Characteristics of immune response profile in patients with immediate allergic and autoimmune urticarial reactions induced by SARS-CoV-2 vaccines.

Severe allergic reactions following SARS-COV-2 vaccination are generally rare, but the reactions are increasingly reported. Some patients may develop prolonged urticarial reactions following SARS-COV-2 vaccination. Herein, we investigated the risk factors and immune mechanisms for patients with SARS-COV-2 vaccines-induced immediate allergy and chronic urticaria (CU). We prospectively recruited and analyzed 129 patients with SARS-COV-2 vaccine-induced immediate allergic and urticarial reactions as well as 115 SARS-COV-2 vaccines-tolerant individuals from multiple medical centers during 2021-2022. The clinical manifestations included acute urticaria, anaphylaxis, and delayed to chronic urticaria developed after SARS-COV-2 vaccinations. The serum levels of histamine, IL-2, IL-4, IL-6, IL-8, IL-17 A, TARC, and PARC were significantly elevated in allergic patients comparing to tolerant subjects (P-values = 4.5 × 10-5-0.039). Ex vivo basophil revealed that basophils from allergic patients could be significantly activated by SARS-COV-2 vaccine excipients (polyethylene glycol 2000 and polysorbate 80) or spike protein (P-values from 3.5 × 10-4 to 0.043). Further BAT study stimulated by patients' autoserum showed positive in 81.3% of patients with CU induced by SARS-COV-2 vaccination (P = 4.2 × 10-13), and the reactions could be attenuated by anti-IgE antibody. Autoantibodies screening also identified the significantly increased of IgE-anti-IL-24, IgG-anti-FcεRI, IgG-anti-thyroid peroxidase (TPO), and IgG-anti-thyroid-related proteins in SARS-COV-2 vaccines-induced CU patients comparing to SARS-COV-2 vaccines-tolerant controls (P-values = 4.6 × 10-10-0.048). Some patients with SARS-COV-2 vaccines-induced recalcitrant CU patients could be successfully treated with anti-IgE therapy. In conclusion, our results revealed that multiple vaccine components, inflammatory cytokines, and autoreactive IgG/IgE antibodies contribute to SARS-COV-2 vaccine-induced immediate allergic and autoimmune urticarial reactions.

Reduction of ACE2 serum concentrations by telbivudine in chronic hepatitis B patients.

BACKGROUND: Coronavirus disease 2019, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has wreaked havoc worldwide since December 2019. Currently, no effective medical treatments have been approved. As the epidemic continues to spread, SARS-CoV-2 mutants emerge, some of which become more infectious with increasing vaccine resistance. The main route for SARS-CoV-2 to enter the host cells is by binding of its spike protein to the host receptor, angiotensin-converting enzyme 2 (ACE2). Besides the membrane-bound form of ACE2, the soluble form of ACE2 (sACE2) can also bind SARS-CoV-2 for viral endocytosis. OBJECTIVE: Previously, we found that telbivudine reduced the concentrations of ACE1 in blood. Therefore, we speculated that this drug might also reduce the concentrations of sACE2. METHODS: In this retrospective study, serum samples from 39 hepatitis B patients receiving telbivudine were collected and examined for sACE2 concentrations using an ELISA kit. RESULTS: It was found that the serum concentrations of sACE2 were significantly declined in chronic hepatitis B patients treated by telbivudine. CONCLUSION: Telbivudine treatment reduced sACE2 concentrations, which could potentially reduce the infection risk of SARS-CoV-2.

MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosis (preprint)

Coronavirus disease 2019 (COVID-19) has spread all over the world for three years, but medical facilities in many areas still aren't adequate. There is a need for rapid COVID-19 diagnosis to identify high-risk patients and maximize the use of limited medical resources. Motivated by this fact, we proposed the deep learning framework MEDNC for automatic prediction and diagnosis of COVID-19 using computed tomography (CT) images. Our model was trained using two publicly available sets of COVID-19 data. And it was built with the inspiration of transfer learning. Results indicated that the MEDNC greatly enhanced the detection of COVID-19 infections, reaching an accuracy of 98.79% and 99.82% respectively. We tested MEDNC on a brain tumor and a blood cell dataset to show that our model applies to a wide range of problems. The outcomes demonstrated that our proposed models attained an accuracy of 99.39% and 99.28%, respectively. This COVID-19 recognition tool could help optimize healthcare resources and reduce clinicians' workload when screening for the virus.

The Omicron variant wave: Where are we now and what are the prospects?

The Omicron variant BA.2 is the dominant form of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in many countries, including those that have already implemented the strictest quarantine mandates that effectively contained the spread of the previous variants. Although many individuals were partially or fully vaccinated, confirmed Omicron infections have far surpassed all other variants combined in just a couple of months since the Omicron variant emerged. The ChAdOx1-S (AstraZeneca), BNT162b2 (Pfizer-BioNTech), and mRNA-1273 (Moderna) vaccines offer protection against the severe illness of SARS-CoV-2 infection; however, these currently available vaccines are less effective in terms of preventing Omicron infections. As a result, a booster dose of BNT162b2 or mRNA-1273 is recommended for individuals >12 years old who had received their second dose of the approved vaccines for >5 months. Herein, we review the studies that assessed the clinical benefits of the booster dose of vaccines against Omicron infections. We also analyzed public data to address whether early booster vaccination effectively prevented the surge of the Omicron infections. Finally, we discuss the consideration of a fourth dose of vaccine as a way to prevent possible upcoming infections.

Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic

The spread of the COVID-19 pandemic has resulted in the launch of contactless delivery services. This research integrates resource matching, service quality evaluation, and perceived value theories to explore the factors that promote the use contactless delivery services. The data was obtained through questionnaire surveys, and research hypotheses were verified through the structural equation modelling approach. With the exception of convenience, the results show that privacy, reliability, security, and flexibility have a significantly positive effect on consumers' intention to use "contactless” delivery services through consumers' perceived value. This study contributes to the literature by introducing theoretical frameworks from various paradigms and enriches the academic research on existing theoretical structure models. It also helps optimize resource allocation and realize the social environment related to coexisting with the COVID-19 pandemic.

The Impact of COVID-19 on Online Medical Education: A Knowledge Graph Analysis Based on Co-term Analysis (preprint)

Background：This study aims to identify the characteristics and future directions of online medical education in the context of the novel coronavirus outbreak new through visual analytics using CiteSpace and VOSviewer bibliometric methods. Method：From Web of Science, we searched for articles published between 2020 and 2022 using the terms online education, medical education and COVID-19, ended up with 2555 eligible papers, and the articles published between 2010 and 2019 using the terms online education, medical education and COVID-19, and we ended up with 4313 eligible papers. Results：Before the COVID-19 outbreak, Medical students and care were the most frequent keywords and the most cited author was BRENT THOMA with 18 times. The United States is the country with the greatest involvement and research impact in the field of online medical education. The most cited journal is ACAD MED with 1326 citations. After the COVID-19 outbreak, a surge in the number of research results in related fields, and ANXIETY and four secondary keywords were identified. In addition, the concentration of authors of these publications in the USA and China is a strong indication that local epidemics and communication technologies have influenced the development of online medical education research. Regarding the centrality of research institutions, the most influential co-author network is Harvard Medical School in the United States; and regarding the centrality of references, the most representative journal to which it belongs is VACCINE. Conclusion：This study found that hey information such as keywords, major institutions and authors, and countries differ in the papers before and after the COVID-19 outbreak. The novel coronavirus outbreak had a significant impact on the online education aspect. For non-medical and medical students, the pandemic has led to home isolation, making it difficult to offer face-to-face classes such as laboratory operations. Students have lost urgency and control over the specifics of face-to-face instruction, which has reduced the quality of teaching. Therefore, we should improve our education model according to the actual situation to ensure the quality of teaching while taking into account the physical and psychological health of students.

The Short-Term Effect of COVID-19 Pandemic on China’s Crude Oil Futures Market: A Study Based on Multifractal Analysis

The ongoing COVID-19 shocked financial markets globally, including China’s crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China’s first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [ FROM AUTHOR]

Contract Owner’s Best Commanding for Sweet Potato Farming Based on the Theory of Planned Behavior

The purpose of this study is to examine and compare different psychological and sociodemographic factors for contracting sweet potato production for farmers with different statuses based upon the theory of planned behavior (TPB). Sustainable production provides contract owners with a sufficient amount of both food crops and a source of bioethanol clean energy. The impact of such factors on potential farmers based on the TPB for a particular contract type is estimated with the data collected in three major sweet potato production cities/counties in Taiwan through the probit model and multinomial logit model. The average size of the surveyed farms is 1.64 ha. The results consistently show that the factors of attitude toward the advantages of contract farming, subjective norms regarding contract farming, perceived contract farming control, and behavior intention have very significant impacts on the selection of contract farming types for professional farmers and brokers. These results indicate that the contract owners will gain the greatest advantage through commanding any factor in TBP for these two groups of farmers, as they have an incentive to manage the sources of sweet potatoes at the best conditions before they have the agreement with the contract owners, either as the supply of bioethanol energy raw materials, supply of food crops, or supply of food processing materials.

A Linear Relationship Between De Ritis Ratio and Mortality in Hospitalized Patients With COVID-19: A Secondary Analysis Based on a Large Retrospective Cohort Study

Background and aims Although some studies have identified a possible link between the De Ritis ratio and the mortality of patients with COVID-19, the predictive value and the optimal cut-value remain unclear. This study aimed to explore the correlation between the De Ritis ratio and mortality in hospitalized COVID-19 patients. Methods The data for this cohort study came from a retrospective cohort study that was carried out in a medical system in New York City. The primary outcome was the in-hospital mortality of included patients. The researchers ran multivariate Cox regression analyses, curve fitting, and subgroup analysis to support our findings. Overall survival in different De Ritis ratio groups was plotted as Kaplan–Meier survival curves. Results The study enrolled 4371 participants with COVID-19 from 1 March 2020 to 16 April 2020. The overall mortality was 24.8% (1082/4371). The curve fitting analyses indicated that the De Ritis ratio has a positive linear connection with mortality in COVID-19 patients. After adjusting for all covariates, participants with a De Ritis ratio ≥ 2 exhibited 1.29 times the risk of in-hospital mortality compared with those with a De Ritis ratio < 1 (HR 1.29, 95% CI 1.02–1.62, p=0.031). The P for trend was<0.05 for all models. Patients in the group with a De Ritis ratio ≥ 2 experienced the shortest survival time in the Kaplan–Meier survival analysis. Conclusion A higher baseline De Ritis ratio is correlated with a corresponding higher mortality among hospitalized people with COVID-19.

Influence of COVID-19 epidemic on China's grain industry

The COVID-19 epidemic has caused different effects on China's grain production and people's lives. In order to promote the orderly development of grain production and ensure food security, this paper studied the impact of the COVID-19 epidemic on China's grain industry. It was found that under the epidemic situation, agricultural employment was difficult, the supply of agricultural materials was tight, traditional technology services to the countryside stagnated, and cross regional farming was blocked. In addition, diseases and insect pests were reappearing, and the international situation was more complex and changeable in this year. The pressure and challenge to stabilize grain production increased. Therefore, this paper suggested that food security should be taken as the top priority. In order to further ensure China's food security, we showed recover spring tillage production and area double cropping rice, ensure the smooth passage of important materials, provide multiform agricultural science and technology services, improve the early warning mechanisms of domestic and international markets, and build a new support system for grain production.

The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model

Background Messages on one’s stance toward vaccination on microblogging sites may affect the reader’s decision on whether to receive a vaccine. Understanding the dissemination of provaccine and antivaccine messages relating to COVID-19 on social media is crucial;however, studies on this topic have remained limited. Objective This study applies the elaboration likelihood model (ELM) to explore the characteristics of vaccine stance messages that may appeal to Twitter users. First, we examined the associations between the characteristics of vaccine stance tweets and the likelihood and number of retweets. Second, we identified the relative importance of the central and peripheral routes in decision-making on sharing a message. Methods English-language tweets from the United States that contained provaccine and antivaccine hashtags (N=150,338) were analyzed between April 26 and August 26, 2021. Logistic and generalized negative binomial regressions were conducted to predict retweet outcomes. The content-related central-route predictors were measured using the numbers of hashtags and mentions, emotional valence, emotional intensity, and concreteness. The content-unrelated peripheral-route predictors were measured using the numbers of likes and followers and whether the source was a verified user. Results Content-related characteristics played a prominent role in shaping decisions regarding whether to retweet antivaccine messages. Particularly, positive valence (incidence rate ratio [IRR]=1.32, P=.03) and concreteness (odds ratio [OR]=1.17, P=.01) were associated with higher numbers and likelihood of retweets of antivaccine messages, respectively;emotional intensity (subjectivity) was associated with fewer retweets of antivaccine messages (OR=0.78, P=.03;IRR=0.80, P=.04). However, these factors had either no or only small effects on the sharing of provaccine tweets. Retweets of provaccine messages were primarily determined by content-unrelated characteristics, such as the numbers of likes (OR=2.55, IRR=2.24, P<.001) and followers (OR=1.31, IRR=1.28, P<.001). Conclusions The dissemination of antivaccine messages is associated with both content-related and content-unrelated characteristics. By contrast, the dissemination of provaccine messages is primarily driven by content-unrelated characteristics. These findings signify the importance of leveraging the peripheral route to promote the dissemination of provaccine messages. Because antivaccine tweets with positive emotions, objective content, and concrete words are more likely to be disseminated, policymakers should pay attention to antivaccine messages with such characteristics.

Research on the Design Strategy of Healing Products for Anxious Users during COVID-19.

With the spread of COVID-19 worldwide, various travel restrictions are becoming a significant trigger for anxiety. Although healing products could relieve anxiety, few scholars have proposed a practical design strategy. Therefore, we offer a design strategy for healing products that includes three phases: preparation, analysis, and verification. In Phase 1, 20 people with moderate or high anxiety are invited to rate 100 samples. Then, FCM is used to obtain representative samples. In Phase 2, a three-layer diagram (incl. the upper, middle, and lower layers) of healing products is obtained using the evaluation grid method. Subsequently, the middle layer is considered evaluation criteria. Additionally, 18 items in the lower layer are considered design guidelines. In Phase 3, we invite two teams to develop innovative designs based on design guidelines and personal experience, generating four alternatives. Finally, four alternatives and four healing commodities are evaluated using grey relation analysis and perceptual questionnaires. The consistency of both evaluations could confirm the validity of the evaluation criteria. The alternatives generated based on the design guidelines are better than other alternatives, demonstrating the effectiveness of the design guidelines. The design strategy is beneficial for developing and evaluating healing products to alleviate people's anxiety during COVID-19.

Meteorological Factors Facilitated Increased Legionnaires’ Disease Notifications and Mortality Pre-COVID-19 and COVID-19 in Hong Kong (preprint)

Annual notification number of Legionnaires’ disease (LD) increased from 66 cases in 2015 to 104 cases in 2020 in Hong Kong, with a case fatality rate (CFR) of 17.3% in 2020. This study investigated possible meteorological factors associated with confirmed LD cases and deaths. The negative binomial regression model was used for monthly LD confirmed cases and the Poisson regression model was used for monthly LD mortality cases. A decision tree model was adopted to identify the thresholds of meteorological factors if any. The confirmed LD cases were highest in July while the LD mortality were highest in August. A negative binomial regression model confirmed that maximum air temperature (P=0.081, RR=1.3, 95% CI=0.97-1.75) and rainfall (P=0.009, RR=1.02, 95% CI=1.0004-1.003) were positively correlated with the increase in confirmed LD cases. A Poisson regression model confirmed that maximum air temperature (P=0.034, RR=1.71, 95%CI=1.04-2.80) was positively correlated with the surge in LD mortality. When rainfall exceeds 78.8 mm, the public should be alerted of the increased risk of contracting LD. Temperature and rainfall were positively associated with the confirmed LD cases in Hong Kong.

A Low-Cost Microfluidic Method for Microplastics Identification: Towards Continuous Recognition.

Plastic pollution has emerged as a growing concern worldwide. In particular, the most abundant plastic debris, microplastics, has necessitated the development of rapid and effective identification methods to track down the stages and evidence of the pollution. In this paper, we combine low-cost plastic staining technologies using Nile Red with the continuous feature offered by microfluidics to propose a low-cost 3D printed device for the identification of microplastics. It is observed that the microfluidic devices indicate comparable staining and identification performance compared to conventional Nile Red staining processes while offering the advantages of continuous recognition for long-term environmental monitoring. The results also show that concentration, temperature, and residency time possess strong effects on the identification performance. Finally, various microplastics have been applied to further demonstrate the effectiveness of the proposed devices. It is found that, among different types of microplastics, non-spherical microplastics show the maximal fluorescence level. Meanwhile, natural fibers indicate better staining quality when compared to synthetic ones.

The low-entropy hydration shell at the binding site of spike RBD determines the contagiousness of SARS-CoV-2 variants (preprint)

The infectivity of SARS-CoV-2 depends on the binding affinity of the receptor-binding domain (RBD) of the spike protein with the angiotensin converting enzyme 2 (ACE2) receptor. The calculated RBD-ACE2 binding energies indicate that the difference in transmission efficiency of SARS-CoV-2 variants cannot be fully explained by electrostatic interactions, hydrogen-bond interactions, van der Waals interactions, internal energy, and nonpolar solvation energies. Here, we demonstrate that low-entropy regions of hydration shells around proteins drive hydrophobic attraction between shape-matched low-entropy regions of the hydration shells, which essentially coordinates protein-protein binding in rotational-configurational space of mutual orientations and determines the binding affinity. An innovative method was used to identify the low-entropy regions of the hydration shells of the RBDs of multiple SARS-CoV-2 variants and the ACE2. We observed integral low-entropy regions of hydration shells covering the binding sites of the RBDs and matching in shape to the low-entropy region of hydration shell at the binding site of the ACE2. The RBD-ACE2 binding is thus found to be guided by hydrophobic collapse between the shape-matched low-entropy regions of the hydration shells. A measure of the low-entropy of the hydration shells can be obtained by counting the number of hydrophilic groups expressing hydrophilicity within the binding sites. The low-entropy level of hydration shells at the binding site of a spike protein is found to be an important indicator of the contagiousness of the coronavirus.

Discovery of Novel and Highly Potent Inhibitors of SARS CoV-2 Papain-Like Protease Through Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, Molecular Dynamics Simulations, and Biological Evaluation

Background and Objective: COVID-19 has struck our society as a great calamity, and the need for effective anti-viral drugs is more urgent than ever. Papain-like protease (PLpro) of SARS CoV-2 plays important roles in virus maturation, dysregulation of host inflammation, and antiviral immune responses, which is being regarded as a promising druggable target for the treatment of COVID-19. Here, we carried out a combined screening approach to identify novel and highly potent PLpro inhibitors for the treatment of COVID-19. Methods: We used a combined screening approach of structure-based pharmacophore modeling and molecular docking to screen an in-house database containing 35,000 compounds. SARS CoV-2 PLpro inhibition assay was used to carry out the biological evaluation of hit compounds. Molecular dynamics (MD) simulations were conducted to check the stability of the PLpro-hit complexes predicted by molecular docking. Results: We found that four hit compounds showed excellent inhibitory activities against PLpro with IC50 values ranging from 0.6 to 2.4 μM. Among them, the most promising compound, hit 2 is the best PLpro inhibitor and its inhibitory activity was about 4 times higher than that of the positive control (GRL0617). The study of MD simulations indicated that four hits could bind stably to the active site of PLpro. Further study of interaction analysis indicated that hit 2 could form hydrogen-bond interactions with the key amino acids such as Gln269 and Asp164 in the PLpro-active site. Conclusion: Hit 2 is a novel and highly potent PLpro inhibitor, which will open the way for the development of clinical PLpro inhibitors for the treatment of COVID-19.

Using Container Houses to Reduce the Risks to Health-Care Workers While Performing the Throat Swab Test and Blood Sampling for SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) is still pandemic all over the world. Patients requesting screening in emergency departments (ED) have continually increased. Establishing additional screening stations outside of the ED to increase the number of patients tested and protect the safety of health care workers poses an urgent challenge. We employed a container house near the entrance of an ED to create an outdoor screening station, which separates suspected patients of COVID-19 from regular emergency patients to prevent cross infections. In our experience, a container house station can not only provide additional screen area but also reduce the consumption of personal protective equipment. Container houses are sturdier than tents and can be fully assembled rapidly. Appropriate protective equipment can be installed with them to fulfi ll demands for COVID-19 screening.

Epidemiological Characteristics of COVID-19 Deaths In China: An Analysis of Environmental Factors (preprint)

Background: As of April 2020, most of the confirmed cases outside Hubei province have been cured or confirmed dead in China. We aimed to understand environmental factors leading to COVID-19-related mortality in non-Hubei region. Methods: : We collected spatial-temporal and environmental data of 99 cases of COVID-19-related deaths outside of Hubei province in Mainland China between January 22, 2020 and April 6, 2020. A descriptive analysis, including a spatial-temporal distribution of daily reported diagnosed cases and related deaths, was conducted. We analyzed the possible environmental factors that affect the provincial-level case fatality rate (CFR) of COVID-19 outside Hubei, China. Results: Among the 99 reported deaths, 59 (59.6%) were male and 40 (40.4%) were female. The mean age at death was 71.30 (SD 12.98) years and 74 deaths were among those 65 years or older. The CFR was negatively correlated with temperature (r=-0.679, P <0.001) and humidity (r=-0.607, P =0.002), while latitude was positively correlated with the CFR (r=0.636, P =0.001). There were no statistically significant associations between CFR and the social environment factors. Conclusion: Higher CFR of COVID-19 was associated with lower temperature, lower humidity, and higher latitude. Continual analysis of daily reported diagnoses and mortality data can help healthcare professionals and policy makers understand the trends within a country in order to better prepare nationwide prevention and care guidelines, along with adequately appropriate funds accordingly.

Preliminary estimates of the reproduction number of the Coronavirus disease (COVID-19) outbreak in Republic of Korea and Italy by 5 March 2020

The novel coronavirus disease 2019 (COVID-19) outbreak has caused 6088 cases and 41 deaths in Republic of Korea, and 3144 cases and 107 death in Italy by 5 March 2020, respectively. We modelled the transmission process in the Republic of Korea and Italy with a stochastic model, and estimated the basic reproduction number R0 as 2.6 (95% CI: 2.3-2.9) or 3.2 (95% CI: 2.9-3.5) in the Republic of Korea, under the assumption that the exponential growth starting on 31 January or 5 February 2020, and 2.6 (95% CI: 2.3-2.9) or 3.3 (95% CI: 3.0-3.6) in Italy, under the assumption that the exponential growth starting on 5 February or 10 February 2020, respectively.

Use of Plastic Bag to Reduce Risks in Operators During Endotracheal Intubation of Patients With Coronavirus Disease 2019.

The rapid spread of coronavirus disease 2019 (COVID-19) has led to a large number of patients being admitted to hospitals, resulting in a near collapse of the medical system. The shortage of negative pressure isolation rooms and personal protective equipment is a potential problem. It is a pressing challenge to prevent the risk of infection in emergency physicians (EPs) during the endotracheal intubation of patients with COVID-19. We used a large clear plastic bag, cut an opening that covered the patient's head, and created a negative pressure environment inside the plastic bag using the hospital's medical gas pipeline system; thus reducing the amount of virus-containing aerosols leaked out and the risk of infection in the operators performing intubation. The video (http://www.caregiver.com.tw/Article.asp?ID=1258#article) about the detailed preparation of the plastic bag intubation kit (PBIK) has been posted on the website. This technique for safe endotracheal intubation in patients with COVID-19 is being used not only by EPs in Taiwan, but also by physicians and paramedics from other countries. Regarding designing the PBIK, our original intention was to use readily available materials to make tools that can improve the safety of the operators performing the intubations in situations where medical resources are exhausted. However, due to limited time and patients, further research is needed for validation.