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BACKGROUND: An orally aerosolised adenovirus type-5 vector-based COVID-19 vaccine (Ad5-nCoV) has recently been authorized for boosting immunization in China. Our study aims to assess the environmental impact of the use of aerosolised Ad5-nCoV. METHODS: We collected air samples from rooms, swabs from the setting desks of the vaccine nebuliser, mask samples from participants and blood samples of nurses who administered the inoculation in the clinical trials. The viral load of adenovirus type-5 vector in the samples and the antibody levels against the wild-type SARS-CoV-2 strain in serum were detected. RESULTS: Only one (4.00%) air samples collected before the initiation of vaccination was positive, which were almost positive during and after the vaccination (97.96%, 100%, respectively). All nurses in the trial A showed at least four-fold increase of the neutralizing antibody against the SARS-CoV-2 after the initiation of the study. In trial B, the positive proportion of the mask samples was 72.97% at 30 minutes after vaccination, 8.11% at day 1, and 0% at days 3, 5, and 7, respectively. CONCLUSION: The vaccination with the orally aerosolised Ad5-nCoV could have some spillage of the vaccine vector viral particles in the environment and cause human exposure.
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China has implemented a series of long-term measures for the public in order to control spread of COVID-19,whether these measures will affect other chronic and acute respiratory infectious diseases and what kind of impact are unclear. Tuberculosis (TB) and scarlet fever (SF) as the representative of chronic and acute respiratory infectious diseases respectively,and China’s Guizhou was an area with high prevalence of TB and SF ,with about 40,000 TB and hundreds of SF cases were reported every year.To assess impact of COVID-19 prevention and control on TB and SF in China’s Guizhou, exponential smoothing method was used to establish a prediction model to analyze the impact of COVID-19 on the number of TB and SF cases in Guizhou,and spatial aggregation analysis was used to describe the spatial changes of TB and SF before and after the outbreak of COVID-19.The parameters of TB and SF prediction models are R²=0.856, BIC=10.972;R²=0.714,BIC=5.325, respectively.TB and SF cases declined rapidly at the beginning of COVID-19 prevention and control,but SF cases number in decline for about 3-6 months,TB cases number remained in decline for 7 months after implementation for 11 months. Spatial aggregation of TB and SF did not change much before and after the COVID-19 outbreak but decreased significantly.Our fndings indicated that China's COVID-19 prevention and control measures also reduced TB and SF prevalence in Guizhou, these measures may lead to a long-term beneficial impact on TB, but a short-term on SF. Area with high TB incidence may benefit from COVID-19 experiences in the future.
Subject(s)
COVID-19 , Fever , Tuberculosis , Communicable DiseasesABSTRACT
Objectives: When diagnosing Coronavirus disease 2019(COVID-19), radiologists cannot make an accurate judgments because the image characteristics of COVID-19 and other pneumonia are similar. As machine learning advances, artificial intelligence(AI) models show promise in diagnosing COVID-19 and other pneumonias. We performed a systematic review and meta-analysis to assess the diagnostic accuracy and methodological quality of the models. Methods: We searched PubMed, Cochrane Library, Web of Science, and Embase, preprints from medRxiv and bioRxiv to locate studies published before December 2021, with no language restrictions. And a quality assessment (QUADAS-2), Radiomics Quality Score (RQS) tools and CLAIM checklist were used to assess the quality of each study. We used random-effects models to calculate pooled sensitivity and specificity, I2 values to assess heterogeneity, and Deeks' test to assess publication bias. Results: We screened 32 studies from the 2001 retrieved articles for inclusion in the meta-analysis. We included 6737 participants in the test or validation group. The meta-analysis revealed that AI models based on chest imaging distinguishes COVID-19 from other pneumonias: pooled area under the curve (AUC) 0.96 (95 % CI, 0.94-0.98), sensitivity 0.92 (95 % CI, 0.88-0.94), pooled specificity 0.91 (95 % CI, 0.87-0.93). The average RQS score of 13 studies using radiomics was 7.8, accounting for 22 % of the total score. The 19 studies using deep learning methods had an average CLAIM score of 20, slightly less than half (48.24 %) the ideal score of 42.00. Conclusions: The AI model for chest imaging could well diagnose COVID-19 and other pneumonias. However, it has not been implemented as a clinical decision-making tool. Future researchers should pay more attention to the quality of research methodology and further improve the generalizability of the developed predictive models.
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The coronavirus SARS-CoV-2 has mutated quickly and caused significant global damage. This study characterizes two mRNA vaccines ZSVG-02 (Delta) and ZSVG-02-O (Omicron BA.1), and associating heterologous prime-boost strategy following the prime of a most widely administrated inactivated whole-virus vaccine (BBIBP-CorV). The ZSVG-02-O induces neutralizing antibodies that effectively cross-react with Omicron subvariants following an order of BA.1>BA.2>BA.4/5. In native animals, ZSVG-02 or ZSVG-02-O induce humoral responses skewed to the vaccine's targeting strains, but cellular immune responses cross-react to all variants of concern (VOCs) tested. Following heterologous prime-boost regimes, animals present comparable neutralizing antibody levels and superior protection across all VOCs. Single-boost only generated ancestral and omicron dual-responsive antibodies, probably by "recall" and "reshape" the prime immunity. New Omicron-specific antibody populations, however, appeared only following the second boost with ZSVG-02-O. Overall, our results support a heterologous boost with ZSVG-02-O, providing the best protection against current VOCs in inactivated virus vaccine-primed populations.
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To compete with the speedy revolution of high technological innovation and restarted economy for the post-COVID-19 period in China, governments and organizations should be active in attracting high-tech talent to enhance independent and indigenous R&D capability. Talent agglomeration effectiveness is the strongest endogenous force pushing competitiveness for regional economy and industrial develo*pment. Due to the complexity of high-tech talent agglomeration, there are still considerable gaps to evaluate the incentive factors. This study evaluates the influential indicator system by using a hybrid fuzzy set theory extended Analytic Hierarchy Process (AHP) approach for proximity to reality from individual, organizational and environmental dimensions. The statistical analysis is adopted to verify the results of fuzzy AHP analysis. This research explores the founding that individual incentives are more important than environmental factors, and environmental incentives are more influential than organizational incentives. Job satisfaction, welfare system, and geographical location are the highest ranking factors. High-tech start-ups should give priority to combine geographical location with political support to reserve site selection or firm relocation for a great effectiveness of high-tech talent agglomeration.
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The natural resources commodity price volatility is one of the leading discussion issues, particularly in global issues. For instance, the global financial crisis and the Covid-19 pandemic have created uncertainties in global economic and financial markets. During the said events, the global economy disrupts the demand and supply chain of raw materials, natural resources, and energy across the globe, which is among the leading issues of price volatility in natural resources. Therefore, it is important to evaluate the volatility of natural resources, especially during these two periods. The current study, unlike previous studies, evaluates the volatility in crude oil prices while using the extended period from 2007 to 11-01 to 2020-11-16 from a global perspective. The empirical analyses are examined using exponential generalized autoregressive conditional heteroscedasticity and the threshold generalized autoregressive conditional heteroscedasticity methods. The estimated results of both approaches indicate the existence of volatility in natural resource commodity prices. Yet, the global financial crisis and Covid-19 pandemic periods exhibit higher volatilities than the rest of the overall period. Comparatively, natural resources commodity price volatility in the Covid-19 pandemic surpasses the volatility than that of the global financial crisis. This study provides relevant policy implications regarding global volatility management based on the empirical results. The study further provides guidelines for future research on the same area and limitations indorded in this study.
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SARS-CoV-2 variants of concern (VOCs), especially the latest Omicron, have exhibited severe antibody evasion. Broadly neutralizing antibodies with high potency against Omicron are urgently needed for understanding working mechanisms and developing therapeutic agents. In this study, we characterized previously reported F61, which was isolated from convalescent patients infected with prototype SARS-CoV-2, as a broadly neutralizing antibody against all VOCs including Omicron BA.1, BA.1.1, BA.2, BA.3 and BA.4 sublineages by utilizing antigen binding and cell infection assays. We also identified and characterized another broadly neutralizing antibody D2 with epitope distinct from that of F61. More importantly, we showed that a combination of F61 with D2 exhibited synergy in neutralization and protecting mice from SARS-CoV-2 Delta and Omicron BA.1 variants. Cryo-EM structures of the spike-F61 and spike-D2 binary complexes revealed the distinct epitopes of F61 and D2 at atomic level and the structural basis for neutralization. Cryo-EM structure of the Omicron-spike-F61-D2 ternary complex provides further structural insights into the synergy between F61 and D2. These results collectively indicated F61 and F61-D2 cocktail as promising therapeutic antibodies for combating SARS-CoV-2 variants including diverse Omicron sublineages.
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INTRODUCTION: Previous studies have linked the relationship between ABO blood group and COVID-19 infection. However, existing evidence is preliminary and controversial. This meta-analysis sought to identify studies that describe COVID-19 and ABO blood group. METHODOLOGY: A literature search was conducted from PubMed, Web of Science, MedRxiv, BioRxiv and Google Scholar databases. Members of cases and controls were extracted from collected studies. Pooled Odds ratio (OR) and 95% confidence interval (95%CI) were calculated and interpreted from extracted data. Publication bias and sensitivity analysis were also applied to confirm our discovery. RESULTS: Total 13,600 patients and 3,445,047 controls were included in the study. Compared to other ABO blood group, blood group O was associated with a lower risk of COVID-19 infection (OR = 0.76, 95%CI 0.66-0.84), while blood group A and AB was associated with a higher risk (OR = 1.25, 95%CI 1.10-1.41; OR = 1.13, 95%CI 1.04-1.23, respectively). In the subgroup analysis, the relationship between blood group A, O and COVID-19 infection remained stable among Chinese, European and Eastern Mediterranean populations. In American population, blood groups B was linked with increased risk of COVID-19 infection (OR = 1.21, 95%CI 1.09-1.35). CONCLUSIONS: Our data suggested that individuals with blood types A and AB are more susceptible to COVID-19, while people with blood type O are less susceptible to infection. More research is needed to clarify the precise role of the ABO blood group in COVID-19 infection to address the global question.
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ABO Blood-Group System , COVID-19/blood , Disease Susceptibility/blood , COVID-19/epidemiology , Global Health , Humans , Pandemics , Risk Assessment , SARS-CoV-2ABSTRACT
Purpose: To improve the understanding of the manifestations associated with computed tomography (CT) in the context of coronavirus disease 2019 (COVID-19). Methods: An analysis of a retrospective nature was carried out on clinically-based data as well as CT manifestations in 102 patients with a COVID-19 diagnosis who were admitted to our hospital between the 24th of January, 2020 and the 5th of February, 2020. Scoring of CT manifestations was accomplished, and the total score was used to determine the severity of lung injury. Results: Of the 102 patients, 10 had mild COVID-19, 72 had COVID-19 that was classed as moderate, 16 had COVID-19 that was severe, and 4 had COVID-19 that was critically severe. In all, 92 patients developed lung lesions, among whom 85 showed bilateral lung involvement. Superior lobe lesions and lesions in the middle-inner zone of the lung less frequently affected patients who developed moderate COVID-19 as compared to patients who developed severe/critically severe COVID-19 (all P < 0.05). The lesion manifestations included ground-glass opacity shadows (98.9%) and mixed-density shadows with consolidation (45.7%). Lamellar lesions and interlobular septal thickening less frequently affected patients with COVID-19 that was moderate than in patients with COVID-19 that was severe or critically severe (P < 0.05). In terms of COVID-19 that was moderate, severe or critically severe, the average scores associated with CT were 10.68 ± 6.32, 22.31 ± 8.07, and 30.75 ± 1.89 points respectively. A cumulative CT score of ≤ 20 points was the critical point for distinguishing moderate COVID-19 from severe/critically severe COVID-19. Conclusion: With regards to CT manifestations that were associated with COVID-19, certain characteristics were demonstrated and these varied in relation to different classifications of COVID-19. Cumulative CT score could be used to evaluate the clinical classification and degree of lung damage in patients who develop COVID-19.
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COVID-19 vaccines from multiple manufacturers are needed to cope with the problem of insufficient supply. We did two single-center, randomised, double-blind, placebo-controlled phase 1 and phase 2 trials to assess the safety, tolerability and immunogenicity of a recombinant COVID-19 vaccine (Sf9 cells) in healthy population aged 18 years or older in China. Eligible participants were enrolled, the ratio of candidate vaccine and placebo within each dose group was 3:1 (phase 1) or 5:1 (phase 2). From August 28, 2020, 168 participants were sequentially enrolled and randomly assigned to receive the low dose vaccine, high dose vaccine or placebo with the schedule of 0, 28 days or 0, 14, 28 days in phase 1 trial. From November 18, 2020, 960 participants were randomly assigned to receive the low dose vaccine, high dose vaccine or placebo with the schedule of 0, 21 days or 0, 14, 28 days in phase 2 trial. The most common solicited injection site adverse reaction within 7 days in both trials was pain. The most common solicited systematic adverse reactions within 7 days were fatigue, cough, sore throat, fever and headache. ELISA antibodies and neutralising antibodies increased at 14 days, and peaked at 28 days (phase 1) or 30 days (phase 2) after the last dose vaccination. The GMTs of neutralising antibody against live SARS-CoV-2 at 28 days or 30 days after the last dose vaccination were highest in the adult high dose group (0, 14, 28 days), with 102.9 (95% CI 61.9-171.2) and 102.6 (95% CI 75.2-140.1) in phase 1 and phase 2 trials, respectively. Specific T-cell response peaked at 14 days after the last dose vaccination in phase 1 trial. This vaccine is safe, and induced significant immune responses after three doses of vaccination.
Subject(s)
COVID-19 Vaccines , COVID-19 , Immunogenicity, Vaccine , SARS-CoV-2/immunology , Adolescent , Adult , COVID-19/blood , COVID-19/immunology , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/immunology , Female , Humans , Male , Middle AgedABSTRACT
Human exposure risks to airborne pollutants, bacteria and viruses in confined spaces have attracted tremendous attention. It is a challenge to degrade these harmful materials over a single device by electrical method other than conventional thermal method. We fabricated an air cleaning device based on a conductive Ag-Co3O4 coating with Ag nanoparticles on a glass fibre cloth (GFC). The device possessed good flexibility and high permeability of the GFC. Powered by low-voltages (< 20 V), the device exhibited a 3-fold formaldehyde conversion in its conventional thermal counterpart, and energy savings of > 90% were achieved. The electrically treated device completely killed Escherichia coli and Staphylococcus aureus and SARS-CoV-2 pseudovirus within a few minutes at a low surface temperature of < 50 °C. The excellent efficiency of the devices was attributed to the confinement of electric power to the coating. The device can serve as a flexible filter for air cleaners or conditioners to ensure that human health is maintained amid the pandemic.
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To investigate the duration of humoral immune response in convalescent coronavirus disease 2019 (COVID-19) patients, we conducted a 12-month longitudinal study through collecting a total of 1,782 plasma samples from 869 convalescent plasma donors in Wuhan, China and tested specific antibody response. The results show that positive rate of IgG antibody against receptor-binding domain of spike protein (RBD-IgG) to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the COVID-19 convalescent plasma donors exceeded 70% for 12 months post diagnosis. RBD-IgG kinetics displayed a gradually downward trend, the titer started to stabilize after 9 months and decreased by 68.1% compared with the 1st month. Moreover, male plasma donors produced more RBD-IgG than female plasma donors and patient age positively correlated with the RBD-IgG titer. A strong positive correlation between RBD-IgG and neutralizing antibody titers was also identified. This study is essential for understanding SARS-CoV-2-induced immune memory to develop vaccine and therapeutics.
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COVID-19 , Coronavirus Infections , ConvalescenceABSTRACT
BACKGROUND AND OBJECTIVES: COVID-19-related quarantine and stress have likely escalated the crisis of Internet addiction. This study aimed to determine the impact of the COVID-19 pandemic on Internet use and related risk factors among the general public in China. METHODS: A large-sample cross-sectional online survey was conducted from March 24 to April 30, 2020, in China, and 20,472 participants completed the survey. We investigated the prevalence and severity of Internet addiction based on the Internet Addiction Test (IAT), and explored the risk factors related to increases in time spent on Internet use and severity of Internet addiction, as well as severe Internet addiction. RESULTS: The overall prevalence of Internet addiction was 36.7% among the general population during the pandemic, and that of severe Internet addiction was 2.8%, according to IAT scores. Time spent on recreational Internet use had significantly increased during the pandemic, and almost half of participants reported increases in the severity of Internet addiction. Risk factors for increases in time spent on Internet use and severity of Internet addiction and severe Internet addiction included having fewer social supporters, perceiving pressure and impact on mental health status due to COVID-19, and being over-engaged in playing videogames. DISCUSSION AND CONCLUSIONS: The COVID-19 pandemic adversely impacted Internet use and increased the prevalence and severity of Internet addiction among the general population in China, especially in vulnerable populations. SCIENTIFIC SIGNIFICANCE: This study provides evidence for policymakers to refine public health policies to control the pandemic and make efforts to provide population-specific prevention and interventions for people at risk of developing Internet addiction. (Am J Addict 2021;00:00-00).