Reduced SARS-CoV-2 infection risk is associated with the use of Seven-Flavor Herb Tea: A multi-center observational study in Shanghai, China.

OBJECTIVE: Omicron, a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, is responsible for numerous infections in China. This study investigates the association between the use of Seven-Flavor Herb Tea (SFHT) and the risk of SARS-CoV-2 infection to develop precise and differentiated strategies for control of the coronavirus disease 2019 (COVID-19). METHODS: This case-control study was conducted at shelter hospitals and quarantine hotels in China. A total of 5348 laboratory-confirmed COVID-19 patients were enrolled between April 1 and May 31, 2022, while 2190 uninfected individuals served as healthy controls. Structured questionnaires were used to collect data on demographics, underlying diseases, vaccination status, and use of SFHT. Patients were propensity-score-matched using 1:1 nearest-neighbor matching of the logit of the propensity score. Subsequently, a conditional logistic regression model was used for data analysis. RESULTS: Overall, 7538 eligible subjects were recruited, with an average age of [45.54 ± 16.94] years. The age of COVID-19 patients was significantly higher than that of uninfected individuals ([48.25 ± 17.48] years vs [38.92 ± 13.41] years; t = 22.437, P < 0.001). A total of 2190 COVID-19 cases were matched with uninfected individuals at a 1:1 ratio. The use of SFHT (odds ratio = 0.753, 95% confidence interval: 0.692, 0.820) was associated with a lower risk of SARS-CoV-2 infection compared to untreated individuals. CONCLUSION: Our findings suggest that taking SFHT reduces the risk of SARS-CoV-2 infection. This is a useful study in the larger picture of COVID-19 management, but data from large-sample multi-center, randomized clinical trial are warranted to confirm the finding. Please cite this article as: Zhang SX, Chen XX, Zheng Y, Cai BH, Shi W, Ru M, Li H, Zhang DD, Tian Y, Chen YL. Reduced SARS-CoV-2 infection risk is associated with the use of Seven-Flavor Herb Tea: A multi-center observational study in Shanghai, China. J Integr Med. 2023; 21(4):369-376.

Early plasma angiopoietin-2 is prognostic for ARDS and mortality among critically ill patients with sepsis.

Angiopoietin-2 (Ang-2) is associated with vascular endothelial injury and permeability in the acute respiratory distress syndrome (ARDS) and sepsis. Elevated circulating Ang-2 levels may identify critically ill patients with distinct pathobiology amenable to targeted therapy. We hypothesized that plasma Ang-2 measured shortly after hospitalization among patients with sepsis would be associated with the development of ARDS and poor clinical outcomes. To test this hypothesis, we measured plasma Ang-2 in a cohort of 757 patients with sepsis, including 267 with ARDS, enrolled in the emergency department or early in their ICU course before the COVID-19 pandemic. Multivariable models were used to test the association of Ang-2 with the development of ARDS and 30-day morality. We found that early plasma Ang-2 in sepsis was associated with higher baseline severity of illness, the development of ARDS, and mortality risk. The association between Ang-2 and mortality was strongest among patients with ARDS and sepsis as compared to those with sepsis alone (OR 1.81 vs. 1.52 per log Ang-2 increase). These findings might inform models testing patient risk prediction and strengthen the evidence for Ang-2 as an appealing biomarker for patient selection for novel therapeutic agents to target vascular injury in sepsis and ARDS.

Age-specific transmission dynamics under suppression control measures during SARS-CoV-2 Omicron BA.2 epidemic.

BACKGROUND: From March to June 2022, an Omicron BA.2 epidemic occurred in Shanghai. We aimed to better understand the transmission dynamics and identify age-specific transmission characteristics for the epidemic. METHODS: Data on COVID-19 cases were collected from the Shanghai Municipal Health Commission during the period from 20th February to 1st June. The effective reproductive number (Rt) and transmission distance between cases were calculated. An age-structured SEIR model with social contact patterns was developed to reconstruct the transmission dynamics and evaluate age-specific transmission characteristics. Least square method was used to calibrate the model. Basic reproduction number (R0) was estimated with next generation matrix. RESULTS: R0 of Omicron variant was 7.9 (95% CI: 7.4 to 8.4). With strict interventions, Rt had dropped quickly from 3.6 (95% CI: 2.7 to 4.7) on 4th March to below 1 on 18th April. The mean transmission distance of the Omicron epidemic in Shanghai was 13.4 km (95% CI: 11.1 to 15.8 km), which was threefold longer compared with that of epidemic caused by the wild-type virus in Wuhan, China. The model estimated that there would have been a total 870,845 (95% CI: 815,400 to 926,289) cases for the epidemic from 20th February to 15th June, and 27.7% (95% CI: 24.4% to 30.9%) cases would have been unascertained. People aged 50-59 years had the highest transmission risk 0.216 (95% CI: 0.210 to 0.222), and the highest secondary attack rate (47.62%, 95% CI: 38.71% to 56.53%). CONCLUSIONS: The Omicron variant spread more quickly and widely than other variants and resulted in about one third cases unascertained for the recent outbreak in Shanghai. Prioritizing isolation and screening of people aged 40-59 might suppress the epidemic more effectively. Routine surveillance among people aged 40-59 years could also provide insight into the stage of the epidemic and the timely detection of new variants. TRIAL REGISTRATION: We did not involve clinical trial.

Genomic evidence for divergent co-infections of co-circulating SARS-CoV-2 lineages.

Co-infection of RNA viruses may contribute to their recombination and cause severe clinical symptoms. However, the tracking and identification of SARS-CoV-2 co-infection persist as challenges. Due to the lack of methods for detecting co-infected samples in a large amount of deep sequencing data, the lineage composition, spatial-temporal distribution, and frequency of SARS-CoV-2 co-infection events in the population remains unclear. Here, we propose a hypergeometric distribution-based method named Cov2Coinfect with the ability to decode the lineage composition from 50,809 deep sequencing data. By resolving the mutational patterns in each sample, Cov2Coinfect can precisely determine the co-infected SARS-CoV-2 variants from deep sequencing data. Results from two independent and parallel projects in the United States achieved a similar co-infection rate of 0.3-0.5 % in SARS-CoV-2 positive samples. Notably, all co-infected variants were highly consistent with the co-circulating SARS-CoV-2 lineages in the regional epidemiology, demonstrating that the co-circulation of different variants is an essential prerequisite for co-infection. Overall, our study not only provides a robust method to identify the co-infected SARS-CoV-2 variants from sequencing samples, but also highlights the urgent need to pay more attention to co-infected patients for better disease prevention and control.

Public Health Safety in Community Living Circles Based on a Behavioral Motivation Perspective: Theoretical Framework and Evaluation System.

Public health problems, such as the spread of COVID-19 and chronic diseases, are mainly caused by the daily life activities of community residents. Therefore, there is a need to build a healthy and safe community living circle through the evaluation of health behaviors in daily life. This paper proposes a theoretical framework and evaluation system for public health safety in community living circles, from a behavioral motivation perspective. Firstly, based on the behavioral motivation theory, a theoretical framework for the study of public health safety in community living circles is constructed from the perspective of the "project-activity-health" coupling relationship network, regarding community residents' daily life activities. Then, a public health safety evaluation system for community living circles is proposed based on this framework, which includes the following: (1) identifying the scope of community living circles based on Spatio-temporal Activities Analysis; (2) Based on the theory of protection motivation, a health behavior evaluation model based on the three elements of "spatial and temporal geographical environment-daily life activities-public health safety" is established; (3) Based on the hierarchy of public health problems, a public health safety evaluation model of the community living circle is established. The behavioral motivation-based evaluation system explores a new approach and research paradigm for community-scale public health safety theory; this will help to achieve the goal of "healthy communities" when further empirical evidence is available.

Clinical Value of Platelets and Coagulation Parameters in Predicting the Severity of Delta Variant SARS-CoV-2.

INTRODUCTION: The present study aimed to analyze the clinical features and laboratory markers of patients with Delta variant SARS-CoV-2 and explore the role of platelet in predicting the severity of Delta. METHODS: This retrospective, observational study was conducted on 863 patients laboratory-confirmed Delta variant SARS-CoV-2. These cases were sub-classified based on disease severity into mild (n = 304), moderate (n = 537), and severe (n = 22). A series of laboratory findings and clinical data were collected and analyzed during hospitalization. RESULTS: Of 863 hospitalized patients with Delta, the median age was 38 years (interquartile range, 30-51 years) and 471 (54.58%) were male. The most common clinical symptoms mainly included cough, fever, pharyngalgia, expectoration, dyspnea, fatigue, and headache, and the commonest comorbidities were hypertension and diabetes. Among the hematological variables, neutrophil count, red blood cell count, and hemoglobin, were found to be statistically significant with regard to subcategories based of disease severity (p < 0.05). Among coagulation parameters, there was a statistically significant difference in D-dimer, fibrinogen, international normalized ratio, and prothrombin time (p < 0.05). Statistically significant differences were observed in platelet markers including platelet count, large platelet count, and plateletcrit (p < 0.05). Additionally, there was strong correlation between platelet and other parameters with disease severity. Logistical regression analysis and ROC curves showed that D-dimer was a single best marker of disease severity (p = 0.005, p < 0.0001); however, platelet (p = 0.009, p = 0.002) and plateletcrit (p = 0.002, p = 0.001) could also predict severe disease. Platelet was identified as an independent risk factor for severe Delta. CONCLUSION: Low platelet may be a marker of disease severity in Delta variant SARS-CoV-2 and may contribute to determine the severity of patients infected with Delta.

Early Humoral Responses of Hemodialysis Patients After Inactivated SARS-CoV-2 Vaccination.

Purpose: To detect antibody responses to inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in patients undergoing hemodialysis and to investigate vaccine-related adverse events. Patients and Methods: A total of 120 hemodialysis (HD) patients and 24 healthy controls (HCs) who had not been previously infected with SARS-CoV-2 and had received their first dose of the inactivated vaccine (CoronaVac; Sinovac Biotech Ltd) were recruited for this study. All participants were scheduled to receive a second dose of inactivated SARS-CoV-2 vaccine. Serum-specific immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies against the SARS-CoV-2 were detected at least 14 days after the second dose of vaccine using a commercial kit. Positive and negative results were defined as a sample/cutoff (S/CO) ratio≥1.00 and <1.00, respectively. Vaccination-related adverse events were assessed using a standardized questionnaire. Results: There were no significant differences regarding the seroprevalences of IgG and IgM antibodies against SARS-CoV-2 and the self-reported vaccination-related adverse events between HD patients and HCs. The analysis results for HD patients suggest that 82 (68.3%) and 27 (22.5%) tested positive for IgG and IgM, respectively. The levels of IgG were higher than IgM levels (P<0.0001). In addition, the IgG-positive group had significantly higher serum albumin levels than the IgG-negative group (P<0.05). Only mild vaccine-related adverse events were observed in two patients (1.66%) and in one healthy individual (4.2%). Conclusion: The seroprevalences of IgG and IgM antibodies against SARS-CoV-2 and vaccination-related adverse effects are similar between HD and HCs. The inactivated SARS-CoV-2 vaccine is effective and safe in inducing near-term immunity in hemodialysis patients.

The rapid and efficient strategy for SARS-CoV-2 Omicron transmission control: analysis of outbreaks at the city level.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron (B.1.1.529) variant is highly transmissible with potential immune escape. Hence, control measures are continuously being optimized to guard against large-scale coronavirus disease 2019 (COVID-19) outbreaks. This study aimed to explore the relationship between the intensity of control measures in response to different SARS-CoV-2 variants and the degree of outbreak control at city level. METHODS: A retrospective study was conducted in 49 cities with COVID-19 outbreaks between January 2020 and June 2022. Epidemiological data on COVID-19 were extracted from the National Health Commission, People's Republic of China, and the population flow data were sourced from the Baidu migration data provided by the Baidu platform. Outbreak control was quantified by calculating the degree of infection growth and the time-varying reproduction number ([Formula: see text]). The intensity of the outbreak response was quantified by calculating the reduction in population mobility during the outbreak period. Correlation and regression analyses of the intensity of the control measures and the degree of outbreak control for the Omicron variant and non-Omicron mutants were conducted, respectively. RESULTS: Overall, 65 outbreaks occurred in 49 cities in China from January 2020 to June 2022. Of them, 66.2% were Omicron outbreaks and 33.8% were non-Omicron outbreaks. The intensity of the control measures was positively correlated with the degree of outbreak control (r = 0.351, P = 0.03). The degree of reduction in population mobility was negatively correlated with the Rt value (r = - 0.612, P < 0.01). Therefore, under the same control measure intensity, the number of new daily Omicron infections was 6.04 times higher than those attributed to non-Omicron variants, and the Rt value of Omicron outbreaks was 2.6 times higher than that of non-Omicron variants. In addition, the duration of non-Omicron variant outbreaks was shorter than that of the outbreaks caused by the Omicron variant (23.0 ± 10.7, 32.9 ± 16.3, t = 2.243, P = 0.031). CONCLUSIONS: Greater intensity of control measures was associated with more effective outbreak control. Thus, in response to the Omicron variant, the management to restrict population movement should be used to control its spread quickly, especially in the case of community transmission occurs widely. Faster than is needed for non-Omicron variants, and decisive control measures should be imposed and dynamically adjusted in accordance with the evolving epidemic situation.

Convolutional Neural Networks Based on Sequential Spike Predict the High Human Adaptation of SARS-CoV-2 Omicron Variants.

The COVID-19 pandemic has frequently produced more highly transmissible SARS-CoV-2 variants, such as Omicron, which has produced sublineages. It is a challenge to tell apart high-risk Omicron sublineages and other lineages of SARS-CoV-2 variants. We aimed to build a fine-grained deep learning (DL) model to assess SARS-CoV-2 transmissibility, updating our former coarse-grained model, with the training/validating data of early-stage SARS-CoV-2 variants and based on sequential Spike samples. Sequential amino acid (AA) frequency was decomposed into serially and slidingly windowed fragments in Spike. Unsupervised machine learning approaches were performed to observe the distribution in sequential AA frequency and then a supervised Convolutional Neural Network (CNN) was built with three adaptation labels to predict the human adaptation of Omicron variants in sublineages. Results indicated clear inter-lineage separation and intra-lineage clustering for SARS-CoV-2 variants in the decomposed sequential AAs. Accurate classification by the predictor was validated for the variants with different adaptations. Higher adaptation for the BA.2 sublineage and middle-level adaptation for the BA.1/BA.1.1 sublineages were predicted for Omicron variants. Summarily, the Omicron BA.2 sublineage is more adaptive than BA.1/BA.1.1 and has spread more rapidly, particularly in Europe. The fine-grained adaptation DL model works well for the timely assessment of the transmissibility of SARS-CoV-2 variants, facilitating the control of emerging SARS-CoV-2 variants.

Convolutional Neural Networks Based on Sequential Spike Predict the High Human Adaptation of SARS-CoV-2 Omicron Variants

The COVID-19 pandemic has frequently produced more highly transmissible SARS-CoV-2 variants, such as Omicron, which has produced sublineages. It is a challenge to tell apart high-risk Omicron sublineages and other lineages of SARS-CoV-2 variants. We aimed to build a fine-grained deep learning (DL) model to assess SARS-CoV-2 transmissibility, updating our former coarse-grained model, with the training/validating data of early-stage SARS-CoV-2 variants and based on sequential Spike samples. Sequential amino acid (AA) frequency was decomposed into serially and slidingly windowed fragments in Spike. Unsupervised machine learning approaches were performed to observe the distribution in sequential AA frequency and then a supervised Convolutional Neural Network (CNN) was built with three adaptation labels to predict the human adaptation of Omicron variants in sublineages. Results indicated clear inter-lineage separation and intra-lineage clustering for SARS-CoV-2 variants in the decomposed sequential AAs. Accurate classification by the predictor was validated for the variants with different adaptations. Higher adaptation for the BA.2 sublineage and middle-level adaptation for the BA.1/BA.1.1 sublineages were predicted for Omicron variants. Summarily, the Omicron BA.2 sublineage is more adaptive than BA.1/BA.1.1 and has spread more rapidly, particularly in Europe. The fine-grained adaptation DL model works well for the timely assessment of the transmissibility of SARS-CoV-2 variants, facilitating the control of emerging SARS-CoV-2 variants.

An overview of nanomaterial-based novel disinfection technologies for harmful microorganisms: Mechanism, synthesis, devices and application.

Harmful microorganism (e.g., new coronavirus) based infection is the most important security concern in life sciences and healthcare. This article aims to provide a state-of-the-art review on the development of advanced technology based on nanomaterial disinfection/sterilization techniques (NDST) for the first time including the nanomaterial types, disinfection techniques, bactericidal devices, sterilization products, and application scenarios (i.e., water, air, medical healthcare), with particular brief account of bactericidal behaviors referring to varied systems. In this emerging research area spanning the years from 1998 to 2021, total of ~200 publications selected for the type of review paper and research articles were reviewed. Four typical functional materials (namely type of metal/metal oxides, S-based, C-based, and N-based) with their development progresses in disinfection/sterilization are summarized with a list of synthesis and design. Among them, the widely used silver nanoparticles (AgNPs) are considered as the most effective bacterial agents in the type of nanomaterials at present and has been reported for inactivation of viruses, fungi, protozoa. Some methodologies against (1) disinfection by-products (DBPs) in traditional sterilization, (2) noble metal nanoparticles (NPs) agglomeration and release, (3) toxic metal leaching, (4) solar spectral response broadening, and (5) photogenerated e-/h+ pairs recombination are reviewed and discussed in this field, namely (1) alternative techniques and nanomaterials, (2) supporter anchoring effect, (3) nonmetal functional nanomaterials, (4) element doping, and (5) heterojunction constructing. The feasible strategies in the perspective of NDST are proposed to involve (1) non-noble metal disinfectors, (2) multi-functional nanomaterials, (3) multi-component nanocomposite innovation, and (4) hybrid techniques for disinfection/sterilization system. It is promising to achieve 100% bactericidal efficiency for 108 CFU/mL within a short time of less than 30 min.

A Nonextensive View on the COVID-19 in the World (preprint)

This paper deals with a general Susceptible-Infectious-Removed (SIR) model for the coronavirus disease 2019 (COVID-19) within a non-extensive view. A time-dependent SIR model was modified when particularly regarding control and mitigation measures in response to the societal impacts of epidemics and pandemics. We validated all the theoretical results by fitting the derived q-distributions with data from the COVID-19 pandemic in the world. It was found that not all the changeable fit parameters are independent, some of which shared common properties, a result corroborated by our model prediction. Our modified SIR model was proved to be effective in fitting the COVID-19 epidemic distributions. The relative non-extensive parameter was strongly connected with the freedom of systems, which thus threw a light upon the prevention and treatment of disease next in the world.

A Nonextensive View on the COVID-19 in the World (preprint)

This paper deals with a general Susceptible-Infectious-Removed (SIR) model for the coronavirus disease 2019 (COVID-19) within a non-extensive view. A time-dependent SIR model was modified when particularly regarding control and mitigation measures in response to the societal impacts of epidemics and pandemics. We validated all the theoretical results by fitting the derived q-distributions with data from the COVID-19 pandemic in the world. It was found that not all the changeable fit parameters are independent, some of which shared common properties, a result corroborated by our model prediction. Our modified SIR model was proved to be effective in fitting the COVID-19 epidemic distributions. The relative non-extensive parameter was strongly connected with the freedom of systems, which thus threw a light upon the prevention and treatment of disease next in the world.

Conceptualizing the Internet Compulsive-Buying Tendency: What We Know and Need to Know in the Context of the COVID-19 Pandemic

Over the past decade, new innovative products and services have been introduced into the marketplace using advanced technology. The enticement of new products lures consumers to buy compulsively. Because of the convenience and the characteristics of online shopping, it will increase the incidence of compulsive-buying behavior. Meanwhile, due to the fact that the COVID-19 pandemic is continuing to spread around the world, consumers may change their decision-making and behavior to shop online more frequently and intensively. The repetitive shopping online means more cardboard, delivery transportations, and vehicles and that more goods will be produced. It will result in an unfriendly result for the environment. Given the critical role of compulsive buying in the emerging Internet retail environment, it is necessary to develop and validate an instrument to measure the Internet compulsive-buying tendency (ICBT). Therefore, a rigorous measurement-scale-development procedure was applied to evaluate the initial 31 items. After two rounds of data collection and assessment, the final instrument contained 18 items that fall into four subconstructs: the tendency to spend online, feelings about online shopping and spending, dysfunctional online spending, and online post-purchase guilt. These factors can provide a basis for predicting tendencies toward Internet compulsive shopping and can be used to evaluate consumers’abnormal behavior in online-shopping circumstances.

Does Proton Pump Inhibitor Use Lead to a Higher Risk of Coronavirus Disease 2019 Infection and Progression to Severe Disease? a Meta-analysis.

The findings of previous research on the association between proton pump inhibitor (PPI) use and the treatment and prevention of coronavirus disease 2019 (COVID-19) are inconsistent. Therefore, this meta-analysis was conducted to clarify the outcomes of patients taking PPIs. This analysis included 14 articles with more than 268,683 subjects. PPI use was not associated with increased or decreased risk of COVID-19 infection (odds ratio [OR] 1.64, 95% confidence interval [CI] = 0.54-5.00, P = 0.39) or mortality (OR = 1.91, 95% CI = 0.86-4.24, P = 0.11). However, PPI use increased the risks of severe disease (OR 1.67, 95% CI = 1.37-2.02, P < 0.00001) and secondary infection (OR 4.62, 95% CI = 2.55-8.39, P < 0.00001). In summary, PPI use was not associated with an increased risk of infection and mortality in COVID-19 but appeared to be associated with an increased risk of progression to severe disease and secondary infection. However, more original studies are urgently needed to further clarify the relationship between PPI use and COVID-19.

Elastase Inhibitor Cyclotheonellazole A: Total Synthesis and In Vivo Biological Evaluation for Acute Lung Injury.

Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is one of the most common complications in COVID-19. Elastase has been recognized as an important target to prevent ALI/ARDS in the patient of COVID-19. Cyclotheonellazole A (CTL-A) is a natural macrocyclic peptide reported to be a potent elastase inhibitor. Herein, we completed the first total synthesis of CTL-A in 24 linear steps. The key reactions include three-component MAC reactions and two late-stage oxidations. We also provided seven CTL-A analogues and elucidated preliminary structure-activity relationships. The in vivo ALI mouse model further suggested that CTL-A alleviated acute lung injury with reductions in lung edema and pathological deterioration, which is better than sivelestat, one approved elastase inhibitor. The activity of CTL-A against elastase, along with its cellular safety and well-established synthetic route, warrants further investigation of CTL-A as a candidate against COVID-19 pathogeneses.

Impact of the coronavirus disease 2019 interventions on the incidence of hand, foot, and mouth disease in mainland China.

BACKGROUND: In early 2020, non-pharmaceutical interventions (NPIs) were implemented in China to reduce and contain the coronavirus disease 2019 (COVID-19) transmission. These NPIs might have also reduced the incidence of hand, foot, and mouth disease (HFMD). METHODS: The weekly numbers of HFMD cases and meteorological factors in 31 provincial capital cities and municipalities in mainland China were obtained from Chinese Center for Disease Control and Prevention (CCDC) and National Meteorological Information Center of China from 2016 to 2020. The NPI data were collected from local CDCs. The incidence rate ratios (IRRs) were calculated for the entire year of 2020, and for January-July 2020 and August-December 2020. The expected case numbers were estimated using seasonal autoregressive integrated moving average models. The relationships between kindergarten closures and incidence of HFMD were quantified using a generalized additive model. The estimated associations from all cities were pooled using a multivariate meta-regression model. FINDINGS: Stringent NPIs were widely implemented for COVID-19 control from January to July 2020, and the IRRs for HFMD were less than 1 in all 31 cities, and less than 0·1 for 23 cities. Overall, the proportion of HFMD cases reduced by 52·9% (95% CI: 49·3-55·5%) after the implementation of kindergarten closures in 2020, and this effect was generally consistent across subgroups. INTERPRETATION: The decrease in HFMD incidence was strongly associated with the NPIs for COVID-19. HFMD epidemic peaks were either absent or delayed, and the final epidemic size was reduced. Kindergarten closure is an intervention to prevent HFMD outbreaks. FUNDING: This research was supported by the National Natural Science Foundation of China (81973102 & 81773487), Public Health Talents Training Program of Shanghai Municipality (GWV-10.2-XD21), the Shanghai New Three-year Action Plan for Public Health (GWV-10.1-XK16), the Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China (2021YFF0306000), 13th Five-Year National Science and Technology Major Project for Infectious Diseases (2018ZX10725-509) and Key projects of the PLA logistics Scientific research Program (BHJ17J013).

New-onset autoimmune phenomena post-COVID-19 vaccination.

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented setback for global economy and health. Vaccination is one of the most effective interventions to substantially reduce severe disease and death due to SARS-CoV-2 infection. Vaccination programmes are being rolled out globally, but most of these vaccines have been approved without extensive studies on their side-effects and efficacy. Recently, new-onset autoimmune phenomena after COVID-19 vaccination have been reported increasingly (e.g. immune thrombotic thrombocytopenia, autoimmune liver diseases, Guillain-Barré syndrome, IgA nephropathy, rheumatoid arthritis and systemic lupus erythematosus). Molecular mimicry, the production of particular autoantibodies and the role of certain vaccine adjuvants seem to be substantial contributors to autoimmune phenomena. However, whether the association between COVID-19 vaccine and autoimmune manifestations is coincidental or causal remains to be elucidated. Here, we summarize the emerging evidence about autoimmune manifestations occurring in response to certain COVID-19 vaccines. Although information pertaining to the risk of autoimmune disease as a consequence of vaccination is controversial, we merely propose our current understanding of autoimmune manifestations associated with COVID-19 vaccine. In fact, we do not aim to disavow the overwhelming benefits of mass COVID-19 vaccination in preventing COVID-19 morbidity and mortality. These reports could help guide clinical assessment and management of autoimmune manifestations after COVID-19 vaccination.