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Objectives: To evaluate COVID-19 vaccines in primary prevention against infections and lessening the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai. Method(s): To investigate whether inactivated vaccines were effective in protecting against COVID-19 infections, we estimated the odds ratio (OR) of the vaccination in COVID-19 cases vs. matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied the multivariate stepwise Logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors. Result(s): Out of the 153,544 COVID-19 patients included in the analysis, 118,124 (76.9%) patients had been vaccinated and 143,225(93.3%) were asymptomatic patients. Of the 10,319 symptomatic patients, 10,031(97.2%), 281(2.7%) and 7(0.1%) experienced mild, moderate, and severe infections, respectively. There is no evidence that the vaccination helped protect from infections (OR=0.82, p=0.613). The vaccination, however, offered a small but significant protection against symptomatic infections (RR=0.92, p < 0.001) and halved the risk of moderate/severe infections (OR=0.48, 95% CI: 0.37 - 0.61). Older age (> 60 years) and malignant tumors were significantly associated with moderate/severe infections. Gender also appeared to be a risk factor for symptomatic infections, with females being associated with a lower risk for moderate/severe illness. Conclusion(s): Inactivated COVID-19 vaccines helped provide a small but significant protection against symptomatic infections and halved risk of moderate/severe illness among symptomatic patients. The vaccination was not effective in blocking COVID-19 Omicron variant community spread.Copyright © 2023
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Objectives: This study aimed to determine disease severity, clinical features, clinical outcome in hospitalized patients with the Omicron variant and evaluate the effectiveness of one-dose, two-dose, and three-dose inactivated vaccines in reducing viral loads, disease course, ICU admissions and severe diseases. Method(s): Retrospective cohort analysis was performed on 5,170 adult patients (>=18 years) identified as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction admitted at Shanghai Medical Center for Gerontology between March 2022 and June 2022. COVID-19 vaccination effectiveness was assessed using logistic regression models evaluating the association between the risk of vaccination and clinical outcomes, adjusting for confounders. Result(s): Among 5,170 enrolled patients, the median age was 53 years, and 2,861 (55.3%) were male. 71.0% were mild COVID-19 cases, and cough (1,137 [22.0%]), fever (592 [11.5%]), sore throat (510 [9.9%]), and fatigue (334 [6.5%]) were the most common symptoms on the patient's first admission. Ct values increased generally over time and 27.1% patients experienced a high viral load (Ct value< 20) during their stay. 105(2.0%) of these patients were transferred to the intensive care unit after admission. 97.1% patients were cured or showed an improvement in symptoms and 0.9% died in hospital. The median length of hospital stay was 8.7+/-4.5 days. In multivariate logistic analysis, booster vaccination can significantly reduce ICU admissions and decrease the severity of COVID-19 outcome when compared with less doses of vaccine (OR=0.75, 95%CI, 0.62-0.91, P<=0.005;OR=0.99, 95%CI, 0.99-1.00, p<0.001). Conclusion(s): In summary, the most of patients who contracted SARSCoV-2 omicron variant had mild clinical features and patients with vaccination took less time to lower viral loads. As the COVID-19 pandemic progressed, an older and less vaccinated population was associated with higher risk for ICU admission and severe disease.Copyright © 2023
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The global tourism industry is struggling to recover from the COVID-19 pandemic. During the COVID-19 pandemic, daily tourism forecasting is more critical than ever before in supporting decisions and planning. Considering the changes in tourist psyche and behaviour caused by COVID-19, this study attempts to investigate whether the statistical modelling methods can work reliably under the new normal when travel restrictions are eased or lifted. To this end, we first compare the predictivity of daily tourism demand data before and during COVID-19, and observe heterogeneous impacts across different geographical scales. Then an improved multivariate & multiscale decomposition-ensemble framework is proposed to forecast daily tourism demand. The empirical study indicates the superiority and practicability of the proposed framework before and during COVID-19. Finally, we call for more research on the comparability of tourism demand forecasting.
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Incidences of major feline viral diseases provide basic information for preventing viral disease in cats. Despite the growing interest in feline viral diseases, sero-surveillances have been lacking. In this study, we analyzed the diagnoses of feline viral diseases and conducted a sero surveillance of feline panleukopenia virus (FPV), feline calicivirus (FCV), feline herpesvirus-1 (FHV-1), and feline infectious peritonitis virus (FIPV) in Korean cats. Of the 204 confirmed cases since 2015, the numbers of diagnoses for FPV, FIPV, FCV, feline influenza virus, and FHV-1 were 156, 32, 12, 3, and 1 case, respectively. In total, 200 sera, collected between 2019 and 2021, were screened for the presence of antibodies against FPV, 2 FCVs, FHV-1, and FIPV using a hemagglutination inhibition test and a virus-neutralizing assay (VNA). The overall seropositive rates in cats tested for FPV, the 2 FCVs, FHV-1, and FIPV were 92.5%. 42.0%, 37.0%, 52.0%, and 14.0%, respectively. A low correlation (r = 0.466) was detected between the VNA titers of 2 FCV strains. The highest incidence and seropositive rate of FPV reveal that FPV is circulating in Korean cats. The low r-value between 2 FCVs suggests that a new feline vaccine containing the 2 kinds of FCVs is required.
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Prurigo nodularis (PN) is a chronic inflammatory skin disease characterized by severe itching accompanied by multiple nodules throughout the body. There is currently no efective drug-targeted treatment for PN. Dupilumab is a fully human monoclonal antibody which can suppress the Th2 inflammatory reaction. We aimed to assess the efficacy and safety of dupilumab in PN. There were 29 PN patients who received dupilumab treatment for four months. Serum total immunoglobulin E (Ig E), eosinophil counts, dermatology life quality index (DLQI), and numeric rating scale (NRS) were assessed on patients before and after treatment. We count the vaccination of novel coronavirus pneumonia (COVID-19) in patients and the impact on PN and treatment measures after vaccination. Plotting was performed using GraphPad Prism8, and the statistical analysis was performed using PASW Statistics18. The eosinophil counts in patients higher decreased to normal, and the Ig E levels gradually decreased and tended to normal levels after receiving dupilumab injection. The average DLQI score at the baseline was 23.93 +/- 0.66 and decreased to 11.66 +/- 0.55 (P < 0.01) and 1.83 +/- 0.22 (P < 0.01) at 1-month and 6-monthfollow-up of treatment, respectively. The average NRS score at the baseline was 9.79 +/- 0.08 and decreased to 3.52 +/- 0.23 (P < 0.01) and 0.31 +/- 0.15 (P < 0.01) at the 1-month and 6monthfollow-up of treatment, respectively. Our study shows that dupilumab has achieved good efficacy in PN with few adverse reactions and high safety. We can recommend that patients follow the advice of specialists to be vaccinated and under the condition of stable disease, separated from dupilumab treatment for one week.
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Understanding the space–time pattern of the transmission locations of COVID-19, as well as the relationship between the pattern, socioeconomic status, and environmental factors, is important for pandemic prevention. Most existing research mainly analyzes the locations resided in or visited by COVID-19 cases, while few studies have been undertaken on the space–time pattern of the locations at which the transmissions took place and its associated influencing factors. To fill this gap, this study focuses on the space–time distribution patterns of COVID-19 transmission locations and the association between such patterns and urban factors. With Hong Kong as the study area, transmission chains of the four waves of COVID-19 outbreak in Hong Kong during the time period of January 2020 to June 2021 were reconstructed from the collected case information, and then the locations of COVID-19 transmission were inferred from the transmission chains. Statistically significant clusters of COVID-19 transmission locations at the level of tertiary planning units (TPUs) were detected and compared among different waves of COVID-19 outbreak. The high-risk areas and the associated influencing factors of different waves were also investigated. The results indicate that COVID-19 transmission began with the Hong Kong Island, further moved northward towards the New Territories, and finally shifted to the south Hong Kong Island, and the transmission population shows a difference between residential locations and non-residential locations. The research results can provide health authorities and policy-makers with useful information for pandemic prevention, as well as serve as a guide to the public in the avoidance of activities and places with a high risk of contagion. © 2023 by the authors.
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Objective: Exploring the disinfection effect of high-pressure carbon dioxide (HPCD) on human coronavirus 229E (hCoV-229E). Methods: The human coronavirus 229E (hCoV-229E) was treated by HPCD at different temperatures (10, 25, and 37 ℃) and pressures (6.3 and 10 MPa) for different time (15 and 30 min). Result: Compared with the control groups under the corresponding temperatures, the virus titer in 50 mL tube treated with HPCD at 10 ℃ and 6.3 MPa for 30 min was significantly decreased (P<0.05). The virus titer was also significantly reduced after treatment with HPCD at 37 ℃ and 10 MPa for 15 min (P<0.01). Moreover, the virus titers inoculated on the surfaces of salmon meat, shrimp shell, and polyethylene packing materials were all significantly decreased after HPCD treatment at 37 ℃ and 10 MPa for 15 min as compared with the corresponding control groups (P<0.05). Conclusion: HPCD treatment at 37 ℃ and 10 MPa for 15 minutes could effectively disinfect hCoV-229E on the surface of food (salmon meat and shrimp shell) and polyethylene packaging materials. © 2023, Editorial Department of Science and Technology of Food Science. All rights reserved.
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In this interview, Prof. Lin Lu introduced ways to improve sleep and relieve stress, influences of sleep on the heart and mental health, essential qualities of psychiatrists, etc. His major viewpoints are: (a) sleep deprivation disrupts physiological functions, (b) prevalence of mental health problems in the general population, health-care workers, and students showed an increasing trend following COVID-19, and (c) it is a tendency for doctors to develop a comprehensive and integrated treatment plan from the physical and mental perspectives. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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Research on student engagement has recently gained popularity as it can address problems such as early dropout and poor achievement. The growing interest in investigating student engagement during the Covid-19 pandemic is reflected in increased publications addressing this topic. However, no review provided research evidence and an overview of existing literature on student engagement during emergency remote teaching (ERT). We reviewed how student engagement studies were undertaken during ERT from three perspectives: (1) the landscape of studies, (2) methodologies issues, and (3) the strategies used to facilitate student engagement. 42 articles were analysed from an initial pool of 436 search results. The findings illustrate that current studies were predominately undertaken in the United States (36%) and China (22%) with focusing on STEM subjects as a dominant discipline. The literature was largely inconsistent in defining and measuring student engagement. In addition, the majority of studies (57%) investigated students' engagement from the perspective of students, unlike other stakeholders. The most prominent finding is that ERT promoted several important engagement strategies, including motivational factors, teachers' facilitation, a hybrid learning model, and using learning technologies to boost students' engagement. © 2023, The Author(s).
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This study explored the effect of perceived social isolation on the mental health of college students during the high-risk period of COVID-19 transmission in Hubei, China and the role of social support from online friends in alleviating this effect. The questionnaire responses of 213 college students from four universities in Hubei were included. Measurement and structural models were constructed using structural equation modeling. The findings revealed that perceived social isolation while under home quarantine was a negative predictor of the mental health of college students in Hubei. Low social support from online friends may lead to a relatively strong relationship between perceived social isolation and mental health in these college students, whereas high social support from online friends may lead to a relatively weak relationship between perceived social isolation and mental health. © 2023, Tech Science Press. All rights reserved.
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OBJECTIVES: To assess emergency department (ED) presentation numbers in Queensland during the coronavirus disease 2019 (COVID-19) pandemic to mid-2021, a period of relatively low COVID-19 case numbers. DESIGN: Interrupted time series analysis. SETTING: All 105 Queensland public hospital EDs. MAIN OUTCOME MEASURES: Numbers of ED presentations during the COVID-19 lockdown period (11 March 2020 - 30 June 2020) and the period of easing restrictions (1 July 2020 - 30 June 2021), compared with pre-pandemic period (1 January 2018 - 10 March 2020), overall (daily numbers) and by Australasian Triage Scale (ATS; daily numbers) and selected diagnostic categories (cardiac, respiratory, mental health, injury-related conditions) and conditions (stroke, sepsis) (weekly numbers). RESULTS: During the lockdown period, the mean number of ED presentations was 19.4% lower (95% confidence interval, -20.9% to -17.9%) than during the pre-pandemic period (predicted mean number: 5935; actual number: 4786 presentations). The magnitudes of the decline and the time to return to predicted levels varied by ATS category and diagnostic group; changes in presentation numbers were least marked for ATS 1 and 2 (most urgent) presentations, and for presentations with cardiac conditions or stroke. Numbers remained below predicted levels during the 12-month post-lockdown period for ATS 5 (least urgent) presentations and presentations with mental health problems, respiratory conditions, or sepsis. CONCLUSIONS: The COVID-19 pandemic and related public restrictions were associated with profound changes in health care use. Pandemic plans should include advice about continuing to seek care for serious health conditions and health emergencies, and support alternative sources of care for less urgent health care needs.
Subject(s)
COVID-19 , Stroke , Humans , Pandemics , Queensland , Interrupted Time Series Analysis , Communicable Disease Control , Emergency Service, Hospital , Stroke/epidemiology , Retrospective StudiesABSTRACT
The COVID-19 pandemic piqued interest in remote work, but research yields mixed findings on the impact of working from home on workers' well-being and job attitudes. The authors develop a conceptual distinction between working from home that occurs during regular work hours (replacement work-from-home) and working from home that occurs outside of those hours (extension work-from-home). Using linked establishment-employee survey data from Germany, the authors find that extension work-from-home is associated with lower psychological well-being, higher turnover intentions, and higher work-to-family and family-to-work conflicts. By contrast, replacement work-from-home is associated with better well-being and higher job satisfaction, but higher work-to-family conflict. Extension work-from-home has more negative effects for women's well-being and work-to-family conflict. This distinction clarifies the conditions under which remote work can have positive consequences for workers and for organizations. © The Author(s) 2023.
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Objective: Exploring the disinfection effect of high-pressure carbon dioxide (HPCD) on human coronavirus 229E (hCoV-229E). Methods: The human coronavirus 229E (hCoV-229E) was treated by HPCD at different temperatures (10, 25, and 37 ℃) and pressures (6.3 and 10 MPa) for different time (15 and 30 min). Result: Compared with the control groups under the corresponding temperatures, the virus titer in 50 mL tube treated with HPCD at 10 ℃ and 6.3 MPa for 30 min was significantly decreased (P<0.05). The virus titer was also significantly reduced after treatment with HPCD at 37 ℃ and 10 MPa for 15 min (P<0.01). Moreover, the virus titers inoculated on the surfaces of salmon meat, shrimp shell, and polyethylene packing materials were all significantly decreased after HPCD treatment at 37 ℃ and 10 MPa for 15 min as compared with the corresponding control groups (P<0.05). Conclusion: HPCD treatment at 37 ℃ and 10 MPa for 15 minutes could effectively disinfect hCoV-229E on the surface of food (salmon meat and shrimp shell) and polyethylene packaging materials. © 2023, Editorial Department of Science and Technology of Food Science. All rights reserved.
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Keeping track of scientific challenges, advances and emerging directions is a fundamental part of research. However, researchers face a flood of papers that hinders discovery of important knowledge. In biomedicine, this directly impacts human lives. To address this problem, we present a novel task of extraction and search of scientific challenges and directions, to facilitate rapid knowledge discovery. We construct and release an expert-annotated corpus of texts sampled from full-length papers, labeled with novel semantic categories that generalize across many types of challenges and directions. We focus on a large corpus of interdisciplinary work relating to the COVID-19 pandemic, ranging from biomedicine to areas such as AI and economics. We apply a model trained on our data to identify challenges and directions across the corpus and build a dedicated search engine. In experiments with 19 researchers and clinicians using our system, we outperform a popular scientific search engine in assisting knowledge discovery. Finally, we show that models trained on our resource generalize to the wider biomedical domain and to AI papers, highlighting its broad utility. We make our data, model and search engine publicly available.
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Objective: Exploring the disinfection effect of high-pressure carbon dioxide (HPCD) on human coronavirus 229E (hCoV-229E). Methods: The human coronavirus 229E (hCoV-229E) was treated by HPCD at different temperatures (10, 25, and 37 ℃) and pressures (6.3 and 10 MPa) for different time (15 and 30 min). Result: Compared with the control groups under the corresponding temperatures, the virus titer in 50 mL tube treated with HPCD at 10 ℃ and 6.3 MPa for 30 min was significantly decreased (P<0.05). The virus titer was also significantly reduced after treatment with HPCD at 37 ℃ and 10 MPa for 15 min (P<0.01). Moreover, the virus titers inoculated on the surfaces of salmon meat, shrimp shell, and polyethylene packing materials were all significantly decreased after HPCD treatment at 37 ℃ and 10 MPa for 15 min as compared with the corresponding control groups (P<0.05). Conclusion: HPCD treatment at 37 ℃ and 10 MPa for 15 minutes could effectively disinfect hCoV-229E on the surface of food (salmon meat and shrimp shell) and polyethylene packaging materials. © 2023, Editorial Department of Science and Technology of Food Science. All rights reserved.
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The purpose of this paper is to explore the role of knowledge-based dynamic capabilities in national innovation systems in the achievement of sustainable development goals, employing an empirical approach in the context of the unprecedented COVID-19 crisis. Based on data from 130 sample countries, we analyzed the impact of knowledge-based dynamic capabilities on the achievement of sustainable development goals using PLS-SEM. In particular, we considered the differences in the impact of knowledge-based dynamic capabilities on the achievement of sustainable development goals at different stages of economic development. The results show that knowledge-based dynamic capabilities have a positive impact on the achievement of sustainable development goals, while their compositional dimensions have a dual impact, both direct and indirect. In addition, knowledge-based dynamic capabilities have different impacts on the achievement of sustainable development goals at different stages of economic development. This indicates that a country's economic development level will affect the relationship between knowledge-based dynamic capabilities and the achievement of sustainable development goals. However, it also means that there is a more complex relationship between these capabilities and the achievement of the goals. This study offers a new perspective for sustainable development research, adds new insights to the theory of linking knowledge-based dynamic capabilities to the achievement of sustainable development goals, and provides a measurement standard for the impact of those capabilities on the goals. © 2023 The Authors
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Since the COVID-19 pandemic, businesses have faced unprecedented challenges when trying to remain open. Because COVID-19 spreads through aerosolized droplets, businesses were forced to distance their services;in some cases, distancing may have involved moving business services online. In this work, we explore digitization strategies used by small businesses that remained open during the pandemic, and survey/interview small businesses owners to understand preliminary challenges associated with moving online. Furthermore, we analyze payments from 400K businesses across Japan, Australia, United States, Great Britain, and Canada. Following initial government interventions, we observe (at minimum for each country) a 47% increase in digitizing businesses compared to pre-pandemic levels, with about 80% of surveyed businesses digitizing in under a week. From both our quantitative models and our surveys/interviews, we find that businesses rapidly digitized at the start of the pandemic in preparation of future uncertainty. We also conduct a case-study of initial digitization in the United States, examining finer relationships between specific government interventions, business sectors, political orientation, and resulting digitization shifts. Finally, we discuss the implications of rapid & widespread digitization for small businesses in the context of usability challenges and interpersonal interactions, while highlighting potential shifts in pre-existing social norms. © 2022 Owner/Author.
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Given the differences of command and control (C2) activities between the field command center and the emergency operations center (EOC), this article combined the edge C2 theory with the parallel C2 theory, and proposed a parallel incident C2 mode based on the observe–orient–decide–act (OODA) loop and planning–readiness–execution–assessment (PREA) loop. The aim is to build up a PREA loop-based parallel incident C2 mode and its related operating mechanism of edge empowerment and energy release in parallel incident C2 mode. The parallel incident C2 mode based on the PREA loop and OODA loop supports the co-existence and connection of the two roles of the incident C2 agent at the emergency scene. The two roles are the executive role of emergency response and operation and the command and organization role of the edge emergency system. This article initiates a deep integration of two different C2 process mechanisms in the emergency response and operation process, taking into account the local emergency scene and the global emergency system. Taken together, a key issue has been well addressed regarding the contradiction that the traditional emergency response cannot be reconciled in terms of rapidity and thoroughness. Author
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The COVID-19 (SARS-CoV-2) pandemic has become an urgent issue and attracted extensive attention all over the world due to its strong infectivity and high mortality. The outbreak of COVID-19 has a negative impact on the development of the world economy, brought inconvenience to people's daily life and threatened our health safety. Considering the global spread of COVID-19 disease with the tremendous number of infections and also deaths, understanding the transmission modes of this virus to formulate effective prevention and control strategies is of vital importance. This paper reviews three main transmission routes (contact, droplet and aerosol) and three possible transmission routes (maternal-infant, fecal-oral and cross-species) of COVID-19, which has reference value and guiding significance for the prevention and control of COVID-19 in the future. © 2022 ACM.
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Federated learning (FL) is a distributed machine learning technique that enables collaborative model training while avoiding explicit data sharing. The inherent privacy-preserving property of FL algorithms makes them especially attractive to the medical field. However, in case of heterogeneous client data distributions, standard FL methods are unstable and require intensive hyperparameter tuning to achieve optimal performance. Conventional hyperparameter optimization algorithms are impractical in real-world FL applications as they involve numerous training trials, which are often not affordable with limited compute budgets. In this work, we propose an efficient reinforcement learning (RL)-based federated hyperparameter optimization algorithm, termed Auto-FedRL, in which an online RL agent can dynamically adjust hyperparameters of each client based on the current training progress. Extensive experiments are conducted to investigate different search strategies and RL agents. The effectiveness of the proposed method is validated on a heterogeneous data split of the CIFAR-10 dataset as well as two real-world medical image segmentation datasets for COVID-19 lesion segmentation in chest CT and pancreas segmentation in abdominal CT. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.