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This paper aims at identifying and explaining the correlation between the Covid-19 and multi-lingualism through cross-country research, drawing on three datasets: WHO data on the expanse of the pandemic, UNESCO data on endangered languages, and the LDI (Linguistic Diversity Index). Results establishing a direct correlation between the pandemic and multi-lingualism vary across the countries, except the USA, India, and Brazil. The three countries experiencing the highest global pandemic caseload occupy the top positions in the number of endangered languages and are among the top ten linguistically diverse countries. Drawing from the research findings, the paper addresses the criticality of investing in multi-lingualism and calls for a shift of perspective among policymakers driven by neoliberal rationale towards greater recognition and higher funding for multi-lingual education.

This paper presents a compilation of personal reflections from 66 contributors on the impact of, and responses to, COVID-19 in accounting education in 45 different countries around the world. It reveals a commonality of issues, and a variability in responses, many positive outcomes, including the creation of opportunities to realign learning and teaching strategies away from the comfort of traditional formats, but many more that are negative, primarily relating to the impact on faculty and student health and well-being, and the accompanying stress. It identifies issues that need to be addressed in the recovery and redesign stages of the management of this crisis, and it sets a new research agenda for studies in accounting education.

Since late 2019, COVID-19 has significantly impacted the world. Understanding the evolution of SARS-CoV-2 is crucial for protecting against future infectious pathogens. In this study, we conducted a comprehensive chronological analysis of SARS-CoV-2 evolution by examining mutation prevalence from the source countries of VOCs: United Kingdom, India, Brazil, South Africa, plus two countries: United States, Russia, utilizing genomic sequences from GISAID. Our methodological approach involved large-scale genomic sequence alignment using MAFFT, Python-based data processing on a high-performance computing platform, and advanced statistical methods the Maximal Information Coefficient (MIC), and also Long Short-Term Memory (LSTM) models for correlation analysis. Our findings elucidate the dynamics of SARS-CoV-2 evolution, highlighting the virus's changing behaviour over various pandemic stages. Key results include the discovery of three temporal mutation patterns-lineage distinct, long-span, and competitive mutations-with varying levels of impact on the virus. Notably, we observed a convergence of advantageous mutations in the spike protein, especially in the later stages of the pandemic, indicating a substantial evolutionary pressure on the virus. One of the most significant revelations is the predominant role of natural immunity over vaccination-induced immunity in driving these evolutionary changes. This emphasizes the critical need for regular vaccine updates to maintain efficacy against evolving strains. In conclusion, our study not only sheds light on the evolutionary trajectory of SARS-CoV-2 but also underscores the urgency for robust, continuous global data collection and sharing. It highlights the necessity for rapid adaptations in medical countermeasures, including vaccine development, to stay ahead of pathogen evolution. This research provides valuable insights for future pandemic preparedness and response strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The COVID-19 pandemic has led governments worldwide to impose extensive restrictions on citizens, some of which may have long-term impact after their removal. Education is arguably the policy domain where closure policies are anticipated to lead to greatest lasting loss, in this case learning loss. Currently, limited data exists from which researchers and practitioners can draw insightful conclusions about how to remedy the problem. In this paper, we outline the global pattern in pandemic school-closure periods and illustrate data needs through the examples drawn from Brazil and India, two large countries which experienced prolonged periods of school closures during the pandemic. We conclude with a series of recommendations for building an improved data environment at government, school and household levels, to serve the building back agenda in education, and to provide better opportunities for evidence-based policymaking thereafter., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The COVID-19 pandemic has highlighted a need for better understanding of countries' vulnerability and resilience to not only pandemics but also disasters, climate change, and other systemic shocks. A comprehensive characterization of vulnerability can inform efforts to improve infrastructure and guide disaster response in the future. In this paper, we propose a data-driven framework for studying countries' vulnerability and resilience to incident disasters across multiple dimensions of society. To illustrate this methodology, we leverage the rich data landscape surrounding the COVID-19 pandemic to characterize observed resilience for several countries (USA, Brazil, India, Sweden, New Zealand, and Israel) as measured by pandemic impacts across a variety of social, economic, and political domains. We also assess how observed responses and outcomes (i.e., resilience) of the COVID-19 pandemic are associated with pre-pandemic characteristics or vulnerabilities, including (1) prior risk for adverse pandemic outcomes due to population density and age and (2) the systems in place prior to the pandemic that may impact the ability to respond to the crisis, including health infrastructure and economic capacity. Our work demonstrates the importance of viewing vulnerability and resilience in a multi-dimensional way, where a country's resources and outcomes related to vulnerability and resilience can differ dramatically across economic, political, and social domains. This work also highlights key gaps in our current understanding about vulnerability and resilience and a need for data-driven, context-specific assessments of disaster vulnerability in the future., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Beesley et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Every year the concern from environmental pollution increases as it affects human health. In the current paper, it is analyzed the evolution of the air quality in different cities on international level related to the reduction in mobility trend due to the emergence of the pandemic. The air pollution is studied in order to achieve healthier cities in the future and create an awareness for the citizens. The COVID-19 pandemic situation was declared during the first months of 2020 and has shown (indirectly) the effects that restrictions on human activity and road traffic have on atmospheric pollutant values. This pandemic condition derived, in most cases, in mobility restrictions in order to decrease the spread of the virus through the density of population in different places and, as a result of these restrictions, pollutant presence decreased equally. This article analyzes some of the largest cities around the world, such as Tsuen Wan district in Hong Kong (China), Los Angeles (USA), London (UK), São Paulo (Brazil), Bangalore (India), Johannesburg (South Africa), and Sydney (Australia) in order to check the different mobility restriction policies established in each location, and how those restrictions led to decrease the levels of some pollutant particles such as NO 2 in the atmosphere. This should serve as a focus of awareness of the city and political interests of how it affects human activity, and those measures should be taken to reduce pollutants., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Scientometrics is a discipline that allows the analysis of the characteristics of publications in each field of knowledge using different indicators. The aim of this research was to analyse world scientific publication as to COVID-19 related to dentistry., Methods: A specialised search strategy was used to obtain all the documents published in journals indexed in the Scopus database between December 2019 and February 2022. The study variables were exported and analysed in SciVal (Elsevier)., Results: In all, 2071 documents were retrieved; of those, Oral Diseases has the highest impact with an average of 12.3 citations per publication, and the British Medical Journal was identified as the journal with the highest scientific output (107). India (292) and the UK (287) were the countries with the most published papers. The Universidade de São Paulo in Brazil was the institution with the highest number of published papers (61) and with the highest impact., Conclusions: During the pandemic, scientific publications on dentistry and COVID-19 have been increasing considerably. International collaboration has the highest percentage of publications whilst India and the UK are the countries with the highest scientific production., Competing Interests: Conflict of interest None disclosed., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

In this paper, Transfer Learning is used in LSTM networks to forecast new COVID cases and deaths. Models trained in data from early COVID infected countries like Italy and the United States are used to forecast the spread in other countries. Single and multistep forecasting is performed from these models. The results from these models are tested with data from Germany, France, Brazil, India, and Nepal to check the validity of the method. The obtained forecasts are promising and can be helpful for policymakers coping with the threats of COVID-19., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 ISA. Published by Elsevier Ltd. All rights reserved.)