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Objective:To explore the differences in laboratory indicators test results of coronavirus disease 2019 (COVID-19) and influenza A and to establish a differential diagnosis model for the two diseases, and to clarify the clinical significance of the model for distinguishing the two diseases. Methods :A total of 56 common COVID-19 patients and 54 influenza A patients were enrolled , and 24 common COVID-19 patients and 30 influenza A patients were used for model validation. The average values of the laboratory indicators of the patients 5 d after admission were calculated,and the elastic network model and the stepwise Logistic regression model were used to screen the indicators for identifying COVID-19 and influenza A. Elastic network models were used for the first round of selection,in which the optimal cutoff of lambda was chosen by performing 10-fold cross validations. With different random seeds,the elastic net models were fit for 200 times to select the high-frequency indexes ( frequency>90% ). A Logistic regression model with AIC as the selection criterions was used in the second round of screening uses;a nomogram was used to represent the final model;an independent data were used as an external validation set,and the area under the curve (AUC) of the validation set were calculate to evaluate the predictive the performance of the model. Results:After the first round of screening, 16 laboratory indicators were selected as the high-frequency indicators. After the second round of screening,albumin/ globulin (A/G),total bilirubin (TBIL) and erythrocyte volume (HCT) were identified as the final indicators. The model had good predictive performance , and the AUC of the verification set was 0. 844 (95% CI:0. 747-0. 941). Conclusion:A differential diagnosis model for COVID-19 and influenza A based on laboratory indicators is successfully established,and it will help clinical and timely diagnosis of both diseases.Copyright © 2022 Jilin University Press. All rights reserved.
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With the upgrading and innovation of the logistics industry, the requirements for the level of transportation smart technologies continue to increase. The outbreak of the COVID-19 has further promoted the development of unmanned transportation machines. Aimed at the requirements of intelligent following and automatic obstacle avoidance of mobile robots in dynamic and complex environments, this paper uses machine vision to realize the visual perception function, and studies the real-time path planning of robots in complicated environment. And this paper proposes the Dijkstra-ant colony optimization (ACO) fusion algorithm, the environment model is established by the link viewable method, the Dijkstra algorithm plans the initial path. The introduction of immune operators improves the ant colony algorithm to optimize the initial path. Finally, the simulation experiment proves that the fusion algorithm has good reliability in a dynamic environment. © 2022 IEEE.
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Coronavirus disease 2019 (COVID-19), as a public health emergency, is a serious threat to human health. Cancer patients have a high risk of being infected with COVID-19. As one of important means of cancer treatment, radiotherapy has become an important alternative to surgery during the epidemic of COVID-19. The radiotherapy department of Peking Union Medical College Hospital ensured the smooth development of radiotherapy work on the setup of prevention and control systems for COVID-19 by establishing admission strategies for cancer patients, disinfection, isolation, daily management measures, scientific exploration, and clinical practice. In this paper, the associated strategies are summarized and analyzed, which can provide experience and reference for radiotherapy treatment under public health emergencies.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
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Urbanization is essential for human development and progress. Therefore, it is urgent to study urban public open space (POS) under the dual impact of urbanization construction and the global COVID-19 outbreak. Bibliometric visual analysis is currently popular in academia, as it can be used to analyze specific fields. This research summarizes the development history, hotspots, and trends in POS, with theoretical and data support based on the Web of Science (WoS) Core Collection. The study period was from 2002 to 2022. A total of 398 papers were collected, with the number of papers increasing over time. The research covers various fields, including environment, architecture, ecology, geography, design, behavior, etc. The results show that POS research hotspots include form layout, social value, and sustainable renewal. This paper demonstrates that there is a lack of vitality in urban POS. Although affected by the COVID-19 pandemic, the fundamental reason for this is that the vitality of POS is not created from multiple dimensions. Vitality should be enhanced according to the space's terrain, ecology, environment, and other factors. POS research lacks crossdisciplinary collaboration and the fusion of multiple fields. Thus, cooperation between the various disciplines involved must be strengthened. In the future, POS research should change its design concept, continue to place the "human" in the leading position, establish a multidisciplinary research system, use local empirical cases, and develop applicable theories that can be extended upon. Thus, it will be possible to build harmonious open spaces that enhance the relationship between the people and the land and provide practical solutions for other countries in which urbanization is advancing.
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During the global efforts to prevent and control the COVID-19 pandemic, extensive research and development of SARS-CoV-2 vaccines using various technical approaches have taken place. Among these, vaccines based on adenovirus vector have gained substantial knowledge and experience in effectively combating potential emerging infectious diseases, while also providing novel ideas and methodologies for vaccine research and development (R&D). This comprehensive review focuses on the adenovirus vector technology platform in vaccine R&D, emphasizing the importance of mucosal immunity induced by adenoviral vector-based vaccine for COVID-19 prevention. Furthermore, it analyzes the key technical challenges and obstacles encountered in the development of vaccines based on the adenovirus vector technology platform, with the aim of providing valuable insights and references for researchers and professionals in related fields.
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Background: Coronavirus disease 2019 (COVID-19) had been a stronger hit in Deep South compared with other developed regions in the United States, and vaccination remains a top priority for all eligible individuals. However, there are limited data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age group, which is of critical importance for future vaccine planning. Racial/ethnic disparities were found in the COVID-19 vaccination, but the vast majority of evidence was generated from studies at the individual level. There is an urgent need for evidence at the population level to reveal and evaluate the booster coverage in racial/ethnic minority communities, which could identify vulnerable communities and inform future healthcare policymaking and resource allocation. We evaluated county-level COVID-19 booster coverage by age group in the Deep South and examined its relationship with residential segregation. Method(s): We conducted an ecological study at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of five Deep South states from December 15, 2021 to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster coverage by age group (e.g., 12 to 17 years old, 18 to 64 years old, and at least 65 years old) by the end of the study period. We examined the longitudinal relationships between residential segregation, interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson mixed model. Result(s): As of October 19, 2022, among the 418 counties, the median percentage of booster coverage was 40% (interquartile range [IQR]: 37.8-43.0%). Compared with elders, youth and adults had lower percentages of booster uptake. There was geospatial heterogeneity in the COVID-19 booster coverage. Results of the Poisson mixed model found that as time increased, higher segregated counties had lower percentages of booster coverage. Such relationships were consistent across the age groups. Conclusion(s): The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccine planning should focus on youth and adults. Healthcare facilities and resources are needed in racial/ethnic minority communities. Residential segregation and COVID-19 booster coverage by age group in the 418 counties across the five Deep South states from December 15, 2021 to October 19, 2022.
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Objective To explore the application value of Biofire Filmarry pneumonia panel (PN) in detection of secondary and concomitant pathogen among critically ill patients with coronavirus disease 2019(COVID-19). Methods We consecutively included and analyzed the clinical data of critically ill patients with COVID-19 transferred to the ICU from February to April 2020 in the Sino-French Campus of Wuhan Tongji Hospital. Samples of Bronchoalveolar lavage fluid obtained by bedside bronchoscopy were sent for Biofire Filmarray PN and standard culture concomitantly. We compared the results of two methods and evaluated their concordance. Results In total, 21 critically ill patients with COVID-19 were included and 54 samples were tested, including 33 (61.1%) Biofire Filmarray PN tests (21 patients) and 21 (38.9%) standard cultures (14 patients), in which 19 pairs (38 samples) underwent both tests simultaneously. In Biofire Filmarray PN group, the turnaround time was about 1 hour. There were 74 positive results in 32 samples (97.0%) from 20 patients, including 29 cases(39.2%) of Acinetobacter baumannii complex, 21 cases (28.4%) of Pseudomonas aeruginosa, 16 cases (21.6%)of Klebsiella pneumoniae, 5 cases (6.8%) of Escherichia coli, 1 case (1.4%)each of Enterobacter cloacae, Haemophilus influenzae, and respiratory syncytial virus. In the standard culture group, the turnaround time was about 3 days. 19 positive results returned in 16 (76.2%) samples from 11 patients, including 8 cases (42.1%) of Pseudomonas aeruginosa, 6 cases (31.6%) of Acinetobacter baumannii, 4 cases (21.1%) of Stenotrophomonas malt and 1 case (5.3%) of Myxobacterium. Among the 19 pairs of "back-to-back" specimens, 15 pairs were concordant, and the agreement ratio was 78.9%. Conclusions Acinetobacter baumannii and Pseudomonas aeruginosa may be the common pathogens of secondary or concomitant infection in critically ill patients with COVID-19. Biofire Filmarray PN is a rapid diagnostic test and has application value in such patients;its sensitivity and accuracy require further investigation with larger sample sizes.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
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It has been more than two years since the outbreak of COVID-19, which has spread to almost every corner of the world and killed a great number of people. Rapid detection and screening have become an important means of controlling the spread of COVID-19. Segmentation of COVID-19 infected tissue from computed tomography (CT) images of a patient’s lungs can provide clinicians with important information to quantify and diagnose COVID-19. However, the accuracy of medical image segmentation is seriously affected by such factors as the low contrast between the infected tissue and the edge of the surrounding environment, the large variation of the infected tissue and the lack of labeling data. Therefore, a deep learning model called CdcSegNet to accurately segment lung lesions from CT images infected by COVID-19 is proposed. In our method, transfer learning is introduced to solve the problem of lack of annotation data, and three modules, i.e., continuous dilated convolution module (CDC), parallel dual attention module (PDA) and additional multi-core pooling layer (AMP) are innovatively proposed to solve the problem of fuzzy segmentation boundary and to segment effectively infected tissues. Extensive experiments and comparison studies are made, and demonstrate that our model CdcSegNet has high accuracy in COVID-19 segmentation, and is superior to the state-of-the-art models in terms of DICE, SEN, SPE, PPV, and VOE. IEEE
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The recent outbreak of novel coronavirus has highlighted the need for a benefit-cost framework to guide unconventional public health interventions aimed at reducing close contact between infected and susceptible individuals. In this paper, we propose an optimal control problem for an infectious disease model, wherein the social planner can control the transmission rate by implementing or lifting lockdown measures. The objective is to minimize total costs, which comprise infection costs, as well as fixed and variable costs associated with lockdown measures. We establish conditions concerning model primitives that guarantee the existence of a straightforward optimal policy. The policy specifies two switching points (Formula presented.), whereby the social planner institutes a lockdown when the percentage of infected individuals exceeds (Formula presented.), and reopens the economy when the percentage of infected individuals drops below (Formula presented.). We subsequently extend the model to cases where the social planner may implement multiple lockdown levels. Finally, numerical studies are conducted to gain additional insights into the value of these controls. © 2023 Wiley Periodicals LLC.
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Particulate air pollution represented by PM2.5 is one of the biggest environmental challenges in the 21st century. Especially in 2020, the global outbreak of COVID-19 has brought new challenges to melt-blown filter materials, such as the attenuation of filtration efficiency with breathing, even no filtration effect for viruses as their smaller diameter, the sharp decline of filter efficiency after oily filtration cycle, and its limit in some explosive occasions. Here, using the diameter difference of polystyrene (PS), polyvinylidene fluoride (PVDF) and nylon 6(PA6) fibers, we report a multistage structure nanofiber membrane (PS/PVDF/PA6&Ag MSNMs) with high efficiency, low resistance and antibacterial effect by constructing gradient pore structure and introducing silver nanoparticles (Ag NPs), overcoming the above defects. The average filtration efficiency of PS/PVDF/PA6&Ag MSNMs for diisooctyl sebacate (DEHS) monodisperse particles from 0.2 μm to 4.9 μm was 99.88%, and the pressure drop was only 128 Pa. After repeated circulation for 100 times, the filtration efficiency and pressure drop remained stable. Above all, the antibacterial nanofiber membrane with high efficiency and low resistance has been preliminarily constructed, the future research will further focus on the performance after circulation. © 2023 Elsevier Ltd
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Introduction (contexte de la recherche): In Parts A and B of the 3-part phase 3 LIBERTY EoE TREET study (NCT03633617), dupilumab 300 mg weekly (DPL qw) vs. placebo (PBO) demonstrated significant efficacy and acceptable safety up to 24 weeks (wks) in adults and adolescents with eosinophilic esophagitis (EoE). For patients (pts) who completed Parts A or B, Part C was an extended active treatment period for 28 wks. Objectif: To assess the safety and efficacy of DPL in pts who completed Part B and continued to Part C, up to 52 wks. Methodes: Of 80 DPL qw pts in Part B, 74 continued DPL qw in Part C (DPL/DPL). Of 79 PBO pts in Part B, 37 pts received DPL qw in Part C (PBO/DPL). Part B co-primary endpoints were proportion of pts achieving peak esophageal intraepithelial eosinophil (eos) count <= 6 eos/high power field (hpf) and absolute change from Part B baseline (BL) in Dysphagia Symptom Score (DSQ) score at Wk 24. Secondary endpoints included peak eos count, EREFS, and HSS grade and stage scores. In Part C, all co-primary and secondary endpoints were assessed at Wk 52 as secondary endpoints. Safety was also assessed. Resultats: Part B BL characteristics were similar across groups. At Wk 52 of Part C, 84.6% of DPL/DPL and 67.6% of PBO/DPL groups achieved peak eos count of <= 6 eos/hpf and mean (SD) absolute change from Part B BL in DSQ score was -30.26 (15.39) for DPL/DPL and -27.25 (11.46) for PBO/DPL pts. At Wk 52, peak eos count, EREFS, HSS grade and stage scores were reduced, compared with Part B BL, and EDP and T2 NESs were suppressed in DPL/DPL and PBO/DPL groups. Dupilumab demonstrated an acceptable safety profile in Part C;the most common (occurring >= 10%) treatment-emergent adverse events in DPL/DPL and PBO/DPL groups were injection-site reactions (13.5% and 10.8%), COVID-19 (9.5% and 10.8%) and nasopharyngitis (4.1% and 10.8%). Conclusion(s): As observed in Part A/C, dupilumab qw demonstrated persistent improvements in clinical, symptomatic, histologic, endoscopic and molecular features of EoE up to 52 wks and had an acceptable safety profile. PBO pts from Part B who received dupilumab in Part C showed similar efficacy to dupilumab qw pts of Part B.Copyright © 2023
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Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-cardiology Group, College of Cardiovascular Physicians of Chinese Medical Doctor Association, and Hypertension Group of the Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of two parts. The sections of Part A include (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis. The sections of Part B contain (IV) Treatment recommendations, and (V) Prospects. This article presents Part B of the consensus. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-Cardiology Group of College of Cardiovascular Physicians of Chinese Medical Doctor Association and Hypertension Group of Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of Part A and Part B. Part A includes (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis and Part B includes (IV) Treatment recommendations and (V) Prospects. This part presents the content of Part A. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
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The COVID-19 pandemic has hit the transportation sector hard;particularly air transportation, as a major mode of long-distance transportation, has been affected tremendously. Since the dawn of COVID-19, politicians and policy makers have discussed the idea of introducing travel bubbles between countries (or counties), to allow for a continued exchange of people and goods. The eponymous Trans-Tasmanian travel bubble is a major example, involving quarantine-free travel between Australia and New Zealand. While both countries have tried to form a travel bubble various times, recurring setbacks and difficulties were faced. In October 2021, this ambitious project presumably has come to an end, with both countries announcing the essential capitulation of their COVIDZero strategies and a planned opening towards broader international travel. In this study, we perform a close investigation of the history behind the Trans-Tasmanian travel bubble as an on-off relationship, identifying a set of drivers for the serious problems involving a sustainable setup and operation. We develop a framework which represents important factors for successful travel bubbles and believe that the satisfaction of all factors at once is extremely challenging. Our results and insights are not specific to the Trans-Tasmanian case only, although it is taken as a running example, but can be generalized to various scales and environments. We hope that our study contributes to the literature by improving our understanding of the highly buzzed travel bubble concept, while providing empirical evidence for the troubles that inherently make such bubbles a tightrope walk. © 2022 The Authors
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The new energy industry is crucial for solving the problem of pollution, and its development requires support from the stock market. This paper proposes a Chinese investor sentiment index based on the Long Short-Term Memory (LSTM) deep learning method, and investigates the effect of investor sentiment on new energy stock returns as well as value at risks (VaR) behavior before and during COVID-19. It also compares these effects on traditional energy companies to identify differences between the new energy and traditional companies. The empirical results show that investor sentiment has significant effects on stock returns and VaR of both new and traditional energy companies but the effects are stronger in the new energy industry. The effects of investor sentiment have increased during COVID-19, and investors pay more attention on risks than returns during COVID-19. These results provide guidance for small and medium-sized investors in China to optimize their investment strategies and alleviate losses associated with extreme risks. © 2022 Elsevier Inc.
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There is an ongoing debate regarding the economic consequences of public policies designed to curb public health crises, such as the COVID-19 pandemic. Many opponents of such policies claim that their economic costs may outweigh their health benefits. In this paper, we use synthetic control analysis to determine the impact of stay-at-home orders on weekly new jobless claims during the initial phase of the COVID-19 pandemic. Our analysis reveals that while new jobless claims spike following the stay-at-home orders, similar spikes are observed within our synthetic control. Specifically, we find that stay-at-home orders account for only 32 percent of the increase in new jobless claims, with the majority of the increase being driven by factors outside of the policy, such as the general spread of the virus and waning consumer confidence. © 2022, Academy of Economics and Finance.
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Hospital ward is one of non-negligible potential places to occur cross-infection among patients and health workers. Air-borne transmission was regarded as the main infection route of the SARS-CoV-2. Preventing the air-borne transmission should be a significant measure, which could effectively mitigate the risk of the virus infection. Based on those consideration, in this study, the influence of different types of air distribution on ventilation effectiveness was modeled through Computational Fluid Dynamics (CFD) simulations. Several typical negative pressure wards same as the ward in Wuhan Thunder God Mountain hospital and conformed to the Chinese National Health Commission (NHC) guidelines were modelled. We simulated the influence of different locations of air supply inlets, analysed the influence of the buffer door and compared the contaminant concentration on different entry route for health workers. The results show that the air distribution required by NHC guidelines could retain a directional airflow from the bed-zone to the toilet, which also has a better accessibility of supply air, and health workers are safer to avoid standing closed to the air exhaust outlet in the downstream area of pollutants during ward rounds. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)
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The spread of COVID-19 has greatly threatened human health and economic growth. Angiotensin-converting enzyme 2 (ACE2) is a receptor for severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). By attaching to ACE2, SARS-COV-2 reduces its expression and induces lung injury. Vitamin D can inhibit the progression of COVID-19 by inhibiting the activity of ROCK pathway, up-regulating ACE2 expression and bio-availability, and slowing down the adverse reactions caused by Ang II accumulation. This study explored a novel mechanism, i.e., vitamin D protects against COVID-19-induced injury by upregulating ACE2 expression. It provides theoretical guidance for the role of Vitamin D in the prevention and treatment of COVID-19. Copyright © 2022 Chinese Journal of Clinical Pharmacology and Therapeutics. All rights reserved.
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The subprime crisis and the COVID-19 crisis have severely impacted the development of global financial stability, which arouses scholars' thinking about the financial risk. Clarifying the contagion mechanism and spatial spillover effect of financial risk under the subprime crisis and the COVID-19 crisis is of great significance for preventing and controlling financial risk. This paper explores and compares the main contagion mechanism, contagion channels, and spatial spillover effects of financial risk during the subprime crisis and the COVID-19 crisis by using the dynamic Spatial Dubin Model. The results show that the transnational contagion mechanism of financial risk during the subprime crisis is the monsoon effect. The inflation rate has a positive spatial spillover effect on financial risk. During the COVID-19 crisis, the transnational contagion mechanism of financial risk is the spillover effect. Net exports and stock market returns have positive spatial spillover effects on financial risk. Financial risk is mainly transmitted across borders through commodity prices during the subprime crisis, while during the COVID-19 crisis, it's through trade exchanges and financial capital flows. In addition, the spatial contagion intensity of financial risks during the COVID-19 crisis is higher than during the subprime crisis. This paper provides experience and reference for countries to formulate financial risk prevention plans. © 2022 ACM.