The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users During the COVID-19 Pandemic

The outbreak of the COVID-19 pandemic triggers infodemic over online social media, which significantly impacts public health around the world, both physically and psychologically. In this paper, we study the impact of the pandemic on the mental health of influential social media users, whose sharing behaviours significantly promote the diffusion of COVID-19 related information. Specifically, we focus on subjective well-being (SWB), and analyse whether SWB changes have a relationship with their bridging performance in information diffusion, which measures the speed and wideness gain of information transmission due to their sharing. We accurately capture users' bridging performance by proposing a new measurement. Benefiting from deep-learning natural language processing models, we quantify social media users' SWB from their textual posts. With the data collected from Twitter for almost two years, we reveal the greater mental suffering of influential users during the COVID-19 pandemic. Through comprehensive hierarchical multiple regression analysis, we are the first to discover the strong relationship between social users' SWB and their bridging performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Improving concrete fatigue resistance with COVID-19 rubber gloves: An innovative sustainable approach

Since the COVID-19 outbreak in late 2019, a surprisingly large amount of personal protective equipment, such as medical rubber gloves, have been frequently used, and this medical waste can cause very major environmental problems. A multidisciplinary collaborative approach is needed to combat the pandemic and lessen the environmental risks associated with the disposal of medical waste. This study developed an innovative approach by incorporating shredded rubber glove fibers (RGF) into aggregates to enhance the fatigue resistance of concrete. In this study, different volume contents (0.5%, 1.0%, 1.5%, 2.0%) of RGF were added to the aggregate for the first time. The effects of different RGF contents on the fatigue characteristics of concrete were examined through repeated loading tests and SEM analysis. The results show that the width and number of cracks produced by rubber glove fiber concrete (RGFC) after repeated loading are significantly reduced compared with normal concrete (NC). Following repeated loading, RGFC exhibited higher total, plastic, and elastic strain values than NC, demonstrating greater deformability and elasticity. However, the maximum total strain growth rate and the total strain growth range of the RGFC group were only 2.26 × 10−3/time and 14.0%, which were significantly smaller than the 3.8 × 10−3/time and 31.7% of the NC group, showing better stability, corresponding to enhance the fatigue resistance of concrete. The interfacial transition zone (ITZ) was abnormally smooth with a thin thickness and no visible gaps were discovered, based on the results of SEM test performed on the RGFC. The findings obtained in this study may provide new ideas for the resource utilization of medical waste. © 2023

Local Housing Market Sentiments and Returns: Evidence from China

This paper examines the impacts of local housing sentiments on the housing price dynamics of China. With a massive second-hand transaction dataset, we construct monthly local housing sentiment indices for 18 major cities in China from January 2016 to October 2020. We create three sentiment proxies representing the local housing market liquidity and speculative behaviors from the transaction dataset and then use partial least squares (PLS) to extract a recursive look-ahead-bias-free local housing sentiment index for each city considered. The local housing sentiments are shown to have robust predictive powers for future housing returns with a salient short-run underreaction and long-run overreaction pattern. Further analysis shows that local housing sentiment impacts are asymmetric, and housing returns in cities with relatively inelastic housing supply are more sensitive to local housing sentiments. We also document a significant feedback effect between housing returns and market sentiments, indicating the existence of a pricing-sentiment spiral which could potentially enhance the ongoing market fever of Chinese housing markets. The main estimation results are robust to alternative sentiment extraction methods and alternative sentiment proxies, and consistent for the sample period before COVID-19.

Measuring COVID-19 Vaccine Hesitancy: Consistency of Social Media with Surveys

We validate whether social media data can be used to complement social surveys to monitor the public’s COVID-19 vaccine hesitancy. Taking advantage of recent artificial intelligence advances, we propose a framework to estimate individuals’ vaccine hesitancy from their social media posts. With 745,661 vaccine-related tweets originating from three Western European countries, we compare vaccine hesitancy levels measured with our framework against that collected from multiple consecutive waves of surveys. We successfully validate that Twitter, one popular social media platform, can be used as a data source to calculate consistent public acceptance of COVID-19 vaccines with surveys at both country and region levels. In addition, this consistency persists over time although it varies among socio-demographic sub-populations. Our findings establish the power of social media in complementing social surveys to capture the continuously changing vaccine hesitancy in a global health crisis similar to the COVID-19 pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The optimal anticoagulation strategy for COVID-19, prophylactic or therapeutic?: a meta-analysis, trial sequential analysis, and meta-regression of more than 27,000 participants

Background: Anticoagulants are promising regimens for treating coronavirus disease 2019 (COVID-19). However, whether prophylactic or intermediate-to-therapeutic dosage is optimal remains under active discussion. Methods: We comprehensively searched PubMed, Embase, Scopus, Web of Science, Cochrane Library, ClinicalTrials, and MedRxiv databases on April 26, 2022. Two independent researchers conducted literature selection and data extraction separately according to predetermined criteria. Notably, this is the first meta-analysis on COVID-19, taking serious consideration regarding the dosage overlap between the 2 comparison groups of prophylactic anticoagulation (PA) and intermediate-to-therapeutic anticoagulation (I-TA). Results: We included 11 randomized controlled trials (RCTs) and 36 cohort studies with 27,051 COVID-19 patients. By analyzing all the RCTs, there was no significant difference in mortality between the PA and I-TA groups, which was further confirmed by trial sequential analysis (TSA) (odds ratio [OR]: 0.93;95% confidence interval [CI]: 0.71–1.22;P = 0.61;TSA adjusted CI: 0.71–1.26). The rate of major bleeding was remarkably higher in the I-TA group than in the PA group, despite adjusting for TSA (OR: 1.73;95% CI: 1.15–2.60;P = 0.009;TSA adjusted CI: 1.09–2.58). RCTs have supported the beneficial effect of I-TA in reducing thrombotic events. After including all studies, mortality in the I-TA group was significantly higher than in the PA group (OR: 1.38;95% CI: 1.15–1.66;P = 0.0005). The rate of major bleeding was similar to the analysis from RCTs (OR: 2.24;95% CI: 1.86–2.69;P < 0.00001). There was no distinct difference in the rate of thrombotic events between the 2 regimen groups. In addition, in both critical and noncritical subgroups, I-TA failed to reduce mortality but increased major bleeding rate compared with PA, as shown in meta-analysis of all studies, as well as RCTs only. Meta-regression of all studies suggested that there was no relationship between the treatment effect and the overall risk of mortality or major bleeding (P = 0.14, P = 0.09, respectively). Conclusion: I-TA is not superior to PA for treating COVID-19 because it fails to lower the mortality rate but increases the major bleeding rate in both critical and noncritical patients. Copyright © 2022 Shandong University, published by Wolters Kluwer, Inc.

INTER-BRAND COVID-19 VACCINE PREFERENCES AND VACCINE HESITANCY: A SURVEY OF A CONVENIENCE SAMPLE

BACKGROUND: Delay in acceptance or refusal of vaccination despite vaccine availability comprise a continuum of attitudes known as vaccine hesitancy. To date, three COVID-19 vaccines have been granted emergency use authorization in the U.S.;yet hesitancy to accept vaccination against COVID-19 remains common. Understanding the nature of inter-brand preferences amongst7 these vaccines may help inform vaccine allocation and outreach strategies. METHODS: In April 2021, a de-identified, web-based survey was administered to a convenience sample of respondents across forty-eight states, assessing standard demographics and presence of COVID-19 vaccine brand preference. Those indicating a preference then ranked four COVID-19 vaccine brands presented in random order. Vaccine hesitancy due to brand preference was assessed as the time length for which the respondent was willing to postpone vaccination if their preferred brand of vaccine was unavailable. RESULTS: Of 1,068 respondents, 55.4% endorsed a preference for a particular COVID-19 vaccine brand. On univariate analysis, preference presence differed significantly by age (p=0.011) and religion (p=0.012). The 50-64 age group had the lowest presence of preference (47.9%) while the 18-29 (61.5%, p=0.002) age group had the highest preference presence. The religious group with the least presence of preference was Jewish (45.2%) while the Atheist/ Agnostic (60.0%, p<0.001) and Catholic (59.2%, p=0.012) groups had the highest preference presence. Upon multivariable analysis however, only age was found to be an independent predictor of preference presence (p=0.027). 45.9% (490/1,068) of all respondents would postpone vaccination if their preferred brand was unavailable, with 14.6% (156/1,068) willing to wait three weeks or longer. Willingness to postpone vaccination based on brand availability varied significantly only by religion on both univariate (p=0.022) and multivariable analysis (p=0.043), with the lowest rates of postponement among the Jewish (43.4%) and the highest among Atheists (63.0%, p<0.001) and Catholics (53.1%, p=0.073). Respondents ranked brands in one predominant order (χ2=765.64, p<0.001). Pfizer was preferred over Moderna (Z=-9.405, p<0.001), JnJ (Z=-15.545, p<0.001), and AstraZeneca (Z=-17.399, p<0.001). Moderna was preferred over JnJ (Z=-11.658, p<0.001) and AstraZeneca (Z=-16.782, p<0.001), and JnJ over AstraZeneca (Z=-10.492, p<0.001). Besides the 65+ subgroup which did not have a significant preference between Pfizer or Moderna vaccines (p=0.773), all age and religious groups had the same rank preferences with all paired comparisons similarly significant, p≤0.001. CONCLUSIONS: Age independently predicted the presence of COVID-19 vaccine brand preference while religion independently predicted vaccine hesitancy due to said preference. Further evaluation of the causes and consequences of such inter-brand preferences may inform efforts to increase vaccination among vaccine-curious individuals and facilitate progress towards herd immunity.

The Gold Standard in Handling a Pandemic at a National Level: Vietnam’s Approach to Dealing with COVID-19

This study looked at how Vietnam, a developing country, in South East Asia has systemically dealt with the COVID-19 pandemic on a national level with remarkable success. This study delved into the approaches taken by Vietnam in pre-mediating the influx of COVID-19 from interlopers into the country and controlling its spread within the confines of the nation. This study examined the steps taken by Vietnam. The quick actions of the government have instilled confidence in their citizens and promoted greater internal travel mobility within the Vietnam, thus helping the local tourism industry to remain vibrant and competitive. Unlike other countries, which have been severely affected by the COVID-19 virus, Vietnam is poised for a head start in its recovery. © 2021 by Emerald Publishing Limited.

From #jobsearch to #mask: Improving COVID-19 cascade prediction with spillover effects

An information outbreak occurs on social media along with the COVID-19 pandemic and leads to infodemic. Predicting the popularity of online content, known as cascade prediction, allows for not only catching in advance hot information that deserves attention, but also identifying false information that will widely spread and require quick response to mitigate its impact. Among the various information diffusion patterns leveraged in previous works, the spillover effect of the information exposed to users on their decision to participate in diffusing certain information is still not studied. In this paper, we focus on the diffusion of information related to COVID-19 preventive measures. Through our collected Twitter dataset, we validated the existence of this spillover effect. Building on the finding, we proposed extensions to three cascade prediction methods based on Graph Neural Networks (GNNs). Experiments conducted on our dataset demonstrated that the use of the identified spillover effect significantly improves the state-of-the-art GNNs methods in predicting the popularity of not only preventive measure messages, but also other COVID-19 related messages. © 2021 Owner/Author.

Recognition of Academic Emotions in Online Classes

Online education has proliferated since the COVID-19 pandemic. Classes have been moved online as a result of school closures. Despite the flexibility offered by online learning, there are several challenges faced. Creating a good classroom climate for online classes is a challenging task. It is difficult for the teachers to obtain emotional feedback from the students, especially in asynchronous classes or classes with large number of students. It is hard for the teachers to evaluate the engagement of the students in class without knowing the students' emotional response. The existing facial expression recognition databases focus on basic human emotions like happy, angry, sad, surprise and neutral. These basic emotions are not appropriate for learning as psychological and pedagogical studies have shown that there are differences between basic human emotions and academic emotions. In view of these problems, this paper presents a study on academic emotions. A dataset comprising four pertinent academic emotions have been established. Empirical analysis on the dataset is conducted using both hand crafted and deep learning approaches. The baseline evaluation demonstrates the suitability of the established academic dataset for online learning. © 2021 IEEE.

Collaborative city digital twin for the COVID-19 pandemic: A federated learning solution

The novel coronavirus, COVID-19, has caused a crisis that affects all segments of the population. As the knowledge and understanding of COVID-19 evolve, an appropriate response plan for this pandemic is considered one of the most effective methods for controlling the spread of the virus. Recent studies indicate that a city Digital Twin (DT) is beneficial for tackling this health crisis, because it can construct a virtual replica to simulate factors, such as climate conditions, response policies, and people's trajectories, to help plan efficient and inclusive decisions. However, a city DTsystem relies on long-term and high-quality data collection to make appropriate decisions, limiting its advantages when facing urgent crises, such as the COVID-19 pandemic. Federated Learning (FL), in which all clients can learn a shared model while retaining all training data locally, emerges as a promising solution for accumulating the insights from multiple data sources efficiently Furthermore, the enhanced privacy protection settings removing the privacy barriers lie in this collaboration. In this work, we propose a framework that fused city DT with FL to achieve a novel collaborative paradigm that allows multiple city DTs to share the local strategy and status quickly. In particular, an FL central server manages the local updates of multiple collaborators (city DTs), providing a global model that is trained in multiple iterations at different city DT systems until the model gains the correlations between various response plans and infection trends. This approach means a collaborative city DT paradigm fused with FL techniques can obtain knowledge and patterns from multiple DTs and eventually establish a 'global view' of city crisis management. Meanwhile, it also helps improve each city's DT by consolidating other DT's data without violating privacy rules. In this paper, we use the COVID-19 pandemic as the use case of the proposed framework. The experimental results on a real dataset with various response plans validate our proposed solution and demonstrate its superior performance. ©2021 Tsinghua University Press. © 2021 Tsinghua University Press. All rights reserved.

The effect of environmental regulation on air quality in China: A natural experiment during the COVID-19 pandemic

The prevention and control measures in place during the coronavirus disease 2019 (COVID-19) pandemic served as perfect conditions for a natural experiment, which has provided an opportunity to investigate the extent to which environmental regulations can improve air quality in the short term. This article examines the relationship between anti-epidemic measures and air quality via a regression discontinuity design (RDD) based on the daily data from 326 prefecture-level cities in China. The empirical results indicate that, during the period of epidemic prevention and control in China, the air quality index (AQI) significantly decreased by 20.56, and the emission concentrations of the pollutants PM2.5, PM10, and NO2 decreased by 19.01, 20.20, and 2.13, respectively. It was further found that the continued operation of life-supporting industries during the epidemic, such as thermal power plants and heating industries, may be the reasons why there were no significant decreases in the concentrations of SO2 and CO. The O3 concentration, which is related to sunlight and the concentrations of NOx, was also not found to have changed significantly in the short term. Moreover, it was found that the more daily confirmed COVID-19 cases in an area, the greater the improvement of the air quality. © 2021 Turkish National Committee for Air Pollution Research and Control

Teleconsulting in the time of a global pandemic: Application to anesthesia and technological considerations

As a result of the various restrictions associated with the current COVID-19 pandemic, the practice of veterinary telehealth is likely to grow substantially. One area in which high quality care can be maintained while respecting physical distancing is teleconsulting, which describes the relationship between an attending and off-site consulting veterinarian. This guide uses a dentistry case to illustrate the provision of real-time anesthesia consulting, with a focus on the technological considerations central to facilitating live, 2-way video-communication. Case selection, teamwork, and patient safety are also discussed.