Associated factors of burnout among Chinese vaccination staff during COVID-19 epidemic: A cross-sectional study.

Objective: During the COVID-19 epidemic, vaccination staff had three main aspects of work: routine vaccination for children and adults, COVID-19 vaccination and COVID-19 prevention and control. All these works significantly increased the workload of vaccination staff. This study aimed to investigate the prevalence and influencing factors of burnout among vaccination staff in Hangzhou, China. Methods: A total of 501 vaccination staff from 201 community/township healthcare centers in Hangzhou were recruited using a cross-sectional survey through WeChat social platform. The Maslach Burnout Inventory-General Scale (MBI-GS) was used to assess the level of burnout. Descriptive statistics were made on the characteristics of participants. Univariate analysis using the chi-square test and multivariable analysis using binary logistic regression were conducted to determine the relative predictors of burnout. Univariate analysis and multiple linear regression were used to determine the relative predictors of exhaustive emotion, cynicism, and personal accomplishment. Results: During the COVID-19 pandemic, 20.8% of the vaccination staff experienced burnout. Educational level above undergraduate education level, medium professional title, and more working time in COVID-19 vaccination work reported a higher degree of job burnout. The vaccination staff was experiencing a high degree of exhaustive emotion, cynicism, and low personal accomplishment. Professional title, working place, and working time for COVID-19 vaccination were associated with exhaustive emotion and cynicism. Professional title and participation time for COVID-19 prevention and control were associated with personal accomplishment. Conclusions: Our findings suggest that the prevalence rate of burnout is high among vaccination staff during the COVID-19 pandemic, especially with a low level of personal accomplishment. Psychological intervention for vaccination staff is urgently needed.

Gender differences in the prevalence and impact factors of adolescent dissociative symptoms during the coronavirus disease 2019 pandemic.

The purpose of this study was to explore the differences between the prevalence and impact factors of adolescent dissociative symptoms (ADSs) by using sex-stratification during the coronavirus disease 2019 (COVID-19) pandemic. A school-based, two-center cross-sectional study was conducted in Hangzhou City, China, between January 1, 2021 and April 30, 2022. The sample included 1,916 adolescents aged 13-18 years that were randomly selected using a multiphase, stratified, cluster sampling technique. A two-stage assessment procedure was used to find out the ADSs. We used a multivariate logistic regression analysis to assess the impact factors of ADSs during the COVID-19 pandemic. The adolescent dissociative scores (t = 4.88, P < 0.001) and positive ADSs rate (Chi-square = 15.76, P < 0.001) in males were higher than in females. Gender-stratified, stepwise multiple logistic regression analysis revealed that the conflict relationship of teacher-student [adjusted odds ratio (AOR) 1.06, 95% confidence interval (CI) 1.01-1.10], family expressiveness (AOR 0.87, 95% CI 0.78-0.98), family conflict (AOR 1.15, 95% CI 1.05-1.27), family organization (AOR 0.88, 95% CI 0.78-0.99), and family cohesion (AOR 0.87, 95% CI 0.77-0.99) were linked to ADSs only in males, while individual psychological states of somatic complaint (AOR 1.04, 95% CI 1.00-1.08) and paranoid ideation (AOR 1.09, 95% CI 1.01-1.19) were associated with female ADSs only. The ADSs seemed to be prevalent in Hangzhou City, studied during the COVID-19 pandemic. Gender differences in the prevalence and impact factors of dissociative symptoms seem to be significant among adolescents. Thus, gender-specific intervention programs against ADSs should be considered as reducing this risk.

Comparative efficacy and safety of pharmacological interventions for severe COVID-19 patients: An updated network meta-analysis of 48 randomized controlled trials.

BACKGROUND: To date, there has been little agreement on what drug is the "best" drug for treating severe COVID-19 patients. This study aimed to assess the efficacy and safety of different medications available at present for severe COVID-19. METHODS: We searched databases for randomized controlled trials (RCTs) published up to February 28, 2022, with no language restrictions, of medications recommended for patients (aged 16 years or older) with severe COVID-19 infection. We extracted data on trials and patient characteristics, and the following primary outcomes: all-cause mortality (ACM), and treatment-emergent adverse events (TEAEs). RESULTS: We identified 4021 abstracts and of these included 48 RCTs comprising 9147 participants through database searches and other sources. For decrease in ACM, we found that ivermectin/doxycycline, C-IVIG (i.e., a hyperimmune anti-COVID-19 intravenous immunoglobulin), methylprednisolone, interferon-beta/standard-of-care (SOC), interferon-beta-1b, convalescent plasma, remdesivir, lopinavir/ritonavir, immunoglobulin gamma, high dosage sarilumab (HS), auxora, and imatinib were effective when compared with placebo or SOC group. We found that colchicine and interferon-beta/SOC were only associated with the TEAEs of severe COVID-19 patients. CONCLUSION: This study suggested that ivermectin/doxycycline, C-IVIG, methylprednisolone, interferon-beta/SOC, interferon-beta-1b, convalescent plasma (CP), remdesivir, lopinavir/ritonavir, immunoglobulin gamma, HS, auxora, and imatinib were efficacious for treating severe COVID-19 patients. We found that most medications were safe in treating severe COVID-19. More large-scale RCTs are still needed to confirm the results of this study.

Analysis of epidemic characteristics of forty-two COVID-19 cluster outbreaks in Hangzhou

Objective: To determine the epidemic characteristics of forty-two coronavirus disease 2019 (COVID-19) cluster outbreaks in Hangzhou city and provide scientific evidence for further prevention and control measures.

Efficacy and Safety of Anticoagulation Treatment in COVID-19 Patient Subgroups Identified by Clinical-Based Stratification and Unsupervised Machine Learning: A Matched Cohort Study.

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively reviewed 2,272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. The association between AC treatment and outcomes was investigated in the propensity score (PS) matched cohort and the full cohort by inverse probability of treatment weighting (IPTW) analysis. Subgroup analysis, identified by clinical-based stratification or unsupervised machine learning, was used to identify sub-phenotypes with meaningful clinical features and the target patients benefiting most from AC. Results: AC treatment was associated with lower in-hospital death risk either in the PS matched cohort or by IPTW analysis in the full cohort. A higher incidence of clinically relevant non-major bleeding (CRNMB) was observed in the AC group, but not major bleeding. Clinical subgroup analysis showed that, at admission, severe cases of COVID-19 clinical classification, mild acute respiratory distress syndrome (ARDS) cases, and patients with a D-dimer level ≥0.5 µg/mL, may benefit from AC. During the hospital stay, critical cases and severe ARDS cases may benefit from AC. Unsupervised machine learning analysis established a four-class clustering model. Clusters 1 and 2 were non-critical cases and might not benefit from AC, while clusters 3 and 4 were critical patients. Patients in cluster 3 might benefit from AC with no increase in bleeding events. While patients in cluster 4, who were characterized by multiple organ dysfunction (neurologic, circulation, coagulation, kidney and liver dysfunction) and elevated inflammation biomarkers, did not benefit from AC. Conclusions: AC treatment was associated with lower in-hospital death risk, especially in critically ill COVID-19 patients. Unsupervised learning analysis revealed that the most critically ill patients with multiple organ dysfunction and excessive inflammation might not benefit from AC. More attention should be paid to bleeding events (especially CRNMB) when using AC.

Efficacy and Safety of Anticoagulation Treatment in COVID-19 Patient Subgroups Identified by Clinical-Based Stratification and Unsupervised Machine Learning: A Matched Cohort Study

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively reviewed 2,272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. The association between AC treatment and outcomes was investigated in the propensity score (PS) matched cohort and the full cohort by inverse probability of treatment weighting (IPTW) analysis. Subgroup analysis, identified by clinical-based stratification or unsupervised machine learning, was used to identify sub-phenotypes with meaningful clinical features and the target patients benefiting most from AC. Results: AC treatment was associated with lower in-hospital death risk either in the PS matched cohort or by IPTW analysis in the full cohort. A higher incidence of clinically relevant non-major bleeding (CRNMB) was observed in the AC group, but not major bleeding. Clinical subgroup analysis showed that, at admission, severe cases of COVID-19 clinical classification, mild acute respiratory distress syndrome (ARDS) cases, and patients with a D-dimer level ≥0.5 μg/mL, may benefit from AC. During the hospital stay, critical cases and severe ARDS cases may benefit from AC. Unsupervised machine learning analysis established a four-class clustering model. Clusters 1 and 2 were non-critical cases and might not benefit from AC, while clusters 3 and 4 were critical patients. Patients in cluster 3 might benefit from AC with no increase in bleeding events. While patients in cluster 4, who were characterized by multiple organ dysfunction (neurologic, circulation, coagulation, kidney and liver dysfunction) and elevated inflammation biomarkers, did not benefit from AC. Conclusions: AC treatment was associated with lower in-hospital death risk, especially in critically ill COVID-19 patients. Unsupervised learning analysis revealed that the most critically ill patients with multiple organ dysfunction and excessive inflammation might not benefit from AC. More attention should be paid to bleeding events (especially CRNMB) when using AC.

Efficacy and safety of current treatment interventions for patients with severe COVID-19 infection: A network meta-analysis of randomized controlled trials.

This study aimed to assess the efficacy and safety of different medications available at present for severe coronavirus disease 2019 (COVID-19) infection. We searched databases for randomized controlled trials (RCTs) published up to April 30, 2021, with Chinese or English language restriction, of medications recommended for patients (aged 18 years or older) with severe COVID-19 infection. We extracted data on trials and patient characteristics, and the following primary outcomes: all-cause mortality (ACM), and treatment-emergent adverse events (TEAEs). We identified 1855 abstracts and of these included 15 RCTs comprising 3073 participants through database searches and other sources. In terms of efficacy, compared with the standard of care (SOC) group, no significant decrease in ACM was found in α-lipoic acid, convalescent plasma (CP), azithromycin, tocilizumab, methylprednisolone, interferon beta, CP/SOC, high dosage sarilumab, low dosage sarilumab, remdesivir, lopinavir-ritonavir, auxora, and placebo group. Compared with placebo, we found that a significant decrease in ACM was only found in methylprednisolone (odds ratio [OR]: 0.16, 95% confidence interval [CI]: 0.03-0.75]. With respect to TEAEs, the CP group showed lower TEAEs than placebo (OR: 0.07, 95% CI: 0.01-0.58) or SOC (OR: 0.05, 95% CI: 0.01-0.42) group for the therapy of severe COVID-19 patients. This study only demonstrated that methylprednisolone was superior to placebo in treating patients with severe COVID-19 infection. Meanwhile, this further confirmed that the safety of other treatment interventions might be inferior to CP for the therapy of severe COVID-19 patients.

Uncovering a conserved vulnerability site in SARS-CoV-2 by a human antibody.

An essential step for SARS-CoV-2 infection is the attachment to the host cell receptor by its Spike receptor-binding domain (RBD). Most of the existing RBD-targeting neutralizing antibodies block the receptor-binding motif (RBM), a mutable region with the potential to generate neutralization escape mutants. Here, we isolated and structurally characterized a non-RBM-targeting monoclonal antibody (FD20) from convalescent patients. FD20 engages the RBD at an epitope distal to the RBM with a KD of 5.6 nM, neutralizes SARS-CoV-2 including the current Variants of Concern such as B.1.1.7, B.1.351, P.1, and B.1.617.2 (Delta), displays modest cross-reactivity against SARS-CoV, and reduces viral replication in hamsters. The epitope coincides with a predicted "ideal" vulnerability site with high functional and structural constraints. Mutation of the residues of the conserved epitope variably affects FD20-binding but confers little or no resistance to neutralization. Finally, in vitro mode-of-action characterization and negative-stain electron microscopy suggest a neutralization mechanism by which FD20 destructs the Spike. Our results reveal a conserved vulnerability site in the SARS-CoV-2 Spike for the development of potential antiviral drugs.

Efficacy and safety of current medications for treating severe and non-severe COVID-19 patients: an updated network meta-analysis of randomized placebo-controlled trials.

BACKGROUND: Many recent studies have investigated the role of drug interventions for coronavirus disease 2019 (COVID-19) infection. However, an important question has been raised about how to select the effective and secure medications for COVID-19 patients. The aim of this analysis was to assess the efficacy and safety of the various medications available for severe and non-severe COVID-19 patients based on randomized placebo-controlled trials (RPCTs). METHODS: We did an updated network meta-analysis. We searched the databases from inception until July 31, 2021, with no language restrictions. We included RPCTs comparing 49 medications and placebo in the treatment of severe and non-severe patients (aged 18 years or older) with COVID-19 infection. We extracted data on the trial and patient characteristics, and the following primary outcomes: all-cause mortality, the ratios of virological cure, and treatment-emergent adverse events. Odds ratio (OR) and their 95% confidence interval (CI) were used as effect estimates. RESULTS: From 3,869 publications, we included 61 articles related to 73 RPCTs (57 in non-severe COVID-19 patients and 16 in severe COVID-19 patients), comprising 20,680 patients. The mean sample size was 160 (interquartile range 96-393) in this study. The median duration of follow-up drugs intervention was 28 days (interquartile range 21-30). For increase in virological cure, we only found that proxalutamide (OR 9.16, 95% CI 3.15-18.30), ivermectin (OR 6.33, 95% CI 1.22-32.86), and low dosage bamlanivimab (OR 5.29, 95% CI 1.12-24.99) seemed to be associated with non-severe COVID-19 patients when compared with placebo, in which proxalutamide seemed to be better than low dosage bamlanivimab (OR 5.69, 95% CI 2.43-17.65). For decrease in all-cause mortality, we found that proxalutamide (OR 0.13, 95% CI 0.09-0.19), imatinib (OR 0.49, 95% CI 0.25-0.96), and baricitinib (OR 0.58, 95% CI 0.42-0.82) seemed to be associated with non-severe COVID-19 patients; however, we only found that immunoglobulin gamma (OR 0.27, 95% CI 0.08-0.89) was related to severe COVID-19 patients when compared with placebo. For change in treatment-emergent adverse events, we only found that sotrovimab (OR 0.21, 95% CI 0.13-0.34) was associated with non-severe COVID-19 patients; however, we did not find any medications that presented a statistical difference when compared with placebo among severe COVID-19 patients. CONCLUSION: We conclude that marked variations exist in the efficacy and safety of medications between severe and non-severe patients with COVID-19. It seems that monoclonal antibodies (e.g., low dosage bamlanivimab, baricitinib, imatinib, and sotrovimab) are a better choice for treating severe or non-severe COVID-19 patients. Clinical decisions to use preferentially medications should carefully consider the risk-benefit profile based on efficacy and safety of all active interventions in patients with COVID-19 at different levels of infection.

Retrospective study of risk factors of 43 patients with severe coronavirus disease 2019 pneumonia

Objective To explore the risk factors of 43 patients with severe coronavirus disease 2019 pneumonia(COVID-19) in Hangzhou. Methods The clinical and epidemiological data of COVID-19 confirmed patients during 1 st January 2020 and 20 th March 2020 in Hangzhou were collected.The risk factors of the severe cases were analyzed by univariate and multivariate logistic regression. Results Up to 20 th March 2020,a total of 169 patients were reported in Hangzhou, among which, 43(25.44%) were severe cases.The analysis showed that over 60 years old[χ~2=6.16,P=0.01;OR(95%CI)=3.35(1.29-8.69)],hypertension[χ~2=6.91,P<0.001;OR(95%CI)=3.80(1.40-10.28)],headache as initial onset symptom [χ~2=4.80,P=0.03;OR(95%CI)=3.02(1.12-8.09)] and delayed hospitalization(Z=-2.21,P=0.03) were statistically significant. Conclusions Age over 60 years, hypertension, headache as initial onset symptom are risk factors and delayed hospitalization is influencing factor of severe COVID-19 patients.It is necessary to monitor COVID-19 patients′ condition and take effective treatment timely.

Rapid genomic characterization of SARS-CoV-2 viruses from clinical specimens using nanopore sequencing.

The novel SARS-CoV-2 outbreak has swiftly spread worldwide. The rapid genome sequencing of SARS-CoV-2 strains has become a helpful tool for better understanding the genomic characteristics and origin of the virus. To obtain virus whole-genome sequences directly from clinical specimens, we performed nanopore sequencing using a modified ARTIC protocol in a portable nanopore sequencer and validated a routine 8-h workflow and a 5-h rapid pipeline. We conducted some optimization to improve the genome sequencing workflow. The sensitivity of the workflow was also tested by serially diluting RNA from clinical samples. The optimized pipeline was finally applied to obtain the whole genomes of 29 clinical specimens collected in Hangzhou from January to March 2020. In the 29 obtained complete genomes of SARS-CoV-2, 33 variations were identified and analyzed. The genomic variations and phylogenetic analysis hinted at multiple sources and different transmission patterns during the COVID-19 epidemic in Hangzhou, China. In conclusion, the genomic characteristics and origin of the virus can be quickly determined by nanopore sequencing following our workflows.

Potential transmission of SARS-CoV-2 on a flight from Singapore to Hangzhou, China: An epidemiological investigation.

BACKGROUND: Between January 24, 2020 and February 15, 2020, an outbreak of COVID-19 occurred among 335 passengers on a flight from Singapore to Hangzhou in China. This study aimed to investigate the source of the outbreak and assess the risk of transmission of COVID-19 during the flight. METHOD: Using a standardized questionnaire, we collected information on the travelers' demographic characteristics and illness before, during, and after the flight. We also collected data on factors potentially associated with COVID-19 transmission during the flight. RESULTS: A total of 16 COVID-19 patients were diagnosed among all passengers; the overall attack rate was 4.8%. The attack rate among passengers who had departed from Wuhan was significantly higher than that among those who had departed from other places. One passenger without an epidemiological history of exposure before boarding developed COVID-19. During the flight, he was seated near four infected passengers from Wuhan for approximately an hour and did not wear his facemask correctly during the flight. CONCLUSIONS: COVID-19 transmission may have occurred during the flight. However, the majority of the cases in the flight-associated outbreak could not be attributed to transmission on the flight but were associated with exposure to the virus in Wuhan or to infected members in a single tour group.

Community Outbreak Investigation of SARS-CoV-2 Transmission Among Bus Riders in Eastern China.

Importance: Evidence of whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), can be transmitted as an aerosol (ie, airborne) has substantial public health implications. Objective: To investigate potential transmission routes of SARS-CoV-2 infection with epidemiologic evidence from a COVID-19 outbreak. Design, Setting, and Participants: This cohort study examined a community COVID-19 outbreak in Zhejiang province. On January 19, 2020, 128 individuals took 2 buses (60 [46.9%] from bus 1 and 68 [53.1%] from bus 2) on a 100-minute round trip to attend a 150-minute worship event. The source patient was a passenger on bus 2. We compared risks of SARS-CoV-2 infection among at-risk individuals taking bus 1 (n = 60) and bus 2 (n = 67 [source patient excluded]) and among all other individuals (n = 172) attending the worship event. We also divided seats on the exposed bus into high-risk and low-risk zones according to the distance from the source patient and compared COVID-19 risks in each zone. In both buses, central air conditioners were in indoor recirculation mode. Main Outcomes and Measures: SARS-CoV-2 infection was confirmed by reverse transcription polymerase chain reaction or by viral genome sequencing results. Attack rates for SARS-CoV-2 infection were calculated for different groups, and the spatial distribution of individuals who developed infection on bus 2 was obtained. Results: Of the 128 participants, 15 (11.7%) were men, 113 (88.3%) were women, and the mean age was 58.6 years. On bus 2, 24 of the 68 individuals (35.3% [including the index patient]) received a diagnosis of COVID-19 after the event. Meanwhile, none of the 60 individuals in bus 1 were infected. Among the other 172 individuals at the worship event, 7 (4.1%) subsequently received a COVID-19 diagnosis. Individuals in bus 2 had a 34.3% (95% CI, 24.1%-46.3%) higher risk of getting COVID-19 compared with those in bus 1 and were 11.4 (95% CI, 5.1-25.4) times more likely to have COVID-19 compared with all other individuals attending the worship event. Within bus 2, individuals in high-risk zones had moderately, but nonsignificantly, higher risk for COVID-19 compared with those in the low-risk zones. The absence of a significantly increased risk in the part of the bus closer to the index case suggested that airborne spread of the virus may at least partially explain the markedly high attack rate observed. Conclusions and Relevance: In this cohort study and case investigation of a community outbreak of COVID-19 in Zhejiang province, individuals who rode a bus to a worship event with a patient with COVID-19 had a higher risk of SARS-CoV-2 infection than individuals who rode another bus to the same event. Airborne spread of SARS-CoV-2 seems likely to have contributed to the high attack rate in the exposed bus. Future efforts at prevention and control must consider the potential for airborne spread of the virus.