Using humor to increase COVID-19 vaccination intention for the unvaccinated: The moderating role of trust in government

Since COVID-19 was declared a global pandemic, scholars and practitioners have put much effort into testing effective advertising strategies for COVID-19 vaccinations. Guided by humor theories, this study aimed to examine (1) the effect of humor on persuading COVID-19 vaccination and (2) the moderating role of trust in government for the unvaccinated population. Across two studies (college students and general adult populations), for lower trust in government individuals, through greater public service advertisement (PSA) processing depth and believability, there was a higher vaccination intention after the humor (non-humor) advertisement. For higher trust in government individuals, there was evidence that the vaccination intention was lowered after the humor (vs. non-humor) message through lowered PSA processing depth and believability. This study expands humor theory into testing COVID-19 vaccination messages while considering an individual psychological factor, trust in the government, that has emerged as an essential determinant to COVID-19 messaging. The contributions to COVID-19 vaccination advertising strategy and advertising to the unvaccinated population, in general, are discussed.

Implications of the Improvement in Atmospheric Fine Particles: A Case Study of COVID-19 Pandemic in Northern Taiwan

The outbreak of COVID-19 pandemic in northern Taiwan led to the implementation of Level 3 alert measures during 2021 and thereby impacted the air quality significantly, which provided an unprecedented opportunity to better understand the control strategies on air pollutants in the future. This study investigated the variations in sources, chemical characteristics and human health risks of PM2.5 comprehensively. The PM2.5 mass concentrations decreased from pre-alert to Level 3 alert by 49.4%, and the inorganic ions, i.e., NH4+, NO3- and SO42-, dropped even more by 71%, 90% and 52%, respectively. Nonetheless, organic matter (OM) and elemental carbon (EC) simply decreased by 36% and 13%, which caused the chemical composition of PM2.5 to change so that the carbonaceous matter in PM2.5 dominated instead of the inorganic ions. Correlation-based hierarchical clustering analysis further showed that PM2.5 was clustered with carbonaceous matter during the Level 3 alert, while that clustered with inorganic ions during both pre-alert and post-alert periods. Moreover, 6 sources of PM2.5 were identified by positive matrix factorization (PMF), in which secondary nitrate (i.e., aging traffic aerosols) exhibited the most significant decrease and yet primary traffic-related emissions, dominated by carbonaceous matter, changed insignificantly. This implied that secondary traffic-related aerosols could be easily controlled when traffic volume declined, while primary traffic source needs more efforts in the future, especially for the reduction of carbonaceous matter. Therefore, cleaner energy for vehicles is still needed. Assessments of both carcinogenic risk and non-carcinogenic risk induced by the trace elements in PM2.5 showed insignificant decrease, which can be attributed to the factories that did not shut down during Level 3 alert. This study serves as a metric to underpin the mitigation strategies of air pollution in the future and highlights the importance of carbonaceous matter for the reduction in PM2.5.

"I Need Husband-Distancing”: Experience of Marital Conflict during the COVID-19 Emergency in South Korea

The purpose of this study was to understand the phenomenon of marital conflict during the coronavirus disease (COVID-19) emergency in South Korea by adapting the vulnerability-stress-adaptation model (VSA;Karney and Bradbury 1995). The public emergency of COVID-19 and social distancing policies caused emotional distress, social isolation, lack of support, and economic crisis in families, increasing the risk of marital conflict. Eleven women who reported experiencing severe marital conflict during the COVID-19 pandemic were interviewed by telephone. The interview data were analyzed through directed content analysis. The women experienced 1) malad-aptation to sudden life changes, 2) family role confusion, 3) economic crisis, and 4) invasion of personal space. These adverse experiences, along with the influence of their spouses' personality traits, led to reduced physical and psychological interaction between the partners and severance of their relationship. Attention must be paid to the mental health and well-being of families to prevent their dissolution. There is an urgent need for community-based psychological intervention and support for families who are house-bound for long periods. Additionally, government policies are necessary to lighten or share the childcare burden on families during the crisis, so women are not compelled to take career breaks. © 2023, Universitaet Bielefeld. All rights reserved.

The effect of COVID-19 outbreak on hospital admissions for dental infections

Cervicofacial infections of dental origin can cause life threatening emergency and we were anticipating that the prevalence of hospital admissions for this reason between the 26 th of March 2020 until the 8 th of June 2020 that the dental practices were closed would increase. We conducted a retrospective analysis of the hospital admissions for cervicfacial infections of dental origin during this period and the results were compared with the admissions the same period last year. Surprisingly there were less admissions in 2020 compared to 2019 which can be attributed to the government guidance to ''Stay at home", "Save lives", "Protect the NHS'' and the treatment provided by the Urgent Dental Care Centers that reduced the pressure on the country's health care system. Proportionately more admissions in 2020 were attributed to dental abscess from mandibular teeth compared to 2019 but there was a small decrease in the incision and drainage under general anesthetic and a small increase in the length of the hospital stay in 2020.Copyright © 2021

Suitability analysis of a temperature and humidity control device using a desiccant rotor

As the amount of ventilation required in buildings has increased to prevent the spread of COVID-19, the inflow of high humidity outside air in summer has increased the processing rate of latent heat loads as well as sensible heat loads. Accordingly, the ability to handle the latent heat load with low energy consumption has become important in order to maintain a comfortable indoor environment. In this study, a humidity control device composed of a desiccant rotor was designed and manufactured, and performance experiments were performed. Using an empirical formula obtained through experiments, a thermal environment simulation was conducted for a school classroom. Furthermore, a temperature-humidity control device that combines a desiccant rotor and heat pump was proposed, and the performance and energy consumption were analyzed by comparing it with the existing heat pump design. With conventional temperature control method using a heat pump, the average indoor relative humidity values in August were 65.7 %, which exceeds the set relative humidity range of 50 +/- 5 %. On the other hand, when using the temperature-humidity control device, the average indoor relative humidity values in August was 50.2 %, a more comfortable indoor environment than when using a conventional method. In addition, the energy consumption was reduced by 3 % compared to existing heat pump design.

Managing bed capacity and timing of interventions: a COVID-19 model considering behavior and underreporting

We develop a mathematical model considering behavioral changes and underreporting to describe the first major COVID-19 wave in Metro Manila, Philippines. Key parameters are fitted to the cumulative cases in the capital from March to September 2020. A bi-objective optimization problem is formulated that allows for the easing of restrictions at an earlier time and minimizes the number of additional beds ensuring sufficient capacity in healthcare facilities. The well-posedness of the model and stability of the disease-free equilibria are established. Simulations show that if the behavior was changed one to four weeks earlier before the easing of restrictions, cumulative cases can be reduced by up to 55% and the peak delayed by up to four weeks. If reporting is increased threefold in the first three months of the estimation period, cumulative cases can be reduced by 61% by September 2020. Among the Pareto optimal solutions, the peak of cases is lowest if strict restrictions were eased on May 20, 2020 and with at least 56 additional beds per day. © 2023 the Author(s).

Quantifying the Effects of Non-Pharmaceutical and Pharmaceutical Interventions Against Covid-19 Epidemic in the Republic of Korea: Mathematical Model-Based Approach Considering Age Groups and the Delta Variant

Early vaccination efforts and non-pharmaceutical interventions (NPIs) were insufficient to prevent a surge of COVID-19 cases triggered by the Delta variant. A compartment model that includes age, vaccination, and variants was developed. We estimated the transmission rates using maximum likelihood estimation, and phase-dependent NPIs according to government policies from 26 February to 8 October 2021. Simulations were done to examine the effects of varying dates of initiation and intensity of eased NPIs, arrival timing of Delta, and speed of vaccine administration. The estimated transmission rate matrices show distinct patterns, with transmission rates of younger groups (0-39 years) much larger with Delta. Social distancing (SD) level 2 and SD4 in Korea were associated with transmission reduction factors of 0.63-0.70 and 0.70-0.78, respectively. The easing of NPIs to a level comparable to SD2 should be initiated not earlier than 16 October to keep the number of severe cases below Korea's healthcare capacity. Simulations showed that a surge prompted by Delta can be prevented if the number of people vaccinated daily or SD level when Delta arrived was higher. The timing of easing, intensity of NPIs, vaccination speed, and screening measures are key factors in preventing another epidemic wave.

Epidemiological Factors Associated with COVID-19 Clusters in Medical and Social Welfare Facilities

The characteristics of coronavirus disease 2019 (COVID-19) clusters in medical and social welfare facilities and the factors associated with cluster size are still not yet fully understood. We reviewed COVID-19 cases in Japan identified from January 15 to April 30, 2020 and analyzed the factors associated with cluster size in medical and social welfare facilities. In this study, COVID-19 clusters were identified in 56 medical and 34 social welfare facilities. The number of cases in those facilities peaked after the peak of the general population. The duration of occurrence of new cases in clusters was positively correlated with the number of cases in both types of facilities (rho = 0.44, P < 0.001;and rho = 0.69, P < 0.001, respectively). However, the number of days between the first case in a prefecture and the onset of clusters was negatively correlated with the number of cases only in clusters in social welfare facilities (rho = 0.4, P = 0.004). Our results suggest that COVID-19 cases in those facilities were prevalent in the latter phase of the disease's community transmission, although the underlying mechanisms for such a trend could differ between medical and social welfare facilities.

D-FEND: A Diffusion-Based Fake News Detection Framework for News Articles Related to COVID-19

The social confusion caused by the recent pandemic of COVID-19 has been further facilitated by fake news diffused via social media on the Internet. For this reason, many studies have been proposed to detect fake news as early as possible. The content-based detection methods consider the difference between the contents of true and fake news articles. However, they suffer from the two serious limitations: (1) the publisher can manipulate the content of a news article easily, and (2) the content depends upon the language, with which the article is written. To overcome these limitations, the diffusion-based fake news detection methods have been proposed. The diffusion-based methods consider the difference among the diffusion patterns of true and fake news articles on social media. Despite its success, however, the lack of the diffusion information regarding to the COVID-19 related fake news prevents from studying the diffusion-based fake news detection methods. Therefore, for overcoming the limitation, we propose a diffusion-based fake news detection framework (D-FEND), which consists of four components: (C1) diffusion data collection, (C2) analysis of the data and feature extraction, (C3) model training, and (C4) inference. Our work contributes to the effort to mitigate the risk of infodemics during a pandemic by (1) building a new diffusion dataset, named CoAID+, (2) identifying and addressing the class imbalance problem of CoAID+, and (3) demonstrating that D-FEND successfully detects fake news articles with 88.89% model accuracy on average. © 2022 ACM.

Does COVID-19 influence the maturity management of industrial sectors? Evidence from global data

Purpose: This study aims to understand how the COVID-19 pandemic dramatically impacts the maturity of all industrial sectors globally. This paper analyses the general patterns of managing maturity in terms of performance and risk-taking of S&P 500 industrial sectors while determining their association with COVID-19. Design/methodology/approach: To analyse the immediate response of COVID-19 on maturity management, the authors gather time-series daily index data of S&P sectors from October 2019 until June 2020 from Bloomberg. The authors select this study period to show the immediate effect of COVID-19 on industrial sector maturity management. The performance and volatility of stock are proxies for managing the maturity of each sector. The authors use vector auto-regression (VAR) methodology to determine the impact of global coronavirus. Findings: This study’s findings suggest that the information technology sectors outperform the other sectors;in contrast, the utility sector exhibits the worst performance during a pandemic. Furthermore, the real estate sector depicts a higher level of systematic risk pattern than other sectors. Interestingly, the empirical result of VAR shows that almost every sector is significantly negatively affected by this pandemic;however, the consumer discretionary sector is immune to it. Research limitations/implications: Overall, this study’s findings for individual economic sectors demonstrate that the managing maturity of each sector acts differently to the coronavirus outbreak. This study offers insights to researchers, policymakers, regulators, financial report users, investors, employees, clients and society. Originality/value: This paper contributes to the existing literature on managing the maturity of industry sectors in terms of observing their trends during the financial crisis. © 2022, Emerald Publishing Limited.

Collection and Analysis of Electricity Consumption Data: The Case of POSTECH Campus

Advanced metering infrastructure (AMI) is an integrated system of smart meters, communication networks, and data management systems. The AMI allows the automatic and remote measurement and monitoring of energy consumption. It also provides important information for the management of peak demand and energy consumption and costs. Pohang University of Science Technology (POSTECH) has developed its own AMI and an IT platform called Open Innovation Big Data Center (OIBC) to store and share various data collected in the campus. In this work, we describe the AMI and the OIBC platform equipped with various sensors and systems for measuring, storing, calling, and monitoring data. Data are collected from seven buildings with different characteristics. We installed 266 sensors at the buildings, including 188 EnerTalk and Biz, 18 plugin, and 60 high-sampling sensors. The sensors collect electricity consumption data in real time, and users can visualize and download the data through the OIBC platform. In this work, we present analysis results of the collected data. The results show that the amounts of electricity consumed by campus buildings are different depending on various factors, including building size, occupant type and their behaviors, and building use. We also compare the amounts of electricity consumed before and after the COVID-19 outbreak. The information extracted can be used to improve the satisfaction of students and faculty as well as the efficiency of electricity management. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Delivering Augmented Information in a Session Initiation Protocol-Based Video Telephony Using Real-Time AR

Online video telephony systems have been increasingly used in several industrial areas because of coronavirus disease 2019 (COVID-19) spread. The existing session initiation protocol (SIP)-based video call system is being usefully utilized, however, there is a limitation that it is very inconvenient for users to transmit additional information during conversation to the other party in real time. To overcome this problem, an enhanced scheme is presented based on augmented real-time reality (AR). In this scheme, augmented information is automatically searched from the Internet and displayed on the user’s device during video telephony. The proposed approach was qualitatively evaluated by comparing it with other conferencing systems. Furthermore, to evaluate the feasibility of the approach, we implemented a simple network application that can generate SIP call requests and answer with AR object pre-fetching. Using this application, the call setup time was measured and compared between the original SIP and pre-fetching schemes. The advantage of this approach is that it can increase the convenience of a user’s mobile phone by providing a way to automatically deliver the required text or images to the receiving side. © 2022. KIPS

Ecological analysis of the temporal trends in the association of social vulnerability and race/ethnicity with county-level covid-19 incidence and outcomes in the United States

Background: The COVID-19 pandemic adversely affected socially vulnerable and minority communities in the US initially, but the temporal trends during the year-long pandemic remain unknown. Objective: We examined temporal association between county-level Social Vulnerability Index (SVI), a percentile-based measure of social vulnerability to disasters, its subcomponents and race/ethnic composition with COVID-19 incidence and mortality in US in the year starting in March 2020. Methods: Counties (n=3091) with > 50 COVID-19 cases by March 6th, 2021 were included. Associations between SVI (and its subcomponents) and county level racial composition with incidence and death per capita were assessed using a negative-binomial mixed-effects model. This model was used to examine potential time varying associations between weekly number of cases/deaths and SVI or racial composition. Data was adjusted for percentage of population aged ≥65 years, state level testing rate, county-level comorbidities, and environmental factors. Results: Higher SVI, indicative of greater social vulnerability, was independently associated with higher COVID-19 incidence (adjusted incidence rate ratio [IRR] per-10 percentile increase:1.02, (95% CI 1.02, 1.03, p<0.001), and death per capita (1.04, (95% CI 1.04, 1.05, p<0.001). SVI became an independent predictor of incidence starting from March 2020, but this association became weak or insignificant by winter, a period that coincided with sharp increase in infection rates and mortality, and when counties with higher proportion of White residents were disproportionately represented (“third wave”). By Spring 2021, SVI was again a predictor of COVID-19 outcomes. Counties with greater proportion of Blacks also observed similar temporal trends in COVID-19-related adverse outcomes. Counties with greater proportion of Hispanics had worse outcomes throughout the duration of the analysis. Conclusion: Except for winter “third wave” when majority White communities had highest incidence of cases, counties with greater social vulnerability and higher minority populations, experienced worse COVID-19 outcomes.

Neighborhood social vulnerability is associated with major adverse cardiovascular events and deaths among patients hospitalized with covid-19: An analysis of the aha covid-19 cardiovascular disease registry

Introduction: The COVID-19 pandemic has disproportionately affected low-income and racial/ethnic minority populations in the US. However, it remains unclear whether hospitalized COVID-19 patients who live in socially vulnerable neighborhoods are more likely to experience major adverse cardiovascular events and/or death. We evaluated the association between neighborhood social vulnerability and in-hospital outcomes in a national cohort of hospitalized COVID-19 patients. Hypothesis: Among patients hospitalized with COVID-19, residence in socially vulnerable neighborhoods is associated with worse in-hospital outcomes. Methods: The American Heart Association COVID-19 Cardiovascular Disease Registry includes patients hospitalized with COVID-19 across 107 hospitals in the US between January 14, 2020 to November 30, 2020. The Social Vulnerability Index (SVI), a composite measure of community vulnerability developed by Center for Disease Control was used to classify the social vulnerability of patients' place of residence defined by zip codes. We fit multivariable logistic regression models to evaluate the association between patient's SVI and in-hospital death or major adverse cardiovascular events (MACE, defined as composite of all-cause death, MI, stroke, new onset heart failure, or cardiogenic shock). Results: Among 20,925 hospitalized COVID-19 patients in the registry, 6083 (29.1%) resided in the most vulnerable communities (highest national quartile of SVI). Compared with those in lowest quartile of SVI, patients in the highest quartile were younger (mean age 59.8±17.7 versus 62.0±17.9), more likely to be women (47.1% vs. 43.2%), Black patients (36.1% vs. 13.3%), and less likely to have private insurance (29.0% vs. 39.1%). After adjusting for demographics (age, sex, race/ethnicity), insurance status, and comorbidities, the highest quartile of SVI (compared to lowest) was associated with higher likelihood of in-hospital MACE (OR [95% CI] 1.28 [1.12, 1.46], p<0.001) as well as in-hospital death (OR 1.37 [1.21, 1.54], p<0.001). Conclusion: Hospitalized patients with COVID-19 who reside in more socially vulnerable neighborhoods experience higher rates of in-hospital MACE and death, independent of race and ethnicity.

Virtual and Open Integration of Culture for Education (VOICE) with Science Teacher Candidates from Korea during COVID-19

Cultural competencies and confidence in teaching diverse students are needed to close achievement gaps between mainstream and minority students in science. In this study, an online teacher education program, Virtual and Open Integration of Culture for Education (VOICE), was designed to help retain teacher candidates' science affinities and cultural competency during the COVID-19 pandemic. Thirty-two Korean teacher candidates were selected as culturally responsive instructors who were able to reduce their cultural bias and preferences about Korean culture and develop culturally responsive instruction. VOICE proceeded through (1) "collaborating,"by connecting seminar speakers worldwide;(2) "designing,"by creating culturally responsive science activities based on Korean culture;and (3) "performing,"by communicating with American students, teacher candidates, teachers, and parents. Pre- and post-survey results show that VOICE increased the teacher candidates' cultural proficiency and interest in science. Guidelines for research on designing online programs to enhance teacher candidates' science affinities and cultural competencies are provided. © Yoon, Ko and Lee, 20 21.

Progress of COVID-19 survivors and the impact of the infection on their ability to return to work

P138 Table 1Employment status of COVID-19 dischargesN 138 Essential services 41 (30) Office/admin 37 (27) Healthcare 16 (12) Non essential services 15 (11) Public transport 10 (7) Enforcement 4 (3) Heavy Goods Vehicle driver 3 (2) Carers 2 (1) Unknown 10 (7) ConclusionOur preliminary data suggests significant symptom burden within 6 weeks post discharge after a COVID-19 infection admission, which may impact on the ability of patients to return to work. In the present analysis there was no significant interaction between return-to-work status and covid severity.

Impact of COVID-19 on TB epidemiology in South Korea.

SETTING: Five referral hospitals, South Korea.OBJECTIVE: To assess epidemiological changes in TB before and during the COVID-19 pandemic.DESIGN: This was a multicentre cohort study of 3,969 patients diagnosed with TB.RESULTS: We analysed 3,453 patients diagnosed with TB prior to the COVID-19 pandemic (January 2016-February 2020) and 516 during the pandemic (March-November 2020). During the pandemic, the number of patients visits declined by 15% from the previous 4-year average, and the number of patients diagnosed with TB decreased by 17%. Patients diagnosed during the pandemic were older than those diagnosed before the pandemic (mean age, 60.2 vs. 56.6 years, P < 0.001). The proportion of patients to have primary TB at a younger age (births after 1980) among those diagnosed with TB was significantly lower during the pandemic than before (17.8% in 2020 vs. 23.5% in 2016, 24.0% in 2017, 22.5% in 2018, 23.5% in 2019; P = 0.005).CONCLUSIONS: The COVID-19 pandemic resulted in a reduction in the number of visits to respiratory departments, leading to fewer patients being diagnosed with TB. However, our results suggest that universal personal preventive measures help to suppress TB transmission in regions with intermediate TB burden.

Operation policy of multi-capacity logistic robots in hotel industry

Purpose: This paper aims to propose an operation policy of multi-capacity room service robots traveling within a hotel. As multi-capacity robots can serve many requests in a single trip, improved operation policy can reduce the investment cost of robots. Design/methodology/approach: Using a mathematical model-based optimization technique, an optimal set of robots with minimum installation cost is derived while serving the entire room service demands. Through testing a variety of scenarios by changing the price and function of robots to be installed, insights that consider the various situations are offered. Findings: Though the increase in capacity saves much time for room service at a lower capacity level, the amount of time saved gradually decreases as the capacity increases. Besides, the installation strategy is divided into two cases depending on the purchase cost of robots. Research limitations/implications: Currently, the studies focusing on the adoption of service robots from an operations view are rarely be found. To reduce the burden of investment cost, this study takes the unique approach to improve the operation policy of service robots by using the multi-capacity robots. Practical implications: This study guides the hotel to install an adequate set of robots. The result confirms that the optimal installation set of robots is affected by various factors, such as the room service information, the hotel structure and the unit execution cycle. Originality/value: After the outbreak of COVID-19, people avoid face-to-face contact and interest in non-contact service is growing. This paper deals with the efficient way to implement non-contact delivery through logistic robots, a timely and important topic. © 2021, Emerald Publishing Limited.