A Novel Design of COVID-19 Vaccine with High Effectiveness and Popularization

In December 2019, a virus named SARS-CoV-2 broke out in Wuhan in China. The spread of the virus has brought great challenges to the global medical system. At present, over 6 million people died of the diseases caused by the virus. Under these situations, various corresponding vaccines such as Oxford, Pfizer, and Moderna vaccines have been developed and applied to the population. Nevertheless, due to the development of variants of the virus such as Delta and Omicron, there has been a decline in the effectiveness of current vaccines to some extent. Moreover, the proportion of people who have been inoculated with the COVID-19 vaccine in low-income countries is less than 20%. In this case, we designed a new vaccine to deal with these problems. Specifically, we utilized the antigens (RBD, HR1, and HR2) of the virus to cope with its potential variants of it, increasing the effectiveness of the vaccine. Moreover, we designed a new cell expression system to increase the efficiency of vaccine production by using CHO cells as host cells, Neo gene as a selective marker, CMV as a promoter, MBP as affinity tag, and β-globin as a terminator. Eventually, it was worth stating that our designed vaccine was hypothesized to be practicable and functional, it just started one step on the way to tackling the variants of this virus and increasing the productivity of the vaccine. The detailed experiments still needed to be implemented to verify the feasibility of our design. © 2023 SPIE.

How Severe is Your COVID-19? Predicting SARS-CoV-2 Infection with Graph Attention Capsule Networks

Recent studies in machine learning have demonstrated the effectiveness of applying graph neural networks (GNNs) to single-cell RNA sequencing (scRNA-seq) data to predict COVID-19 disease states. In this study, we propose a graph attention capsule network (GACapNet) which extracts and fuses Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transcriptomic patterns to improve node classification performance on cells and genes. Significantly different from the existing GNN approaches, we innovatively incorporate a capsule layer with dynamic routing into our model architecture to combine and fuse gene features effectively and to allow those more prominent gene features present in the output. We evaluate our GACapNet model on two scRNA-seq datasets, and the experimental results show that our GACapNet model significantly outperforms state-of-the-art baseline models. Therefore, our study demonstrates the capability of advanced machine learning models to generate predictive features and evolutionary patterns of the SARS-CoV-2 pathogen, and the applicability of closing knowledge gaps in the pathogenesis and recovery of COVID-19. © 2022 IEEE.

The Clash between CLIL and TELL: Effects and Potential Solutions of Adapting TELL for Online CLIL Teaching

The relationship between technology and society is an ever-changing dynamic, but one in which education is a key domain. In educational practice, the use of computer technology has increasingly become an inseparable part of teaching students in numerous ways across the world. The COVID-19 global pandemic accelerated this dramatically, with online teaching environments becoming the sole way for students to access education for extended periods of time. This shift to online teaching also required that teachers learn new skills and deal with new challenges. Based on mixed-methods research conducted with 20 teachers from an established content and language integrated learning school in mainland China, this research paper investigates the different challenges and problems that were faced by content and language integrated learning teachers in their experiences of online teaching and, in tandem with wider content and language integrated learning and technology-enhanced language learning literature, develops some potential solutions for future use. © 2023 by the authors.

Specific mining of COVID-19 reviews using deep learning methods

Sentiment classification is a valid measure to monitor public opinion on the COVID-19 epidemic. This study provides a significant basis for preventing the spread of adverse public opinion. Firstly, in epidemic texts, we use a convolutional neural network and bidirectional long short-term memory neural network BiLSTM model to classify and analyze the sentiment of the comment texts about the epidemic situation on Weibo. Secondly, embedded in the model layer to generate adversarial samples and extract semantics. Then, semantic information is weighted using the attention mechanism. Finally, the RMS optimizer is used to update the neural network weights iteratively. According to comparative experiments, the experimental results show that such four evaluation metrics as accuracy, precision, recall, and f1-score with our proposed model have obtained better classification performance. © 2022 IEEE.

The impact of institutional management on teacher entrepreneurship competency: The mediating role of entrepreneurial behaviour

Although COVID-19 is far away, the impact of the pandemic on the management of higher education remains. Within the field of entrepreneurship education research, the influence of institutional management on teacher entrepreneurship competency (TEC) has attracted more attention as they are considered one of the key engines of economic recovery. Using quantitative research as well as SEM, a total of 1241 entrepreneurship education faculty members at China's double first-class universities were surveyed using a questionnaire. The results suggest that entrepreneurship group management (EGM) and mechanism protection (EMP) in institutions have a positive predictive effect on TEC, while a partial mediating effect exists after considering teacher entrepreneurial behaviours (TEB) (including Teacher's behaviour of innovation and autonomy (BIA) and resource seeking and management (BSM)). Overall, the management of entrepreneurship education in Chinese universities has a good effect on the development of TEC. Thus, the application of tripartite interaction theory in entrepreneurship education institutions provides a good reference for the personal sustainable development of entrepreneurship teachers. The significance of institutional management for teachers should shift from the traditional provision of work to professional development and growth. © 2023 The Authors

Synthesis and enzymatic inhibition effects of thiazolidinedione 3C-like protease inhibitors

The 3C-like protease (also known as Mpro) plays a key role in SARS-CoV-2 replication and has similar substrates across mutant coronaviruses, making it an ideal drug target. We synthesized 19 thiazolidinedione derivatives via the Knoevenagel condensations and Mitsunobu reactions as potential 3C-like protease inhibitors. The activity of these inhibitors is screened in vitro by employing the enzymatic screening model of 3C-like protease using fluorescence resonance energy transfer. Dithiothreitol is included in the enzymatic reaction system to avoid non-specific enzymatic inhibition. Active inhibitors with diverse activity are found in this series of compounds, and two representative inhibitors with potent inhibitory activity are highlighted. © The Author(s) 2023.

Geospatial Network Analysis and Origin-Destination Clustering of Bike-Sharing Activities during the COVID-19 Pandemic

Bike-sharing data are an important data source to study urban mobility in the context of the coronavirus disease 2019 (COVID-19). However, studies that focus on different bike-sharing activities including both riding and rebalancing are sparse. This limits the comprehensiveness of the analysis of the impact of the pandemic on bike-sharing. In this study, we combine geospatial network analysis and origin-destination (OD) clustering methods to explore the spatiotemporal change patterns hidden in the bike-sharing data during the pandemic. Different from previous research that mostly focuses on the analysis of riding behaviors, we also extract and analyze the rebalancing data of a bike-sharing system. In this study, we propose a framework including three components: (1) a geospatial network analysis component for a statistical and spatiotemporal description of the overall riding flows and behaviors, (2) an origin-destination clustering component that compensates the network analysis by identifying large flow groups in which individual edges start from and end at nearby stations, and (3) a rebalancing data analysis component for the understanding of the rebalancing patterns during the pandemic. We test our framework using bike-sharing data collected in New York City. The results show that the spatial distribution of the main riding flows changed significantly in the pandemic compared to pre-pandemic time. For example, many riding trips seemed to expand the purposes of riding for work-home commuting to more leisure activities. Furthermore, we found that the changes in the riding flow patterns led to changes in the spatiotemporal distributions of bike rebalancing, such as the shifting of the rebalancing peak time and the increased ratio between the number of rebalancing and the total number of rides. Policy implications are also discussed based on our findings.

KSMDB: A classification method in imbalanced COVID dataset based on KmeansSMOTE and DeBERT

2022 is already the third year of the COVID-19 outbreak, and public opinion information about the outbreak has always been at the forefront of hot searches. The imbalance problem prevalent in many reviews of COVID-19 causes classification models to favor most categories in training and prediction process, resulting in low accuracy of small sample classification data generated by imbalanced data sets. Therefore, it is suggested here that the text classification model is based on the combination of the KMeansSMOTE method combined with DeBERT. First of all, during data processing, the KmeansSMOTE algorithm is utilized to oversample the imbalance of the COVID dataset, which increases the classification accuracy of the model. Besides, we put a stacked denoising bidirectional transformer encoder (DeBERT) to use, a more and richer hidden feature vector is extracted by adding an embedded layer after the input tag, and the noise data is reconstructed to solve the noise problem in the process of raw data existence and oversampling. Furthermore, on the basis of model training, overfitting can be alleviated by adopting an early stopping strategy. A world of experiments using the COVID dataset demonstrates the effectiveness of the proposed method for solving simple imbalance and noise problems. With an overall accuracy of 87%, which improves the classification effect of minority samples and provides a new feasible method for the war of epidemic prevention. © 2022 IEEE.

Health Journalists' Social Media Sourcing During the Early Outbreak of the Public Health Emergency

Although journalists' social media sourcing can empower non-elite sources and diversify public discussions, counterarguments maintain that social media sourcing relies on a small group of elites and reinforces social division. To contribute to that debate, we examined how health journalists from the mainstream news organizations in the U.S. used Twitter's @mention for sourcing during the first three months of the COVID-19 outbreak. Using a sample of public Twitter posts published by the journalists, we formed co-@mentioned networks (i.e., two sources were connected if @mentioned in the same post) to examine the structure of the networks and identify important sourcing informants. Among the results, elite sources (e.g., health journalists and health experts in the public sector) and influential users (i.e., verified users with a large number of followers and who post frequently) dominated the sourcing repertoire. Moreover, the networks were fragmented because the sources were clustered into several close-knit subgroups. Analyzing exponential random graph models to examine the formation mechanism of the networks revealed that, as the pandemic's severity increased, influential users played a more salient role in the sourcing repertoire, and a homogeneous cluster consisting of journalists and news organizations emerged.

[Analysis of common viral infection in surveillance cases of febrile respiratory syndrome in 9 provinces of China from 2009 to 2021].

Objective: To understand the common viral infection among the surveillance cases of fever respiratory syndrome (FRS) in nine provinces in China. Methods: The research data were obtained from nine provinces (Anhui, Beijing, Guangdong, Hebei, Hunan, Jilin, Shandong, Shaanxi and Xinjiang) in the "Infectious Disease Surveillance Technology Platform Information Management System" of the Chinese Center for Disease Control and Prevention from January 2009 to June 2021. Finally, 8 243 FRS cases with nucleic acid detection results of eight viruses [human influenza virus (HIFV), human respiratory syncytial virus (HRSV), human adenovirus (HAdV), human parainfluenza virus (HPIV), human rhinovirus (HRV), human metapneumovirus (HMPV), human coronavirus (HCoV) and human Boca virus (HBoV)] were included in the study. The χ2 test/Fisher exact probability method was used to analyze the difference of virus detection rate in different age groups, regions and seasons. Results The M (Q1, Q3) age of 8 243 FRS cases was 4 (1, 18) years old, and 56.56% (4 662 cases) were children under 5 years old. Males accounted for 58.1% (4 792 cases) of all cases. All cases were from outpatient/emergency department (2 043 cases) and inpatient department (6 200 cases). The virus detection rates of FRS cases from high to low were HRSV, HIFV, HPIV, HRV, HAdV, HMPV, HCoV and HBoV. Two or more viruses were detected simultaneously in 524 cases, accounting for 15.66% of virus-positive cases. The difference of the virus detection rate in different age groups was statistically significant (all P values<0.05), and the virus detection rate in children<5 years old was higher (49.96%). The positive rate of any virus in south China was higher than that in north China (P<0.001). The virus-positive FRS cases were detected throughout the year. The detection rate of HRSV was higher in autumn and winter. The detection rate of HIFV was higher in winter. The detection rate of HMPV was higher in winter and spring. The detection rates of HPIV, HRV, HCoV and HBoV were higher in summer and autumn, while there was no significant difference in the detection rate of HAdV in different seasons. Compared with 2009-2019, the detection rate of any virus in 2020-2021 decreased from 41.37% to 37.86%. The detection rate of HIFV decreased sharply from 10.62% to 1.37%. The detection rate of HPIV decreased from 8.24% to 5.88%. The detection rate of HRV and HBoV increased from 5.43% and 1.79% to 9.67% and 3.19%, respectively. Conclusion: HRSV and HIFV infections are more common among FRS cases in nine provinces in China from 2009 to 2021, and the epidemiological characteristics of eight common respiratory viruses vary in different age groups, regions and seasons.

OPTIMIZING COVID-19 VACCINE DIFFUSION IN RESPIRATORY MUCOSA THROUGH STOKES-EINSTEIN MODELING

SARS-COV-2 vaccines, all of which are currently intramuscular shots, have the ability to prevent serious injury. However, the absence of sufficient mucosal immunity is a major concern. To counteract this deficiency that has led to continued transmission from vaccinated individuals and breakthrough cases, reformulating vaccines to be inhalable presents a logical administration route. Predecessor research has reported the inhalable route to be viable as aerosolized vaccine nanoparticles, AAV phage nanoparticles, and PIV-5 viruses were recently identified to elicit immune responses. In this study, the diffusion of vaccine nanoparticles across the mucosa is characterized and modeled, with respect to their observed behavior from previous studies in relation to the Stokes-Einstein equation, to predict the most efficient model of an inhalable COVID-19 vaccine. The Stokes-Einstein equation has been used in several studies to predict diffusion coefficients. These predictions may be modified to fit the specifications of mucosal interactions. It was determined that mucosal interactions play a significant role in vaccine nanoparticle diffusion, as demonstrated by the viral vector and virus-like nanoparticle diffusion, and can be characterized by an equivalent hydrodynamic radius. Moreover, as a counter to mucosal interactions, PEGylation was found to drastically decrease the viscous slowing of the mucus medium. © 2022 by ASME

Toward dialogue through a holistic measuring framework – the impact of social media on risk communication in the COVID-19

Purpose: Despite the huge potential of social media, its functionality and impact for enhanced risk communication remain unclear. Drawing on dialogic theory by integrating both “speak from power” and “speak to power” measurements, the article aims to propose a systematic framework to address this issue. Design/methodology/approach: The impact of social media on risk communication is measured by the correlation between “speak from power” and “speak to power” levels, where the former primarily spoke to two facets of the risk communication process – rapidness and attentiveness, and the latter was benchmarked against popularity and commitment. The framework was empirically validated with data relating to coronavirus disease (COVID-19) risk communication in 25,024 selected posts on 17 official provincial Weibo accounts in China. Findings: The analysis results suggest the relationship between the “speak from power” and “speak to power” is mixed rather than causality, which confirms that neither the outcome-centric nor the process-centric method alone can render a full picture of government–public interconnectivity. Besides, the proposed interconnectivity matrix reveals that two provinces have evidenced the formation of government–public mutuality, which provides empirical evidence that dialogic relationships could exist in social media during risk communication. Originality/value: The authors' study proposed a prototype framework that underlines the need that the impact of social media on risk communication should and must be assessed through a combination of process and outcome or interconnectivity. The authors further divide the impact of social media on risk communication into dialogue enabler, “speak from power” booster, “speak to power” channel and mass media alternative. © 2021, Emerald Publishing Limited.

Infectious Disease Prevention and Control Capacity of Community Health Institutions in Beijing: Current Status and Recommendations for Problems

Background: During the fight against the COVID-19 pandemic, Beijing's community health institutions showed some weaknesses in infectious disease prevention and control. To improve their capabilities in this aspect to fully play their role as a sentinel for monitoring infectious diseases, it is urgent to investigate and analyze their current status to find problems, then put forward recommendations. Objective: To investigate the infectious disease prevention and control level in Beijing's community health institutions, and identify and analyze the problems, with suggestions put forward. Methods: From May to July 2020, a questionnaire survey was conducted in all community health centers(CHCs) in Beijing. Information was collected, including the basic situation, departments, staff structure, infrastructure situation, the provision of public health services, and emergency response capacity for infectious diseases and public health emergencies of the CHC, and was analyzed using descriptive analysis. The above-mentioned data were checked and supplemented if necessary in accordance with the information in the China's National COVID-19 Surveillance Network and Beijing Community Health Statistics 2019. Results: Of the 342 CHCs in total in Beijing as of 2019, 90(26.32%) had a fever clinic, 102(29.82%) had a gastrointestinal clinic, and 54(15.79%) had both a fever clinic and a gastrointestinal clinic. Among the incumbent workers in the CHCs(n=28 809), 2 887(10.02%) held a position in public health, and 178(6.17%) had a senior professional title. HIV testing was carried out in 159 CHCs(46.49%). SARS-CoV-2 nucleic acid testing was accessible in 11 CHCs(3.22%). For 29 kinds of common infectious diseases, 140(40.94%) CHCs had no diagnosis and treatment capabilities, 135(39.47%) had capabilities managing 1-5 kinds, only 29(8.48%) were able to diagnose and treat >10 kinds. Conclusion: The CHCs in Beijing may have a series of problems in the infectious disease prevention and control system and mechanism, sentinel fever clinic, infectious disease diagnosis and treatment capacity, public health workforce development and other aspects. Therefore, the infectious disease prevention and control plan of the CHCs should be developed more appropriately from an overall point of view, to address the problems and improve the current status as soon as possible. Copyright © 2021 by the Chinese General Practice.

Summary of perioperative analgesia and sedation management of 19 lung transplant recipients

Objective: To summarize and explore the management experience of postoperative analgesia and sedation in lung transplant recipients. Methods: A total of 19 cases of lung transplantation were performed in Renmin Hospital of Wuhan University from December 2016 to December 2020, and all of them were transferred back to intensive care unit after surgery, the clinical data were retrospectively analyzed. Results: Among the 19 patients, the main diagnoses were chronic obstructive pulmonary disease in 5 cases, idiopathic pulmonary fibrosis in 6 cases, bronchiectasis in 2 cases, pneumoconiosis in 4 cases, Kartagener syndrome in 1 case and COVID-19 pneumonia with advanced pulmonary fibrosis in 1 case. There were 12 cases of double lung transplantation, and 7 cases of unilateral lung transplantation in (4 cases of left single lung transplantation and 3 cases of right single lung transplantation). Nine patients used ECMO to complete the operation, and 5 cases took ECMO back to the intensive care unit. All patients were treated with opioid analgesia, mainly sufentanil at a dose of 0.2-0.3 μg/(kg•h), midazolam and propofol are mainly used as sedatives at doses of 0.02-0.1 mg/(kg•h) and 0.3-0.4 mg/(kg•h), respectively, and the Richmond agitation sedation scale was -3.01±1.32 within 24 hours after operation. The main postoperative adverse events were delirium (1 case) and respiratory depression (1 case). There were 6 deaths during the perioperative period. One case died of multi-drug resistant bacteria infection, 1 case died of circulatory failure caused by active thoracic hemorrhage post-operation, the third case died of intraoperative cardiac arrest, and the other 3 cases were given up because of multiple organs failure. Conclusion: Analgesia and sedation is an important treatment for patients after lung transplantation. Choosing the depth of sedation according to the functional state of organs of lung transplant recipients and implementing the sedation strategy aiming at organ function protection is helpful to maintain the stability of cardiopulmonary function after lung transplantation. © 2021, Editorial Board of Medical Journal of Wuhan University. All right reserved.

Investigation and analysis of the mental pressure of outpatient medical attendants and nurses during the COVID-19 pandemic in china

Certain sicknesses or contaminations influence an enormous number of individuals in a limited capacity to focus time. A neighbourhood endemic illness can flare-up into a scourge influencing the entire populace or district which on occasion reach out to different nations and mainlands and become pandemic. Pandemics brings about death toll just like the economy. Pooled endeavors and assets, compelling sharing of information, equal numerous methodologies just as the physical and mental condition of forefront staff impact the board of pandemics. The COVID illness COVID-19 brought about by SARS-CoV-2 began in Dec 2019 from Wuhan in China, is currently an overall general wellbeing crisis influencing a huge number of people. It influences numerous cutting edge medical care laborers as well. Here, we contemplated mental pressure and proficient personality of Nurses and Staff for potential relationships, assuming any, and break down affecting elements. We utilized a purposive testing method with 415 Nurses and Staff in Nanjing, China through an overall data poll, seen pressure scale, and nursing proficient personality survey. Attendants and Staff' inception, month to month everyday costs, and their insight on plague counteraction and treatment have indicated a critical effect on their mental pressure (P< 0.010). Essentially, Nurse's and Staff's sexual orientation, inception, clinical practices, and information on counteraction and treatment, and whether they effectively learn such information sway altogether on their expert personality (P< 0.010). The general score of mental pressure were (24.470 +/- 07.350) and proficient personality had 72.470 +/- 08.070. The pressure condition showed a negative connection with the level of expert character (P< 0.01, r = -00.457). Expanded mental pressure, had a lower feeling of expert personality. Generally speaking, the examination of information on saw pressure and expert character pandemic proposes that feelings of anxiety are contrarily relative to information in compelling methods of taking care of the pandemic. Attendants and Staff with clinical practice fared better as far as expert character. The examination proposes Nurses and Staff to remain zeroed in on investigations, clinical practice, and directing, whenever required.

[Investigation of pathogenic agents causing acute respiratory tract infections in pediatric patients in a children's hospital assigned for case screening in Beijing during the outbreak of COVID-19].

Objective: To investigate the spectrum of pathogenic agents in pediatric patients with acute respiratory infections (ARI) during the outbreak of coronavirus infectious diseases 2019 (COVID-19). Methods: Three groups of children were enrolled into the prospective study during January 20 to February 20, 2020 from Capital Institute of Pediatrics, including children in the exposed group with ARI and epidemiological history associated with COVID-19 from whom both pharyngeal and nasopharyngeal swabs were collected, children in the ARI group without COVID-19 associated epidemiological history and children in the screening group for hospital admission, with neither COVID-19 associated epidemiological history nor ARI. Only nasopharyngeal swabs were collected in the ARI group and screening group. Each group is expected to include at least 30 cases. All specimens were tested for 2019-nCoV nucleic acid by two diagnostic kits from different manufacturers. All nasopharyngeal swabs were tested for multiple respiratory pathogens, whilst the results from the ARI group were compared with that in the correspondence periods of 2019 and 2018 used by t or χ(2) test. Results: A total of 244 children were enrolled into three groups, including 139 males and 105 females, the age was (5±4) years. The test of 2019-nCoV nucleic acid were negative in all children, and high positive rates of pathogens were detected in exposed (69.4%, 25/36) and ARI (55.3%, 73/132) groups, with the highest positive rate for mycoplasma pneumoniae (MP) (19.4%, 7/36 and 17.4%, 23/132, respectively), followed by human metapneumovirus (hMPV) (16.7%, 6/36 and 9.8%, 13/132, respectively). The positive rate (11.8%, 9/76) of pathogens in the screening group was low. In the same period of 2019, the positive rate of pathogens was 83.7% (77/92), with the highest rates for respiratory syncytial virus (RSV) A (29.3%, 27/92), followed by influenza virus (Flu) A (H1N1) (19.6%, 18/92) and adenovirus (ADV) (14.1%, 13/92), which showed significant difference with the positive rates of the three viruses in 2020 (RSV A: χ(2)=27.346, P<0.01; FluA (H1N1): χ(2)=28.083, P<0.01; ADV: χ(2)=7.848, P=0.005) . In 2018, the positive rate of pathogens was 61.0% (50/82), with the highest rate for human bocavirus (HBoV) (13.4%, 11/82) and followed by ADV (11.0%, 9/82), and significant difference was shown in the positive rate of HBoV with that in 2020 (χ(2)=6.776, P=0.009). Conclusions: The infection rate of 2019-nCoV is low among children in Beijing with no family clustering or no close contact, even with epidemiological history. The spectrum of pathogens of ARI in children during the research period is quite different from that in the previous years when the viral infections were dominant. MP is the highest positively detected one among the main pathogens during the outbreak of COVID-19 in Beijing where there is no main outbreak area.

[Recommendations for the treatment of severe coronavirus disease 2019 based on critical care ultrasound].

Severe patients with coronaviras disease 2019 (COVID-19) are characterized by persistent lung damage, causing respiratory failure, secondary circulatory changes and multiple organ dysfunction after virus invasion. Because of its dynamic, real-time, non-invasive, repeatable and other advantages, critical ultrasonography can be widely used in the diagnosis, assessment and guidance of treatment for severe patients. Based on the recommendations of critical care experts from all over the country who fight against the epidemic in Wuhan, this article summarizes the guidelines for the treatment of COVID-19 based on critical ultrasonography, hoping to provide help for the treatment of severe patients. The recommendations mainly cover the following aspects: (1) lung ultrasound in patients with COVID-19 is mainly manifested by thickened and irregular pleural lines, different types of B-lines, shred signs, and other consolidation like dynamic air bronchogram; (2) Echocardiography may show right heart dysfunction, diffuse cardiac function enhancement, stress cardiomyopathy, diffuse cardiac depression and other multiple abnormalities; (3) Critical ultrasonography helps with initiating early treatment in the suspect patient, screening confirmed patients after intensive care unit admission, early assessment of sudden critical events, rapid grading assessment and treatment based on it; (4) Critical ultrasonography helps to quickly screen for the etiology of respiratory failure in patients with COVID-19, make oxygen therapeutic strategy, guide the implementation of lung protective ventilation, graded management and precise off-ventilator; (5) Critical ultrasonography is helpful for assessing the circulatory status of patients with COVID-19, finding chronic cardiopulmonary diseases and guiding extracorporeal membrane oxygenation management; (6) Critical ultrasonography contributes to the management of organs besides based on cardiopulmonary oxygen transport; (7) Critical ultrasonography can help to improve the success of operation; (8) Critical ultrasonography can help to improve the safety and quality of nursing; (9) When performing critical ultrasonography for patients with COVID-19, it needs to implement three-level protection standard, pay attention to disinfect the machine and strictly obey the rules from nosocomial infection. (10) Telemedicine and artificial intelligence centered on critical ultrasonography may help to improve the efficiency of treatment for the patients with COVID-19. In the face of the global spread of the epidemic, all we can do is to share experience, build a defense line, We hope this recommendations can help COVID-19 patients therapy.