce the labor burden of medical staff, alleviate the contradiction of medical resources shortage, improve the quality of hospital outpatient service and build a new intelligent medical service platform. Meanwhile, it also provides relevant reference for the design of intelligent medical products. © 2022 The authors and IOS Press.

Bioinformatics analysis on structure and function and expression vector construction of SARS-CoV-2 related protein TMPRSS2

Aim Human TMPRSS2 is a transmembrane serine protease.In this paper, the structure and function of the protein were systematically analyzed by bioinformatics, the codon was optimized and the pro- karvotie expression vector was constructed to explore the molecular mechanism of SARS-CoV-2 infecting host cells.Methods The recombinant expression vector pET-22b-TMPRSS2 was generated by molecular cloning technology.The homology, functional sites, subcellular localization, three-dimensional structure and evolutionary characteristics of TMPRSS2 protein were systematically analyzed by using analytical tools such as Protparam, NetPhos3.1, Blast, Clustal X2 and MEGA7.0.Results The prokarvotic expression plas- mid was constructed correctly;TMPRSS2 belongs to medium molecular weight protein, which is composed of 492 amino acid residues.The theoretical isoelectric point is 8.12, the molecular extinction coefficient is 118 145 L * mol~1 * cm"1 , and the half-life is 30 h;TMPRSS2 has 15 potential glycosylation sites and 49 possible phosphorylation sites.It is a transmembrane hydrophilie protein without signal sequenee.In addition, the protein has 13 potential B-cell epitopes and 7 T-eell epitopes.Seeondarv structure analysis showed that random coil accounted for the highest proportion of TMPRSS2 protein ( 0.453 3) , followed by extended strand (0.252 0).Sequence comparison and evolutionary analysis showed that the highest sequence consistency and closest genetic relationship with human TMPRSS2 was Pan troglodytes, followed by gorilla.Conclusions Human-derived TMPRSS2 protein is ev- olutionarilv conserved and functionally important.Hie results of this study can help to reveal the structure and mechanism of action of TMPRSS2 protein, provide ideas for the diagnosis and treatment of COYID-19, and accelerate the research and development process of new drugs targeting TMPRSS2 protein. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

Accelerating Drug Discovery and Development: Translational Medicine in Combating the COVID-19 Pandemic

The world was struck by SARS-CoV-2 (COVID-19) unexpectedly at the end of 2019. The initial small-scale infection quickly turned into a pandemic that affected every corner of the world. In order to provide adequate treatment to the infected population and curb the spread of the virus, the world united as one in this unprecedented war of humans versus pathogens. Moreover, the world faces a greater challenge in the post-pandemic recovery and prevention of the next pandemic. In this chapter, we leveraged the principles of translational medicine to illustrate the fundamental discoveries and revolutionary technologies in virus detection clinical treatment, and vaccine development. The knowledge and experience garnered will undoubtedly impact and benefit the future of drug discovery and development. © 2022 John Wiley & Sons, Inc. All rights reserved.

Meeting the Challenges of Myocarditis: New Opportunities for Prevention, Detection, and Intervention-A Report from the 2021 National Heart, Lung, and Blood Institute Workshop.

The National Heart, Lung, and Blood Institute (NHLBI) convened a workshop of international experts to discuss new research opportunities for the prevention, detection, and intervention of myocarditis in May 2021. These experts reviewed the current state of science and identified key gaps and opportunities in basic, diagnostic, translational, and therapeutic frontiers to guide future research in myocarditis. In addition to addressing community-acquired myocarditis, the workshop also focused on emerging causes of myocarditis including immune checkpoint inhibitors and SARS-CoV-2 related myocardial injuries and considered the use of systems biology and artificial intelligence methodologies to define workflows to identify novel mechanisms of disease and new therapeutic targets. A new priority is the investigation of the relationship between social determinants of health (SDoH), including race and economic status, and inflammatory response and outcomes in myocarditis. The result is a proposal for the reclassification of myocarditis that integrates the latest knowledge of immunological pathogenesis to refine estimates of prognosis and target pathway-specific treatments.

Youth social innovation during the COVID-19 pandemic in the Philippines: a quantitative and qualitative descriptive analyses from a crowdsourcing open call and online hackathon

Introduction Young people have played a pivotal role as part of the COVID-19 response, including developing health messages and social innovations. Social innovation in health engages multiple stakeholders in linking social change and health improvement. The study examined the feasibility of youth ideas and innovations to address the impacts of the COVID-19 pandemic using quantitative and qualitative descriptive analyses. Methods In partnership with the WHO, academic institutions, youth organisations and civil society groups, we conducted a crowdsourcing open call among Filipino youth (15-30 years old) using a structured Special Programme for Research and Training in Tropical Diseases/Social Innovation in Health Initiative process. The open call had three categories: youth voices to cocreate the post-COVID-19 world (entries were texts, images, videos and music), youth-led COVID-19 social innovations, and youth-led social innovations not related to COVID-19. Each submission was evaluated by three independent judges. Finalists were selected in each of the categories alongside four grand winners. All finalists were invited to attend a 1 day online civic hackathon. Results We received a total of 113 entries (youth voices to cocreate the post-COVID world=76;youth-led COVID-19 social innovations=17;youth-led social innovations not related to COVID-19=20). Twelve entries focused on youth mental health during the pandemic. The online hackathon provided the participants mentorship for further development of their ideas. Finalists were able to produce draft health communication campaigns and improved social innovations. Conclusion Many Filipino youth created exceptional entries in response to the open call. This suggests the feasibility of including youth voices in strategic planning processes. A global youth social innovation call is recommended.

Multi-label topic classification for COVID-19 literature annotation: A BioBERT-based feature enhancement approach

With the rapid expansion and exponential growth of biomedical literatures, especially in the current environment of COVID-19 pandemic, it is urgent to explore an effective technology to automatically manage and categorize massive information for biomedical texts. The wide application and powerful performance of BERT have shown promising results in the field of natural language processing. Thus, we first choose the improved pre-trained language models CovidBERT and BioBERT as the basis, from the best performance of which further enhances semantic representation of with extra title information. Finally, a novel feature enhancement method is proposed to exploit and integrate the distribution of label information effectively. The experimental results show that our model achieves an instance-based F1 score, precision and recall of 93.94%, 93.5% and 94.38% in the task of multi-label topic classification from track 5 BioCreative VII. © VDE VERLAG GMBH - Berlin - Offenbach.

Orally delivered perilla (Perilla frutescens) leaf extract effectively inhibits SARS-CoV-2 infection in a Syrian hamster model

On analyzing the results of cell-based assays, we have previously shown that perilla (Perilla frutescens) leaf extract (PLE), a food supplement and orally deliverable traditional Chinese medicine approved by the Taiwan Food and Drug Administration, effectively inhibits SARS-CoV-2 by directly targeting virions. PLE was also found to modulate virus-induced cytokine expression levels. In this study, we explored the anti-SARS-CoV-2 activity of PLE in a hamster model by examining viral loads and virus-induced immunopathology in lung tissues. Experimental animals were intranasally challenged with different SARS-CoV-2 doses. Jugular blood samples and lung tissue specimens were obtained in the acute disease stage (3-4 post-infection days). As expected, SARS-CoV-2 induced lung inflammation and hemorrhagic effusions in the alveoli and perivascular areas;additionally, it increased the expression of several immune markers of lung injury - including lung Ki67-positive cells, Iba-1-positive macrophages, and myeloperoxidase-positive neutrophils. Virus-induced lung alterations were significantly attenuated by orally administered PLE. In addition, pretreatment of hamsters with PLE significantly reduced viral loads and immune marker expression. A purified active fraction of PLE was found to confer higher antiviral protection. Notably, PLE prevented SARS-CoV-2-induced increase in serum markers of liver and kidney function as well as the decrease in serum high-density lipoprotein and total cholesterol levels in a dose-dependent fashion. Differently from lung pathology, monitoring of serum biomarkers in Syrian hamsters may allow a more humane assessment of the novel drugs with potential anti-SARS-CoV-2 activity. Our results expand prior research by confirming that PLE may exert an in vivo therapeutic activity against SARS-CoV-2 by attenuating viral loads and lung tissue inflammation, which may pave the way for future clinical applications.

Research on the Impact of COVID-19 on Import and Export Strategies

Due to the spread of COVID-19, the public health crisis is bound to have a huge impact on the world economy and international trade. How to study the import and export strategies under the coronavirus pandemic has become a major issue that many scholars need to solve urgently. Therefore, a two-stage game model is constructed, and the reverse solution method is used to obtain the optimal output of enterprises in importing countries and exporting countries before and after the outbreak of pandemic, as well as the optimal subsidies for enterprises from exporting countries and the optimal import quarantine rate for importing countries. Based on the game between the two countries without the pandemic outbreak, the impact of the pandemic on the output, profits, and social welfare of enterprises in the two countries was compared. Enterprises in exporting countries face double threats from the pandemic and import quarantine fees. The increase in import quarantine fees reduces the social welfare of exporting countries. In order to effectively control the spread of the pandemic, subsidies are an effective means to restore exports to normal. Reasonable collection of import quarantine fees by importing countries can promote bilateral trade, but an excessive collection will be counterproductive. The governments of exporting countries should establish emergency mechanisms and relevant subsidy policies, and enterprises should continuously improve their competitiveness. At the same time, countries should abandon the concept of trade protection and negotiate and cooperate to jointly deal with the pandemic.

Perception of Online Teaching and Learning (T&L) Activities Among Postgraduate Students in Faculty of Health Sciences, Universiti Kebangsaan Malaysia (UKM)

The COVID-19 pandemic has changed the landscape of teaching pedagogies, assessment methods, supervision, and student engagement in higher education institutions. Exploration of students’ perception on online teaching and learning (T&L) in terms of their level of satisfaction is an important core indicator of their acceptance to enhance the long-term impact of the online (T&L) activities. The objective of the study is to determine the level of satisfaction of online (T&L) activities and its involved technical support among postgraduate students in the Faculty of Health Sciences, Universiti Kebangsaan Malaysia (UKM). A validated questionnaire was used to conduct the survey. A total of 81 postgraduate students were recruited using purposive sampling in the study. Results showed that more than 86% of the students were satisfied with the online T&L activities except for two areas where 50% of the students felt that the curriculum structure design was too heavy and they felt stressed after attending the first online class and examination. On the other hand, more than 70% of the students were satisfied with the technical support for the online T&L. Although the satisfaction level for both was high, there was no association between them, χ2 (1, N = 162) = 3.8, p = 0.42. In conclusion, the postgraduate students of the Faculty of Health Sciences, UKM are satisfied with the online T&L process, which implies a good reception. A review of curriculum structure and design that considers the psychological and behavior changes among students during online T&L is also recommended for the online T&L continues to be effective in the future. Copyright © 2022 Ghazali, Zainodin, Madhavan, Gnanasundram, Nisar, Abd Rashid, Muniandy and Tang.

DistCare: Distilling Knowledge from Publicly Available Online EMR Data to Emerging Epidemic for Prognosis

Due to the characteristics of COVID-19, the epidemic develops rapidly and overwhelms health service systems worldwide. Many patients suffer from life-threatening systemic problems and need to be carefully monitored in ICUs. An intelligent prognosis can help physicians take an early intervention, prevent adverse outcomes, and optimize the medical resource allocation, which is urgently needed, especially in this ongoing global pandemic crisis. However, in the early stage of the epidemic outbreak, the data available for analysis is limited due to the lack of effective diagnostic mechanisms, the rarity of the cases, and privacy concerns. In this paper, we propose a distilled transfer learning framework, DistCare, which leverages the existing publicly available online Electronic Medical Records to enhance the prognosis for inpatients with emerging infectious diseases. It learns to embed the COVID-19-related medical features based on massive existing EMR data. The transferred parameters are further trained to imitate the teacher model's representation based on distillation, which embeds the health status more comprehensively on the source dataset. We conduct Length-of-Stay prediction experiments for patients in ICUs on real-world COVID-19 datasets. The experiment results indicate that our proposed model consistently outperforms competitive baseline methods. In order to further verify the scalability of DistCare to deal with different clinical tasks on different EMR datasets, we conduct an additional mortality prediction experiment on End-Stage Renal Disease datasets. The extensive experiments demonstrate that DistCare can benefit the prognosis for emerging pandemics and other diseases with limited EMR.