ABSTRACT
Coronavirus disease 2019(COVID-19) poses a challenge to hospitals for the prevention and control of public health emergencies. As the main battlefield of preventing and controlling COVID-19, large public hospitals should develop service protocols of diagnosis and treatment for outpatient, emergency, hospitalization, surgery, and discharge. The construction of medical protocols should be based on the risk factors of key points and focused on pre-inspection triage and screening, to establish a rapid response mechanism to deal with exogenous and endogenous risk factors. Implementation of all-staff training and assessment, strengthening the information system, and use of medical internet service are important. This study explores the construction of medical protocols in large public hospitals during the pandemic, and provides a reference for the orderly diagnosis and treatment in hospitals during the pandemic.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
ABSTRACT
With the rapid development of edge computing in the post-COVID19 pandemic period, precise workload forecasting is considered the basis for making full use of the edge limited resources, and both edge service providers (ESPs) and edge service consumers (ESCs) can benefit significantly from it. Existing paradigms of workload forecasting (i.e., edge-only or cloud-only) are improper, due to failing to consider the inter-site correlations and might suffer from significant data transmission delays. With the increasing adoption of edge platforms by web services, it is critical to balance both accuracy and efficiency in workload forecasting. In this paper, we propose ELASTIC, which is the first study that leverages a cloud-edge collaborative paradigm for edge workload forecasting with multi-view graphs. Specifically, at the global stage, we design a learnable aggregation layer on each edge site to reduce the time consumption while capturing the inter-site correlation. Additionally, at the local stage, we design a disaggregation layer combining both the intra-site correlation and inter-site correlation to improve the prediction accuracy. Extensive experiments on realistic edge workload datasets collected from China's largest edge service provider show that ELASTIC outperforms state-of-the-art methods, decreases time consumption, and reduces communication cost. © 2023 ACM.
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In the current situation of coronavirus disease 2019, "to prevent import from abroad and to defend internal rebound" is the general principle. Facing the changes in the epidemic situation, especially the winter and spring epidemics, it is a huge challenge to carry out a scientific, precise and flexible program for the prevention and control of healthcare-associated infections so that to ensure the safety of healthcare workers and patients. After more than one year of anti-epidemic work, Peking Union Medical College Hospital has summarized and formulated a four-level retractable and releasable hierarchical program of prevention and control. It is dynamically adjusted according to the responsive level of public health emergencies in Beijing and the relevant regulations of epidemic prevention and control. All departments can also respond quickly to ensure the resumption of work. This program provides reference for the prevention and control of coronavirus disease 2019 and other sudden infectious diseases.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
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In order to improve risk prevention and control capabilities for international sports events under the background of COVID-19, case data of 23 international sports since the pandemic outbreak were collected, and an evolutionary network model with COVID-19 as risk source was established. Then, risk analysis on the model was carried out based on in-and-out degree, number of sub-net nodes, the shortest path and average path of complex network theory, key risk event nodes were identified, and preventive measures were put forward. Finally, critical chains were obtained by analyzing causal mechanism and types of risk chains, and countermeasures and suggestions for chain disconnection and disaster mitigation were put forward. The results show that severe epidemic situation and rising risk of virus transmission in host cities are the key nodes in evolutionary network, and cycle chain of political relations and public opinion is the most destructive one. Therefore, it is necessary to promote the development of a public opinion monitoring system and strengthen positive publicity of sports events. © 2020 China Safety Science Journal. All rights reserved.
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A painful lesson got from pandemic COVID-19 is that preventive healthcare service is of utmost importance to governments since it can make massive savings on healthcare expenditure and promote the welfare of the society. Recognizing the importance of preventive healthcare, this research aims to present a methodology for designing a network of preventive healthcare facilities in order to prevent diseases early. The problem is formulated as a bilevel non-linear integer programming model. The upper level is a facility location and capacity planning problem under a limited budget, while the lower level is a user choice problem that determines the allocation of clients to facilities. A genetic algorithm (GA) is developed to solve the upper level problem and a method of successive averages (MSA) is adopted to solve the lower level problem. The model and algorithm is applied to analyze an illustrative case in the Sioux Falls transport network and a number of interesting results and managerial insights are provided. It shows that solutions to medium-scale instances can be obtained in a reasonable time and the marginal benefit of investment is decreasing. © 2023, Journal of Industrial and Management Optimization. All Rights Reserved.
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The pandemic outbreak of COVID-19 created panic all over the world. As therapeutics that can effectively wipe out the virus and terminate transmission are not available, supportive therapeutics are the main clinical treatments for COVID-19. Repurposing available therapeutics from other viral infections is the primary surrogate in ameliorating and treating COVID-19. The therapeutics should be tailored individually by analyzing the severity of COVID-19, age, gender, comorbidities, and so on. We aim to investigate the effects of COVID-19 therapeutics and to search for laboratory parameters indicative of severity of illness. Multi-center collaboration and large cohort of patients will be required to evaluate therapeutics combinations in the future. This study is a single-center retrospective observational study of COVID-19 clinical data in China. Information on patients' treatment modalities, previous medical records, individual disease history, and clinical outcomes were considered to evaluate treatment efficacy. After screening, 2,844 patients are selected for the study. The result shows that treatment with TCM (Hazard Ratio (HR) 0.191 [95% Confidence Interval (CI), 0.14–0.25];p < 0.0001), antiviral therapy (HR 0.331 [95% CI 0.19–0.58];p = 0.000128), or Arbidol (HR 0.454 [95% CI 0.34–0.60];p < 0.0001) is associated with good prognostic of patients. Multivariate Cox regression analysis showed TCM treatment decreased the mortality hazard ratio by 69.4% (p < 0.0001). © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
ABSTRACT
In order to improve risk prevention and control capabilities for international sports events under the background of COVID-19, case data of 23 international sports since the pandemic outbreak were collected, and an evolutionary network model with COVID-19 as risk source was established. Then, risk analysis on the model was carried out based on in-and-out degree, number of sub-net nodes, the shortest path and average path of complex network theory, key risk event nodes were identified, and preventive measures were put forward. Finally, critical chains were obtained by analyzing causal mechanism and types of risk chains, and countermeasures and suggestions for chain disconnection and disaster mitigation were put forward. The results show that severe epidemic situation and rising risk of virus transmission in host cities are the key nodes in evolutionary network, and cycle chain of political relations and public opinion is the most destructive one. Therefore, it is necessary to promote the development of a public opinion monitoring system and strengthen positive publicity of sports events. © 2020 China Safety Science Journal. All rights reserved.
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Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
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Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
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This paper examines the volatility spillover between the soybean futures contracts traded in the US Chicago Board of Trade (CBOT) and China Dalian Commodity Exchange (DCE) through a normalized Copula–GARCH(1,1) - t model with structural changes. The structural change points are identified through a combination of Bayesian diagnosis with Z-test. The study finds that the volatility spillover exists between the DCE and CBOT soybean futures and weakens through time. We further identify seven structural change points in the volatility spillover relationship, suggesting it is going through significant structural changes. The changes are related to major social-political events including the trade conflict between China and the US, the COVID-19 pandemic and the Russia-Ukraine war. © 2023 Taylor & Francis Group, LLC.
ABSTRACT
Humans are facing an unprecedented historical crisis and challenge. To identify the strategies that we can use to cope with historical crisis and challenge, we should investigate two well-studied strategies: "slow strategy, ” which is essentially an investment in the future, and "fast strategy” or "live fast, die young.” According to "The Ant and the Grasshopper, ” Aesop's fable, which is under the pretext of intertemporal choice of social insects, the "slow” rather than the "fast” strategy is recommended for those who want to survive the environmental crisis. Intertemporal choice requires tradeoffs among outcomes whose effects occur at different times. In the commonly accepted language of intertemporal choice, the Ant, whose choice is the "larger but later” (LL) option, is more likely to survive the harsh winter than the Grasshopper, whose choice is the "smaller but sooner” (SS) option. To determine the optimal intertemporal choice strategy that can help us to cope with the COVID-19 pandemic, we included 26, 355 participants from 18 Asian, African, European, American, and Oceanian countries in the present study. We investigated the participants' preferences in intertemporal choice with double-dated mixed outcomes, evaluated the degree of change in their intertemporal choice by differentiating the common currency in peacetime and epidemic time (i.e., two kinds of change indicators used for differentiating currencies and stages, respectively). We then asked them to rate their self-rated surviving achievement in the fight against COVID-19. Considering that individuals' surviving achievements were affected by individual-and religious-level factors, we analyzed all data by using multilevel linear analysis to reflect the data's hierarchical structure. After considering individual differences in personal factors and religious factors, we constructed two-level models to explore the effects of the change in intertemporal choice on self-rated surviving achievement, and measured the moderating role of cultural orientation in terms of Hofstede's six culture dimensions. The findings of the cross-national survey revealed that Change Indicator 1 (∆ currency) and Change Indicator 2 (∆ stage) of Chinese/Singaporeans could jointly predict their self-rated surviving achievement. Meanwhile, only Change Indicator 2 (∆ stage) alone could predict the self-rated surviving achievement of people in the cultural circle that included the India, Malaysia, Philippines, and Nigeria. Neither Change Indicator 1 (∆ currency) nor Change Indicator 2 (∆ stage) of the people in other cultures could significantly predict their self-rated surviving achievement. On the basis of the gist of The Book of Change and the resulting findings, we suggested that 1) how you differentially (flexibly) made an intertemporal choice in peacetime and epidemic time would reflect the extent to which you would survive the war against COVID-19. In addition, 2) the mindset of change might shape the competitive advantage of a nation, such as China, in response to the historical crisis. The closer the cultural distance of a country or nation from China, the greater the possibility of benefitting from a similar competitive advantage. It is our hope that our findings would contribute to answer the question of what are "Psychological Characteristics and Behaviors of Chinese People in Response to Historical Crisis?”. © 2023, Science Press. All rights reserved.
ABSTRACT
The COVID-19 pandemic has triggered a set of government policies and supermarket regulations, which affects customers' grocery shopping behaviours. However, the specific impact of COVID-19 on retailers at the customer end has not yet been addressed. Using text-mining techniques (i.e., sentiment analysis, topic modelling) and time series analysis, we analyse 161,921 tweets from leading UK supermarkets during the first COVID-19 lockdown. The results show the causes of sentiment change in each time series and how customer perception changes according to supermarkets' response actions. Drawing on the social media crisis communication framework and Situational Crisis Communication theory, this study investigates whether responding to a crisis helps retail managers better understand their customers. The results uncover that customers experiencing certain social media interactions may evaluate attributes differently, resulting in varying levels of customer information collection, and grocery companies could benefit from engaging in social media crisis communication with customers. As new variants of COVID-19 keep appearing, emerging managerial problems put businesses at risk for the next crisis. Based on the results of text-mining analysis of consumer perceptions, this study identifies emerging topics in the UK grocery sector in the context of COVID-19 crisis communication and develop the sub-dimensions of service quality assessment into four categories: physical aspects, reliability, personal interaction, and policies. This study reveals how supermarkets could use social media data to better analyse customer behaviour during a pandemic and sustain competitiveness by upgrading their crisis strategies and service provision. It also sheds light on how future researchers can leverage the power of social media data with multiple text-mining methodologies. © 2022 The Authors
ABSTRACT
Taylor's law states that the spatial variance of the population density varies as the power function of the mean population density. This law is tested on daily Covid-19 infection density for five periods between February 25, 2020 and March 15, 2021. The Italian provinces are grouped by geography into three ensembles. A simultaneous-equation model accounts for correlations between the ensembles, between Italian provinces within each ensemble, and for temporal autocorrelations. The selected periods show ensembles with all Taylor's law slopes below 2 (reflecting State interventions at the national level), or all above 2 (reflecting interventions at the local level), or some ensembles above while others were below. Slope of Taylor's law and average density trend indicate whether the infection density is highly concentrated in a few provinces (when the slope is greater than 2 with increasing density, and when the slope is less than 2 with decreasing density) or spread evenly among all provinces in an ensemble (when the slope is greater than 2 with decreasing density, and when the slope is less than 2 with increasing density), which allows the government and epidemiologists to design disease control policies for targeted provinces and ensembles in Italy. © 2023 Taylor & Francis.
ABSTRACT
Humans are facing an unprecedented historical crisis and challenge. To identify the strategies that we can use to cope with historical crisis and challenge, we should investigate two well-studied strategies: "slow strategy, ” which is essentially an investment in the future, and "fast strategy” or "live fast, die young.” According to "The Ant and the Grasshopper, ” Aesop's fable, which is under the pretext of intertemporal choice of social insects, the "slow” rather than the "fast” strategy is recommended for those who want to survive the environmental crisis. Intertemporal choice requires tradeoffs among outcomes whose effects occur at different times. In the commonly accepted language of intertemporal choice, the Ant, whose choice is the "larger but later” (LL) option, is more likely to survive the harsh winter than the Grasshopper, whose choice is the "smaller but sooner” (SS) option. To determine the optimal intertemporal choice strategy that can help us to cope with the COVID-19 pandemic, we included 26, 355 participants from 18 Asian, African, European, American, and Oceanian countries in the present study. We investigated the participants' preferences in intertemporal choice with double-dated mixed outcomes, evaluated the degree of change in their intertemporal choice by differentiating the common currency in peacetime and epidemic time (i.e., two kinds of change indicators used for differentiating currencies and stages, respectively). We then asked them to rate their self-rated surviving achievement in the fight against COVID-19. Considering that individuals' surviving achievements were affected by individual-and religious-level factors, we analyzed all data by using multilevel linear analysis to reflect the data's hierarchical structure. After considering individual differences in personal factors and religious factors, we constructed two-level models to explore the effects of the change in intertemporal choice on self-rated surviving achievement, and measured the moderating role of cultural orientation in terms of Hofstede's six culture dimensions. The findings of the cross-national survey revealed that Change Indicator 1 (∆ currency) and Change Indicator 2 (∆ stage) of Chinese/Singaporeans could jointly predict their self-rated surviving achievement. Meanwhile, only Change Indicator 2 (∆ stage) alone could predict the self-rated surviving achievement of people in the cultural circle that included the India, Malaysia, Philippines, and Nigeria. Neither Change Indicator 1 (∆ currency) nor Change Indicator 2 (∆ stage) of the people in other cultures could significantly predict their self-rated surviving achievement. On the basis of the gist of The Book of Change and the resulting findings, we suggested that 1) how you differentially (flexibly) made an intertemporal choice in peacetime and epidemic time would reflect the extent to which you would survive the war against COVID-19. In addition, 2) the mindset of change might shape the competitive advantage of a nation, such as China, in response to the historical crisis. The closer the cultural distance of a country or nation from China, the greater the possibility of benefitting from a similar competitive advantage. It is our hope that our findings would contribute to answer the question of what are "Psychological Characteristics and Behaviors of Chinese People in Response to Historical Crisis?”. © 2023, Science Press. All rights reserved.
ABSTRACT
This study uses the event study method to study and analyse the impact of the release of policy information related to the COVID-19 epidemic on the changes in the stock prices of listed companies of property service enterprises in China. The results show that the Hong Kong capital market has been greatly affected by the release of policy information related to the COVID-19 epidemic. Additionally, the study demonstrates that the policy effect of the introduction of policy information related to the COVID-19 epidemic exists in the short term, and that the effectiveness of policy information related to the COVID-19 epidemic will change over time.
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The COVID-19 pandemic has negatively affected the physical and mental health of many. It remains unclear whether such impacts differ across diverse races or age groups, or along the course of the pandemic. This study assessed trends in levels of depression and anxiety symptoms among U.S. adults during COVID-19 and whether differences emerged across race and age. Data were drawn from the Understanding America Study (UAS) COVID-19 survey, a longitudinal panel survey of a nationally representative sample of over 6,000 individuals. A mixed effect linear model was conducted to assess the influence of race and age on the level of depression and anxiety over time during the pandemic, controlling for covariates such as marital status, employment status, and household income. Results indicate that greater age was associated with lower levels of depression and anxiety. Additionally, trends in levels of depression and anxiety vary across races (e.g., minority populations generally reported lower or comparable levels of depression and anxiety comparing to the White). Findings further suggest significant interactions between age and race, especially among minoritized adults. Study findings underscore the importance of future research and tailored strategies to improve culturally sensitive and age-appropriate mental health services targeting diverse populations.
ABSTRACT
COVID-19 continues to spread and spread, and the epidemic situation in China and Japan is not optimistic, which brings huge hidden dangers and serious impact to the economic cooperation and development of China and Japan. Aiming at the comments and feedback of Chinese and Japanese people on government policies, this paper proposes a text emotional tendency analysis method based on maximum entropy model, which extracts word relation features and semantic features from the comment context. The maximum entropy model is used to identify the emotional tendency of words, and the smoothing technique is used to solve the problem of sparse features. At the same time, through the weighting and normalization of specific emotional words and punctuation marks, the uncertainty of the emotional tendency of words in the context is further reduced, and the experimental results verify the effectiveness of the model.
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The outbreak of COVID-19 and the unprecedented policies issued by the government have compelled citizens to reshape their daily travel behavior. Questionnaires were designed to obtain three main related indicators of socio-economic and demographic characteristics, primary travel purposes and patterns, and factors influencing mode choice to explore the impact of the pandemic on travel behavior and mode preferences of urban residents. By applying the online survey method with Snowball sampling techniques, a total of 591 valid questionnaire responses from Hong Kong residents were received in the designated time period. Then, the non-parametric test methods (e.g., McNemar-Bowker test and Mann-Whitney U test) were employed to implement the statistical analysis. Traffic administrators can use the survey findings to adjust current policies or delineate new policies to align with the passenger travel behavior. This will ensure more fluid and safer transportation. © ASCE.
ABSTRACT
[Objective] This paper tries to measure the netizens' trust in government microblogs during public health emergencies, and then explores reasons for the changes. [Methods] First, we calculated the trust from the comments on government microblogs with the comment objects, the topic similarity between comments and microblogs, as well as their sentiments. Then, we added the numbers of likes and forwards/retweets to decide the comprehensive trust of the netizens toward the government microblogs. [Results] We examined out model with microblog data on COVID-19 and found that topics related to industrial and government efforts fighting the pandemic enhanced the trust in government microblogs. There were great differences in the development trends and reasons of the trust in government microblogs from different fields. [Limitations] We only used the events and the microbloggers as the objects of comments. [Conclusions] The proposed model could help government agencies improve decision making, public trust, and lead online opinion during public health emergencies. © 2022, Chinese Academy of Sciences. All rights reserved.