A review of some Covid-19 pandemic numbers in European Union, Canada, and Mexico

The rapidity and extent of Covid-19 infections have shown how a phenomenon that initially seemed geographically circumscribed quickly spread worldwide. In 2020, the spread of infection and the containment and management measures taken by local governments have been quite heterogeneous. Therefore, here we investigate the different ways of the spread of the infection in different areas, and specifically in Canada, Mexico, and the European Union states. For this purpose, for each area, official data on infection in 2020 are used to depict, analyze, and compare the monthly contagion's curves and the Rt index, both in absolute and relative terms. © Springer Nature Switzerland AG 2023. All rights reserved.

Impact of Regional Mobility on Air Quality during COVID-19 Lockdown in Mississippi, USA Using Machine Learning.

Social distancing measures and shelter-in-place orders to limit mobility and transportation were among the strategic measures taken to control the rapid spreading of COVID-19. In major metropolitan areas, there was an estimated decrease of 50 to 90 percent in transit use. The secondary effect of the COVID-19 lockdown was expected to improve air quality, leading to a decrease in respiratory diseases. The present study examines the impact of mobility on air quality during the COVID-19 lockdown in the state of Mississippi (MS), USA. The study region is selected because of its non-metropolitan and non-industrial settings. Concentrations of air pollutants-particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ozone (O3), nitrogen oxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)-were collected from the Environmental Protection Agency, USA from 2011 to 2020. Because of limitations in the data availability, the air quality data of Jackson, MS were assumed to be representative of the entire region of the state. Weather data (temperature, humidity, pressure, precipitation, wind speed, and wind direction) were collected from the National Oceanic and Atmospheric Administration, USA. Traffic-related data (transit) were taken from Google for the year 2020. The statistical and machine learning tools of R Studio were used on the data to study the changes in air quality, if any, during the lockdown period. Weather-normalized machine learning modeling simulating business-as-scenario (BAU) predicted a significant difference in the means of the observed and predicted values for NO2, O3, and CO (p < 0.05). Due to the lockdown, the mean concentrations decreased for NO2 and CO by -4.1 ppb and -0.088 ppm, respectively, while it increased for O3 by 0.002 ppm. The observed and predicted air quality results agree with the observed decrease in transit by -50.5% as a percentage change of the baseline, and the observed decrease in the prevalence rate of asthma in MS during the lockdown. This study demonstrates the validity and use of simple, easy, and versatile analytical tools to assist policymakers with estimating changes in air quality in situations of a pandemic or natural hazards, and to take measures for mitigating if the deterioration of air quality is detected.

On the Methodological Aspects of the Clinical Trials for COVID-19 Conducted in the First Year of the Pandemic: A Descriptive Analysis.

In 2020, the whole planet was plagued by the extremely deadly COVID-19 pandemic. More than 83 million people had been infected with COVID-19 while more than 1.9 million people around the planet had died from this virus in the first year of the pandemic. From the first moment, the medical community started working to deal with this pandemic. For this reason, many clinical trials have been and continue to be conducted to find a safe and efficient cure for the virus. In this paper, we review the 96 clinical trials, registered in the ClinicalTrials.gov database, that had been completed by the end of the first year of the pandemic. Although the clinical trials contained significant heterogeneity in the main methodological features (enrollment, duration, allocation, intervention model, and masking) they seemed to be conducted based on an appropriate methodological basis.

Two Years Later: How COVID-19 Has Shaped the Teacher Workforce

The unprecedented challenges of teaching during COVID-19 prompted fears of a mass exodus from the profession. We examine the extent to which these fears were realized using administrative records of Massachusetts teachers between 2015–2016 and 2021–2022. Relative to prepandemic levels, average turnover rates were similar going into the fall of 2020 but increased by 17% (from 15.0% to 17.5%) going into the fall of 2021. The fall 2021 increases were particularly high among newly hired teachers (31% increase) but were lower among Black and Hispanic/Latinx teachers (5% increases among both groups). Gaps in turnover rates between schools serving higher and lower concentrations of economically disadvantaged students narrowed during the first 18 months of the pandemic. The same holds true for gaps in turnover between schools serving higher and lower shares of Black and Hispanic/Latinx students. Together, these findings highlight important differences in teachers' responses to the pandemic across subgroups and the need to improve early-career retention to ensure long-term stability within the teacher workforce.

#WashTheHate: Understanding the Prevalence of Anti-Asian Prejudice on Twitter During the COVID-19 Pandemic

Prejudice and hate directed toward Asian individuals has increased in prevalence and salience during the COVID-19 pandemic, with notable rises in physical violence. Concurrently, as many governments enacted stay-at-home mandates, the spread of anti-Asian content increased in online spaces, including social media. In the present study, we investigated temporal and geographical patterns in social media content relevant to anti-Asian prejudice during the COVID-19 pandemic. Using the Twitter Data Collection API, we queried over 13 million tweets posted between January 30, 2020, and April 30, 2021, for both negative (e.g., #kungflu) and positive (e.g., #stopAAPIhate) hashtags and keywords related to anti-Asian prejudice. In a series of descriptive analyses, we found differences in the frequency of negative and positive keywords based on geographic location. Using burst detection, we also identified distinct increases in negative and positive content in relation to key political tweets and events. These largely exploratory analyses shed light on the role of social media in the expression and proliferation of prejudice as well as positive responses online. © 2022 IEEE.

Observation of Online vs Offline Learning Experience

As the outbreak of COVID-19 increased in various countries. India is also majorly affected with the COVID-19 by that education system is affected, and it has transferred the traditional face-to-face teaching to online education platform. Considering student's perspective on both online and offline learning mode in India, we conducted a survey to collect the data. In that survey questionnaire, focus was on the factors and situation which can affect the education system. Using that data, we used Kruskal Wallis test to collect the evidence for which learning mode is better and Naive Bayes Algorithm, we were able to conclude the results. © 2022 IEEE.

The Long-Term Solvency of Teacher Pension Plans: How We Got to Now and Prospects for Recovery

The COVID-related financial market decline and economic recession have raised new concerns regarding the financial sustainability of retirement plans for state and local government employees, the largest group of whom is public school teachers. Using data from the Public Plans Database and the National Income and Product Accounts, I analyze teacher pension plans over the 2001–2019 period, seeking to answer questions regarding teacher pensions' funded status, investment decisions and returns, adequacy of contributions, and generosity of benefits. These data show that teacher pension funding peaked at the beginning of the 2001–2019 period due to the tech bubble's inflation of asset values, but then it declined thereafter due to investment returns that significantly underperformed assumptions, failures by sponsoring governments to consistently make full contributions, and increases in the generosity of pension benefits. School districts will face substantial funding challenges in the post-COVID period, as investment losses are factored into contribution rates, government revenues available to make contributions shrink, and education funding from state governments comes under pressure. I outline several policy alternatives that policymakers may consider, but none would make restoring teacher pensions to full funding a painless process. © 2022 AERA.

How Did Colleges Disburse Emergency Aid During COVID-19? An Implementation Analysis of the Higher Education Emergency Relief Fund

To address the unprecedented challenges of the COVID-19 pandemic, Congress authorized the Higher Education Emergency Relief Fund (HEERF I) in March 2020 with over $6 billion allocated for emergency financial aid. In this paper, we utilize the administrative burden framework to analyze HEERF I implementation for a stratified random sample of colleges, focusing on the implications for equity. We find that disbursement policies varied along two dimensions: (1) whether they imposed burdens on students by requiring applications and proof of hardship and (2) whether they targeted needy students and varied the amount of aid according to need. When we examine sectoral differences, we find that private for-profit colleges were more likely to place higher burden on students, whereas public and minority-serving institutions were more likely to reduce burden. © 2023 AERA.

Exploring Marketing Innovation on MSMEs in Indonesia: A Descriptive Study

This research aims to describe the data by measuring the demographic survey of MSMEs in Indonesia with innovation. This study also explicitly explores the interactions between demographic data elements, especially gender with the most selected and used innovation in COVID-19 pandemic situation. Utilizing cross-sectional survey data from 300 Indonesian MSMEs owners, this study is empirically tested using descriptive analysis. Cross-tabulation is also used to examine demographic data elements, particularly those related to gender and marketing innovation. The descriptive analysis frequency data shows that marketing innovation has a greater impact on the performance of MSMEs during the COVID-19 pandemic than product innovation,, process innovation and organizational innovation. Additionally, this study's cross-tabulation of marketing innovation and gender shows that men tend to agree more on items MI2 and MI3 it's because more flexible and convenient in distributing products especially during COVID-19 pandemic crisis and women tend to agree on MI1 it's because women more active in social media than men. The findings show that demography, especially in gender, has an influence on the tendency to use marketing innovation decisions in COVID-19 pandemic situation. Therefore, the results of this study will increase our understanding of MSME performance and innovation. It also creates an understanding for MSMEs owners of gender based MSME enterprises in Indonesia. © 2022 WSEAS TRANSACTIONS on SYSTEMS. All rights reserved.

Open science progress: A literature assessment of open access articles

The open science movement has been widely adopted in multiple scientific fields across nations. Its benefit has been proven in many cases, most notably when the practice accelerated the search for solutions to the Covid-19 pandemic both in medical and socio-economic contexts. Still, the movement has faced multiple challenges, including an imbalance in the adoption of its numerous aspects. For example, the open access aspect which indicates the starting point of the movement has been widely practiced. Unfortunately, while open access is essential, an open access practice alone is not enough to pursue open science. In this work, we would like to assess the imbalance of the adoption, especially to measure how open access practice contributes to other practices, namely open data and open source as a sub-aspect of the open reproducibility research. Our assessment is based on descriptive statistic analysis of 300 open access articles from three domains, that is engineering, social and life science. Our findings indicated that the free and open source computer codes were dominantly adopted by the three scientific fields. However, social science has the lowest involvement in public data. © 2022 ACM.

Data stories and dashboard development: a case study of an aviation schedule and delay causes

In this case study, five key processes in modelling a data story of aviation data patterns during COVID-19 have been executed. It started with the collection of secondary data from relevant sources. Data inspection, transformation, and preparation activities, including data cleaning, filtering, and sampling, are all included in this work. Iterative exploratory data analysis (EDA) has been conducted to determine the pattern of each independent attribute, followed by an assessment after the data story is modelled and integrated on a dashboard. The questionnaire has been distributed and the visuals were assessed by giving respondents a few tasks to interpret stories based on their comprehension. The result shows that the data stories have been interpreted in a similar narrative by all the respondents. The overall mean score is 4.71, and this significantly shows that the respondents agree and strongly agree that the visual objects help in communicating patterns and stories. The overall process gives researchers experience and guidelines for future work. Overall, the objectives of the study have been met. Nevertheless, it gives researchers a lot of experience in interpreting data, cleansing and transformation, analysis, modelling the visualisation by selecting suitable charts, and integrating the objects together into a dashboard.

Descriptive analysis of depression among adolescents in Huangshi, China.

BACKGROUND: More adolescents suffered from depressive disorder, and what was worse, the morbidity increased annually. The situation was getting worse during COVID-19 pandemic. The prevalence of depression among adolescents in China has increased a lot due to social and economic development, family-associated reasons, academic stress, interpersonal relationships, and so on. OBJECTIVE: This study aimed to determine the prevalence, gender differences, risk factors, and abnormal illness behaviors of depression among adolescents in Huangshi, China. METHODS: A descriptive analysis was conducted based on the data from clinical interviews and self-reports by the patients. Depression was assessed and diagnosed using the DSM-5 Diagnostic and Statistical Manual of Mental Disorders. RESULTS: Depression was most frequently seen in 674 patients with mental illnesses (282, 41.84%). The male-to-female ratio was 1:2.44, and their age ranged from 9 to 18. The majority of patients are in high school (261/282, 92.55%), and the highest morbidity occurred at 16 years. More cases were diagnosed in urban than in rural areas. Genetic factors, school violence, academic stress, sleep disorders, and family-related factors were essential factors leading to depression among adolescents. Most patients had sleep disorders (84.75%). In family-related factors, left-behind children and unrecognized/misunderstood by their families were prominently diagnosed with depression. A large portion of individuals with depression felt apathetic, solitary, and sluggish and were unable to study, work, and live normally (212/282, 75.18%); they even committed suicide or attempted suicide (228/282, 80.85%) and inflicted self-harm (146/282, 51.77%). CONCLUSIONS: An increasing trend of depression has been observed since 2018, especially in 2021. This depression has led to suicide or suicidal attempts and self-harm, reflecting the severity of mental health among adolescents in Huangshi. Therefore, this study aimed to draw the attention of society, families, and schools to the importance of mental health among adolescents, providing guidance and references for the prevention, diagnosis, and treatment of young depressive disorders in China.

The Behavioral and Social Dimension of the Public Health System of European Countries: Descriptive, Canonical, and Factor Analysis.

BACKGROUND: The state and prospects of the healthcare industry of a country are among its top priorities because the quality of life and health of its citizens are indicators of its success and competitiveness. The aim of this study is to conduct a theoretical analysis and qualitative and quantitative assessments of indicators by developing an integral indicator in the context of behavioral, social, demographic, and economic factors that characterize the level of healthcare system development in European countries using multivariate statistical modeling methods. METHODS: The study was implemented using Statistica 10 and Statistica Portable statistical packages. The statistical base of the study was formed using descriptive analysis; a group of 10 European countries was identified using a cluster analysis based on the application of an iterative divisive k-means method. The degree and significance of the interrelations between the components characterizing the studied groups of indicators were determined using canonical correlations by conducting a canonical analysis. Factor modeling is conducted by applying the analysis of the main components to determine the relevant indicators for assessing the level of healthcare system development to build integral indicators of the level of healthcare system development in European countries. RESULTS: The need to improve the level of healthcare system development in European countries was confirmed. Shortcomings and possible reserves for potential improvement of the healthcare system were identified. CONCLUSIONS: The results can help public authorities, officials and employees of the healthcare sector organize and conduct effective, timely, high-quality regulation and adjustment of the regulatory and legislative framework to improve healthcare system development.

Healthcare Providers' Adherence to Recommended Pneumococcal and Influenza Vaccination in Patients Discharged with Respiratory Diseases from General Medical Wards.

The periodic assessment of adherence to vaccination recommendations is an essential component of any vaccination process. This study aimed to investigate the adherence of healthcare providers to the international recommendations on influenza and pneumococcal vaccine in patients discharged from the internal medicine department with respiratory diseases. All medical records of adult patients who are 18 years of age and older with respiratory illnesses and who were discharged in January-February, May-June, and October-November of 2018 were retrospectively analyzed. A total of 264 discharge summaries from 190 patients were included in this analysis. The mean age was 55.5 years, with 54.7% of them being males. Pneumonia was the leading cause of hospitalization (63.7%), followed by asthma or chronic obstructive pulmonary disease (COPD) exacerbation (27.4%). None of the discharged patients had immunization recommendations at discharge or a documented immunization request within 6 months of discharge from the hospital. The findings of this study demonstrated that healthcare providers need to pay more attention to adhering to the global recommendations on influenza and pneumococcal vaccine among patient who were recently discharged with respiratory disease. Additional measures are needed to improve adherence to routinely recommended vaccines among adults with respiratory diseases.

Barriers and facilitators influencing EBP readiness: Building organizational and nurse capacity.

BACKGROUND: Organizational supported evidence-based practice (EBP) enables nurses to be change agents and impact patient outcomes. Globally, a multitude of barriers limits EBP implementation, evaluation, and dissemination, which include time constraints, staff, resource access, education, technology, and fiscal support. These barriers and other disenfranchising elements hinder nurses' ability to actualize EBP and change practice within their workplace. AIMS: This study describes the EBP readiness, barriers, and facilitators reported by inpatient registered nurses (RNs) employed in a nationwide healthcare system before COVID-19. METHODS: The study employed a cross-sectional descriptive survey design using the 2005 Nursing EBP Survey for RN EBP readiness. The setting included 14 hospitals in Southern California. The survey was deployed in November 2016 and closed after 23 weeks. Descriptive statistics analyzed demographics and EBP scores, with inferential statistics for associations between demographics and EBP scores. ANOVA examined differences between EBP scores, service lines, years of employment, and education level. A content approach synthesized open-ended barrier and facilitator questions into seven specific themes. RESULTS: Seven hundred and twenty-four nurses completed the survey. Overall, the scores of inpatient RNs were highest scores for Practice Climate, suggesting the health system fosters a climate conducive to EBP. Scores were lowest for Data Collection and Implementation. Qualitative themes were: (1) Everyone Involved in EBP Implementation, (2) Fear and Resistance to Change, (3) Protected Release Time, (4) Knowing EBP Culture Outside of Current Organization, (5) Organizational Communication and Education, (6) Management and Leadership Support, and (7) Pragmatic Solutions to Facilitate EBP. Fear and Resistance to Change cut across all themes. LINKING EVIDENCE TO ACTION: Nurses at all organizational levels from the C-suite to the bedside can create strategies to determine essential EBP readiness components, including EBP mentors to guide knowledge uptake activities. Pragmatic solutions for EBP capacity require frontline nurse feedback, commitment, and partnership with nursing leaders.

Factors Affecting E-Wallet Usage in Sarawak

E-wallet is a part of the fintech solution that provides customer convenience through fast speed of transaction using RFID technology, QR code and stable internet connection. The usage of e-wallet in Malaysia and Sarawak has risen in the past few years and accelerated during the Covid-19 pandemic crisis due to the needs of contactless payment to reduce the spread of the virus. However, the usage of e-wallet and factors that affect the usage of e-wallet in Sarawak has not been identified through research. Therefore, this research aims to identify the factors influencing e-wallet usage and evaluate the factors using Technology Acceptance Model (TAM) affecting Sarawakians perception towards e-wallet in general and towards Sarawak's own e-wallet app, SarawakPay. Data collection of online questionnaires have been distributed and 111 responses was analyzed using descriptive analysis and correlation analysis as well as multiple linear regression to obtain mean and standard deviation values. Five formulated hypotheses were tested using multiple linear regression showing a significant and positive relationship among the TAM variables. Descriptive analysis results have also shown that top factors affecting usage of SarawakPay is performance expectancy and perceived value. The result from this research indicates that the usage of e-wallet in Sarawak is still at medium level. The evaluation using TAM shows that there is significant relationship between the Technological and Social factors to the usage of e-wallet in Sarawak. © 2022 IEEE.

The impact of the COVID-19 Pandemic on Purchasing Priorities of Generation X and Y Consumers

This paper presents the second part of the research conducted at Riga Technical University aimed to explore the impact of the COVID-19 pandemic on Generation X (Gen X) and Generation Y (Gen Y) consumer behavior and purchasing priorities. While the changes in consumer behavior have already been analyzed and published earlier [1], the changes in purchasing priorities which might have caused changes in consumer behavior, are going to be studied in this work. The choice of these two generations is not made randomly;on the contrary, it was an intentional selection among other consumers, as they make a very active and prominent part of buyers all over the world. The research methods used are comparative descriptive analysis, Chi-square test and qualitative content analysis of data collected in an electronic survey of respondents from Asia, Europe, and America. The findings show that statistically significant differences between the changes in purchasing priorities of both generations are found for: meat and dairy products, fruit & vegetables, non-alcoholic and alcoholic drinks, clothes & shoes, body care & cosmetics, entertainment (pay TV services, computer games, etc.) and transport. Altogether, purchasing priorities of Gen X consumers were impacted by the COVID-19 pandemic less than Gen Y consumers. Copyright 2022. © by the International Institute of Informatics and Systemics. All rights reserved.

MAISoN'22: 8th International Workshop on Mining Actionable Insights from Social Networks Special Edition on Mental Health and Social Media

The eighth edition of the workshop on Mining Actionable Insights from Social Networks (MAISoN 2022) took place virtually on April 26th, 2022, co-located with the ACM Web Conference 2022 (WWW 2022). This year, we organized a special edition with focus on mental health and social media. The aim of this edition was to bring together researchers from different disciplines to discuss research that goes beyond descriptive analysis of social media data and instead investigate different techniques that use social media data for building diagnostic, predictive and prescriptive analysis models for mental health applications. This topic attracted a lot of interest from the community especially because of all the considerations surrounding the impact of social media during the COVID-19 pandemic which has impacted on people's mental health issues. © 2022 Owner/Author.

A Descriptive Analysis of Cohesion within Virtual and Physical Small Groups of Mothers in Bandwidth-Constrained Communities in Cape Town

Isolation contributes to deteriorating health outcomes during the first 1000 days of a child's life (the period from conception to two years). Mothers and their growing babies are at risk of pregnancy-related complications and malnutrition during this sensitive period due to inadequate information. This study describes how a faith-based organization (FBO) in Cape Town leverages available resources in both physical and virtual spaces to support mothers through antenatal classes. We observed seven small groups in their physical spaces, interviewed seven mothers and analyzed fifteen WhatsApp chat groups to understand the group structure, dynamics, and interactions. When the model was introduced to the mothers in the physical and virtual spaces simultaneously, cohesion was achieved and sustained. However, during the COVID-19 pandemic, where strong indications of stress and isolation were evident, a strange paradox was noted: all groups showed weak ties (with minimal communication among members). It was hard to explain the non-commitment despite efforts from the moderators to encourage sharing among mothers. We identified two underlying causes: a minimal sense of belonging to the group and bandwidth constraints. Further analysis showed that bandwidth constraints digitally excluded some mothers from active participation. These findings indicated the need for HCI and technology designers to design less bandwidth-intensive interactive platforms for inclusivity. © 2022 ACM.

Between Awareness and Acceptance: a more mature School Teachers' Perspective on Integrated Learning one year after the pandemic outbreak

One year after the outbreak of the pandemic that provoked a forced and massive adoption of technology enhanced learning practices, followed by a continuous evolution of their delivery modalities (on-line learning, blended learning, parallel blended learning, hybrid learning) and, finally, by a strong commitment to come back to a "new normal", we have investigated, by mean of a survey, the evolution of: a) perceptions and perspectives of Italian school's teachers about integrated learning;b) the undergoing innovation process characterized by unprecedented features and vastness. The exploration has been conducted by integrating perspectives and factors introduced in the past by several models - TAM, UTAUT, DOI, TOE, KAM - to describe technology innovation and adoption processes. We observed a higher perceived teachers' technological and pedagogical preparation, together with a higher readiness of the schools to react to unexpected events or sudden prescriptions. A readiness that should be ascribed mainly to the quality of the management and to an increase in the level of collaboration and cohesion among the actors of the learning process, rather than to an enhancement of the technological infrastructures. Collaboration, indeed, emerges as the main peculiarity of this last year, an engine capable to foster the spread of competences and a beacon capable to guide the choice of teaching practices. The influence of contextual factors appears not relevant and that of the "perceived values" somewhat marginal. As far as the innovation process: the awareness phase developed satisfactory and, in parallel, the acceptance phase also started. The possible transition to the adoption phase appears uncertain and not easy to characterize. At the time of the survey, however, the teachers perceived, the integrated learning as a modality that could be used in the future to realize 36% of the school activities.