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In terms of scale, shock, and disenfranchisement, the disruption to formal education arising from COVID-19 has been unprecedented. Anecdotally, responses from teachers and educators around the world range from heightened caution to being inspired by distance education as the "new normal." Of all the challenges, face-to-face and formal teaching have been most heavily affected. Despite some education systems demonstrating resilience, a major challenge is sustaining quality and inclusiveness in formal education suddenly delivered at a distance. In probing these issues, this article profiles international perspectives on the role of open education in responding to the impact on formal school and higher education caused by the COVID-19 pandemic. We proceed by highlighting and analysing practices and case studies from 13 countries representing all global regions, identifying and discussing the challenges and opportunities that have presented themselves. Reports cover the period from the beginning of 2020 until 11 March 2021, the first anniversary of the COVID-19 outbreak as declared by the World Health Organization. In our comparative study, we identify seven key aspects of which three (missing infrastructure and sharing OER, open education and access to OER, and urgent need for professional development and training for teachers) are directly related to open education at a distance. After comparing examples of existing practice, we make recommendations and offer insights into how open education strategies can lead to interventions that are effective and innovative--to improve formal education at a distance in schools and universities in the future.

This study uses an education in emergencies (EiE) lens and a scientometric approach to examine the educational research landscape during the COVID-19 pandemic by analyzing 95,628 publications indexed in the Web of Science Core Collection database from 2020 to February 2023. It employed descriptive and network approaches to map growth trajectory, productivity, social structure, conceptual structure, and research methodologies used in the retrieved sources. The findings reveal a steady increase in publications on education and COVID-19 since the onset of the pandemic. However, the majority of productive countries and institutions are in the Global North, with limited representation from the Global South, except for China. English is the dominant language in publications, and funding agencies from English-speaking countries are the most active. The most frequently occurring keywords revolve around performativity, institutions, teaching methodologies, attitudes, and experiences, while keywords related to social justice are a peripheral focus. Publications mainly focus on technical and methodological aspects of education, such as online teaching and learning. Most productive journals represent a mix of foci and are not limited to distance learning. The extracted literature showcases diversity in research methodologies used. Future studies should use systematic reviews on narrow topics to evaluate the effects of the pandemic, inform decision-making, enhance education system resilience, and envision a more equitable education system. The study's contributions are notable for its unique EiE perspective, comprehensive scope, extensive data extraction, and meticulous examination of research design, effectively addressing limitations in bibliometric software.

Background/purpose: The current study aims to analyze the thematic structures and trends of scientific publications that examine the relationship between the COVID-19 pandemic and education, while presenting a roadmap for future research on this topic. Materials/methods: The data were obtained from the Web of Science Core Collection (WoSCC) bibliographic database by identifying the publications that examine the relationship between the COVID-19 pandemic and education, then were analyzed using bibliometric methodology and content analysis. VOSviewer, GraphPad softwares, and visualization maps were used to analyze the data and to present the findings. Results: The results of the study show that publications examining the relationship between the COVID-19 pandemic and education focused on "online education" and "teacher education," while the countries that contributed the most to publications on this issue were USA, United Kingdom, Canada, and Spain. It was determined that most publications preferred the "theoretical model" and the majority of the research data were obtained through "scale/interview forms." Furthermore, the findings of this study revealed that during the COVID-19 pandemic period, the editorial/refereeing processes of the articles submitted to academic journals were carried out very quickly and the articles were published unusually quickly. Conclusion: This study indicated that the majority of scientific studies on COVID-19 are focused on the field of health, and that there is limited edition research on COVID-19-related education. To the best of the authors' knowledge, the current study is the first research article in the international literature to examine the thematic structures and trends of scientific publications on the relationship between solely education and COVID-19 through bibliometric and content analysis; and contributes to the knowledge base on COVID-19-related education by mapping the existing knowledge.

This rapid systematic review aims to examine emerging evidence on the effects of COVID-19 on educational institutions and assess the prevalence of e-learning changes in the sector. This paper reviews literature on learning, teaching, and assessment approaches adopted since the COVID-19 outbreak, and assesses the impact on the sector, staff, and students, summarizing findings from peer-reviewed articles. It categorizes these into five key themes: (1) digital learning; (2) e-learning challenges; (3) digital transition to emergency virtual assessment (EVA); (4) psychological impact of COVID-19; and (5) creating collaborative cultures. This represents the first systematic review of COVID-19's impact on education, clarifying current themes being investigated. The author suggests that the term 'emergency virtual assessment' (EVA) is now added for future research discussion. Finally, the paper identifies research gaps, including researching the impact on lesser developed countries, the psychological impact of transition, and the important role of leadership and leadership styles during the transition and handling of the pandemic.

Social media has significantly transformed how political discussions and deliberations occur, mainly by providing a digital realm for the public sphere. This study aims to analyse the extent of polarised opinions across Spain, Italy and the United Kingdom regarding COVID-19 during 2020 within social media. To do this, we examined YouTube comments (n=111,808) using automatic analysis and machine-learning techniques based on algorithms. This methodological strategy denoted an innovative and unique quantitative approach for this field of study. In line with previous research, the hypothesis was that the degree of polarization does not crystallize in the same manner in different countries' digital spheres. Therefore, it could be said that higher levels of polarization occur amongst Southern European countries like Spain and Italy (both countries adhering to a polarised pluralism model), compared to other countries ascribing to the liberal model (the United Kingdom in our study), which provides evidence supporting previous research studies. The results confirmed the hypothesis that the polarization of digital deliberation between Spain and Italy is higher than in the United Kingdom. But, also, the findings based on more disaggregated analysis suggest that the most polarized attitudes are even rewarded by other users in Mediterranean countries.

Face coverings have been key in reducing the spread of COVID-19. At the same time, they have hindered interpersonal communication, particularly for those who rely on speechreading to aid communication. The available research indicated that deaf/hard of hearing (HoH) people experienced great difficulty communicating with people wearing masks and negative effects on wellbeing. Here we extended these findings by exploring which factors predict deaf/HoH people's communication difficulties, loss of information, and wellbeing. We also explored the factors predicting perceived usefulness of transparent face coverings and alternative ways of communicating. We report the findings from an accessible survey study, released in two written and three signed languages. Responses from 395 deaf/HoH UK and Spanish residents were collected online at a time when masks were mandatory. We investigated whether onset and level of deafness, knowledge of sign language, speechreading fluency, and country of residence predicted communication difficulties, wellbeing, and degree to which transparent face coverings were considered useful. Overall, deaf/HoH people and their relatives used masks most of the time despite greater communication difficulties. Late-onset deaf people were the group that experienced more difficulties in communication, and also reported lower wellbeing. However, both early- and late-onset deaf people reported missing more information and feeling more disconnected from society than HoH people. Finally, signers valued transparent face shields more positively than non-signers. The latter suggests that, while seeing the lips is positive to everyone, signers appreciate seeing the whole facial expression. Importantly, our data also revealed the importance of visual communication other than speechreading to facilitate face-to-face interactions.

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients. [ABSTRACT FROM AUTHOR]

Introduction: Monitoring the evolution of COVID-19 has been essential for health decision-making. But this requires reliable numbers of the infected, dead and hospitalized, often difficult to have for multiple reasons. The use of fast and reliable estimation techniques, such as indirect surveys, is an option. Objectives: To present the CoronaSurveys project, which monitors COVID-19 by combining indirect surveys with the Network Scaleup Method (NSUM). Methodology: The system uses indirect online anonymous surveys to inquire about COVID-19, and the NSUM method to estimate cases. The system offers multi-language surveys with questions to track active cases, new cases, and fatalities, among others. Results: CoronaSurveys has been operating since March 2020, and continues to collect data, with over one hundred responses to date (over one million samples). The system has made good estimates for Spain and the United Kingdom, among other countries. Conclusion: This system is suitable in countries with limited health infrastructure or in situations of lack of knowledge about the pandemic, such as at the beginning of COVID-19, because its implementation cost is small and it requires simple devices to use it and few participants to obtain good estimates. [ABSTRACT FROM AUTHOR]

Background: On admission to hospital, patients with community-acquired pneumonia (CAP), undergo extensive diagnostic testing. Two high-throughput laboratory-based PCR panels which return a result in 5.5 hours (h) have been developed to test for pathogens commonly associated with upper (Respiratory 1 Panel) and lower (Respiratory 3 Panel) respiratory tract infections (GeneFirst, Oxford). These could replace multiple diagnostic tests currently used. Methods: An online survey, completed by senior clinicians in the UK, France and Spain, was used to collect data on the diagnostic testing of immunocompetent and immunocompromised adults admitted to hospital with CAP, including the cost of diagnostics. Data were used to inform a cost-comparison model. For each country, the average cost of diagnostic testing per patient was calculated separately for immunocompetent and immunocompromised patients. The model compared three testing strategies with standard of care (SoC). In the Panel 1 strategy, the Respiratory 1 Panel was used for patients that would otherwise have tests which could be replaced by Respiratory 1 Panel, equivalent strategies for Respiratory 3 Panel and for both panels combined were assessed. Results: In total, 48 surveys were completed (UK = 17; France = 15; Spain = 16). Compared with SoC, the Panel 1 + 3 strategy was most favourable, resulting in cost savings for immunocompetent and immunocompromised patients respectively, of €22.09 (£18.50) and €26.12 (£21.88) in the UK, €99.60 and €108.77 in France and €27.07 and €51.87 in Spain. Conclusion: In all three countries, the use of these respiratory panels could reduce the average cost of diagnostics used for patients admitted to hospital with CAP. [ABSTRACT FROM AUTHOR]

We conducted an updated meta-analysis to evaluate the 30-day mortality of hip fractures during the COVID-19 pandemic and assess mortality rates by country. We systematically searched Medline, EMBASE, and the Cochrane Library up to November 2022 for studies on the 30-day mortality of hip fractures during the pandemic. Two reviewers used the Newcastle–Ottawa tool to independently assess the methodological quality of the included studies. We conducted a meta-analysis and systematic review including 40 eligible studies with 17,753 patients with hip fractures, including 2280 patients with COVID-19 (12.8%). The overall 30-day mortality rate for hip fractures during the pandemic was 12.6% from published studies. The 30-day mortality of patients with hip fractures who had COVID-19 was significantly higher than those without COVID-19 (OR, 7.10; 95% CI, 5.51–9.15; I2 = 57%). The hip fracture mortality rate increased during the pandemic and varied by country, with the highest rates found in Europe, particularly the United Kingdom (UK) and Spain. COVID-19 may have contributed to the increased 30-day mortality rate in hip fracture patients. The mortality rate of hip fracture in patients without COVID-19 did not change during the pandemic. [ABSTRACT FROM AUTHOR]

During the outbreak of a disease caused by a pathogen with unknown characteristics, the uncertainty of its progression parameters can be reduced by devising methods that, based on rational assumptions, exploit available information to provide actionable insights. In this study, performed a few (~6) weeks into the outbreak of COVID-19 (caused by SARS-CoV-2), one of the most important disease parameters, the average time-to-recovery, was calculated using data publicly available on the internet (daily reported cases of confirmed infections, deaths, and recoveries), and fed into an algorithm that matches confirmed cases with deaths and recoveries. Unmatched cases were adjusted based on the matched cases calculation. The mean time-to-recovery, calculated from all globally reported cases, was found to be 18.01 days (SD 3.31 days) for the matched cases and 18.29 days (SD 2.73 days) taking into consideration the adjusted unmatched cases as well. The proposed method used limited data and provided experimental results in the same region as clinical studies published several months later. This indicates that the proposed method, combined with expert knowledge and informed calculated assumptions, could provide a meaningful calculated average time-to-recovery figure, which can be used as an evidence-based estimation to support containment and mitigation policy decisions, even at the very early stages of an outbreak. [ABSTRACT FROM AUTHOR]

Background and Aim: COVID-19 is a highly contagious infectious disease, and it has affected people's daily life and has raised great concern for governments and public health officials. Forecasting its future behavior may be useful for allocating medical resources and defining effective strategies for disease control, etc. Materials and Methods: The collected data was the cumulative and the absolute number of confirmed, death, and recovered cases of COVID-19 from February 20 to July 03, 2021. We used hierarchical cluster analysis. To forecast the future behavior of COVID-19, the Auto-Regressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), Automatic Forecasting Procedure (Prophet), Naive, Seasonal Naive (s-Naive), boosted ARIMA, and boosted Prophet models were used. Results: The results of clustering showed a similar behavior of coronavirus in Iran and other countries such as France, Russia, Turkey, United Kingdom (UK), Argentina, Colombia, Italy, Spain, Germany, Poland, Mexico, and Indonesia. It also revealed similar patterns of SARS-CoV-2 for the same countries in six groups. Results showed that XGBoost models' family had higher accuracy than other models. Conclusion: In Iran, COVID-19 showed similar behavior patterns compared to the studied developed countries. The family of XGBoost models showed practical results and high precision in forecasting behavior patterns of the virus. Concerning the rapid spread of the virus worldwide, these models can be used to forecast the behavior patterns of SARS-CoV-2. Preventing the spread of the coronavirus, controlling the disease, and breaking down its chain necessitates community assistance, and in this mission, the role of statisticians cannot be neglected. [ABSTRACT FROM AUTHOR]

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Although the health care systems in Europe are considered the global benchmark, European nations were severely affected by the coronavirus disease 2019 (COVID-19) pandemic. This manuscript aimed to examine the strategies implemented to combat the COVID-19 pandemic by France, the United Kingdom, Spain, Italy, Germany, and Russia and their outcomes in terms of the number of cases, testing, and deaths. This is the first review of its kind that extensively analyzes the preparedness, mitigation, and response strategies against the COVID-19 pandemic adopted by these nations. This paper further suggests a strategic preparedness model for future pandemics. From the analysis, we found that a decentralized approach, prompt decision-making and timely execution, coordination between local health authorities, and public participation in the implementation of strategies could substantially reduce the case fatality rate. Nations with a high percentage of gross domestic product invested in the health sector, as well as more nurses, physicians, hospital beds, intensive care unit beds, and ventilators, better managed the pandemic. Instead, nations that postponed their pandemic response by delaying tracking, tracing, testing, quarantine, and lockdown were badly affected. The lessons learned from the present pandemic could be used as a guide to prepare for further pandemics. [ABSTRACT FROM AUTHOR]

Background In responding to Covid-19, governments have tried to balance protecting health while minimizing gross domestic product (GDP) losses. We compare health-related net benefit (HRNB) and GDP losses associated with government responses of the UK, Ireland, Germany, Spain and Sweden from UK healthcare payer perspective. Methods We compared observed cases, hospitalizations and deaths under 'mitigation' to modelled events under 'no mitigation' to 20 July 2020. We thus calculated healthcare costs, quality adjusted life years (QALYs), and HRNB at £20,000/QALY saved by each country. On per population (i.e. per capita) basis, we compared HRNB with forecast reductions in 2020 GDP growth (overall or compared with Sweden as minimal mitigation country) and qualitatively and quantitatively described government responses. Results The UK saved 3.17 (0.32–3.65) million QALYs, £33 (8–38) billion healthcare costs and £1416 (220–1637) HRNB per capita at £20,000/QALY. Per capita, this is comparable to £1455 GDP loss using Sweden as comparator and offsets 46.1 (7.1–53.2)% of total £3075 GDP loss. Germany, Spain, and Sweden had greater HRNB per capita. These also offset a greater percentage of total GDP losses per capita. Ireland fared worst on both measures. Countries with more mask wearing, testing, and population susceptibility had better outcomes. Highest stringency responses did not appear to have best outcomes. Conclusions Our exploratory analysis indicates the benefit of government Covid-19 responses may outweigh their economic costs. The extent that HRNB offset economic losses appears to relate to population characteristics, testing levels, and mask wearing, rather than response stringency. [ABSTRACT FROM AUTHOR]

Background: With the outbreak of COVID-19 pandemic across the world, people have suffered an unexpected setback to their mental health. As psychological support is being provided to patients and healthcare workers, the general population and university students go unnoticed. This review aims to present existing literature that reports the effects of COVID-19 on psychological outcomes of the general population and university students in different countries. Methods: A manual search was conducted on PubMed, Google Scholar and Mendeley from inception to 31st January 2021. Articles were selected based on the predetermined eligibility criteria. Results: During COVID-19 pandemic, relatively high rates of depression (4.5% to 72.3%), anxiety (12.7% to 85.7%) and stress (5% to 90.1%) were reported in the general population as well as in university students, depression (3% to 70.5%), anxiety (9% to 63.3%) and stress (61.5% to 25%) in India, Nepal, Pakistan, China, Spain, US, UK, France, Egypt, Ethiopia, Bangladesh, Nigeria and Saudi Arabia. Risk factors associated include female gender, younger age group (≤40 years), unemployment, student status, and frequent exposure to social media/news concerning COVID-19. Conclusions: The COVID-19 pandemic is associated with highly significant levels of psychological disorders such as depression, anxiety and stress. Alleviating the hazardous effects of COVID-19 on mental health should be given due attention internationally. [ABSTRACT FROM AUTHOR]

Background: Since December 2019, the world has been facing one of the most critical health threats of the last decades. In March 2021, the official number of deaths passed 2.6 million worldwide. Most countries have developed policies to control the disease. Nevertheless, countries have experienced different outcomes related to their various adapted policies. Complementing our first report, in this article, we report our findings of comparing the policies adopted to combat coronavirus disease 2019 (COVID-19) in Iran, with those from nine selected countries, including China, Japan, South Korea, Singapore, Germany, the United States, the United Kingdom, Spain, and Italy, to draw evidence-informed policy lessons. Methods: This is a qualitative study conducted based on document analysis related to COVID-19 policies in Iran and nine selected countries. Using a deductive approach, data were extracted and analyzed based on the components of the WHO Building Blocks Framework. Finally, we compared the Iranian policies with the nine selected countries. Results: Documents analysis revealed a spectrum of policies, which have led to a variety of outcomes. Based on our findings, three main strategies (widespread testing, comprehensive contact tracing, and timely measures) were the most effective directions to combat COVID-19. Conclusion: The experience of the first and second waves of COVID-19 showed that the risk of coronavirus is serious and will continue until a vaccine or decisive treatment is achieved. Therefore, countries are required to adopt appropriate and tailored policies to deal with this crisis effectively. Applying the experiences from the previous waves is essential for more efficient performance in the likely upcoming waves. INSET: 260. [ABSTRACT FROM AUTHOR]

Background: To control the spread of the new SARS-CoV-2 infection's disease (COVID-19), appropriate precautionary behaviors by the public should be promoted. There are international differences in public cognitive and behavioral pattern, attitudes toward information sources, and anxiety about COVID-19. Information about these differences could increase understanding of the patterns of epidemic-related anxiety and behavior, and would help optimize future policies for preventing the next wave of the epidemic. Methods: To examine between-country differences in perception, attitude, and precautionary behaviors toward COVID-19, we conducted a cross-sectional study using an online questionnaire survey. Participants were adults who had been registered in Cross Marketing Group Inc. and living in the UK, Spain, or Japan. A total of 8,000 people stratified by age were recruited on a first-come, first-serve basis. Knowledge of and anxiety about COVID-19, the frequency of access and perceived credibility of several information sources, and the frequency of each precautionary behavior were examined on March 27–28, 2020, in Japan and April 17–21, 2020, in the UK and Spain. Results: Knowledge, anxiety, and the frequency of precautionary behaviors were higher in the UK and Spain than in Japan. Participants with infected acquaintances were more concerned about COVID-19. However, participants in the UK rarely wore a medical mask. Participants in the UK and Spain were more eager to obtain information about COVID-19 than those in Japan. Participants in Spain tended not to trust official information and to believe specialists' comments instead. Conclusion: The rapidity of the spread of COVID-19, cultural background, and recent political situations seemed to contribute to the international differences here. [ABSTRACT FROM AUTHOR]

Many different countries have been under lockdown or extreme social distancing measures to control the spread of COVID-19. The potentially far-reaching side effects of these measures have not yet been fully understood. In this study we analyse the results of a multi-country survey conducted in Italy (N = 3,504), Spain (N = 3,524) and the United Kingdom (N = 3,523), with two separate analyses. In the first analysis, we examine the elicitation of citizens' concerns over the downplaying of the economic consequences of the lockdown during the COVID-19 pandemic. We control for Social Desirability Bias through a list experiment included in the survey. In the second analysis, we examine the data from the same survey to predict the level of stress, anxiety and depression associated with being economically vulnerable and having been affected by a negative economic shock. To accomplish this, we have used a prediction algorithm based on machine learning techniques. To quantify the size of this affected population, we compare its magnitude with the number of people affected by COVID-19 using measures of susceptibility, vulnerability and behavioural change collected in the same questionnaire. We find that the concern for the economy and for "the way out" of the lockdown is diffuse and there is evidence of minor underreporting. Additionally, we estimate that around 42.8% of the populations in the three countries are at high risk of stress, anxiety, and depression, based on their level of economic vulnerability and their exposure to a negative economic shock. [ABSTRACT FROM AUTHOR]

We describe the outcomes in cancer patients during the initial outbreak of the COVID-19 in Europe from the retrospective, multi-center observational OnCovid study. We identified 204 cancer patients from eight centers in the United Kingdom, Italy, and Spain aged >18 (mean = 69) and diagnosed with COVID-19 between 26 February and 1 April 2020. A total of 127 (62%) were male, 184 (91%) had a diagnosis of solid malignancy, and 103 (51%) had non-metastatic disease. A total of 161 (79%) had >1 co-morbidity. A total of 141 (69%) patients had >1 COVID-19 complication. A total of 36 (19%) were escalated to high-dependency or intensive care. A total of 59 (29%) died, 53 (26%) were discharged, and 92 (45%) were in-hospital survivors. Mortality was higher in patients aged >65 (36% vs. 16%), in those with >2 co-morbidities (40% vs. 18%) and developing >1 complication from COVID-19 (38% vs. 4%, p = 0.004). Multi-variable analyses confirmed age > 65 and >2 co-morbidities to predict for patient mortality independent of tumor stage, active malignancy, or anticancer therapy. During the early outbreak of SARS-CoV-2 infection in Europe co-morbid burden and advancing age predicted for adverse disease course in cancer patients. The ongoing OnCovid study will allow us to compare risks and outcomes in cancer patients between the initial and later stages of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]