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The aim of this paper is to assess the influence of selected geographical factors on the diversity of the development of the COVID-19 pandemic in Europe's regions, and on its dynamics across the continent. The work took into account 250 of NUTS-2 regions. The datasets included the course of the COVID-19 pandemic (two dependent variables), intervening actions (four variables of the research background), and potential environmental and socio-economic conditioning (twelve independent variables). The dependent variables' set was composed of two indexes: morbidity and temporal inertia. The temporal scope of the research was 23 March 2020-15 May 2022, with weekly resolution. By means of multiple linear regression model, the influence of the administrative actions and of the selected natural and socio-economic factors was assessed. Finally, a synthetic Regional Epidemic Vulnerability Index (REVI) for each individual region was calculated. It allowed us to classify the regions into three categories: resistant, neutral, or sensitive. REVI's spatial distribution indicates that the zone of above-average vulnerability occurred in the western part of Europe and around the Alps. Therefore, focus ought to extend beyond regional statistics, towards spatial relationships, like contiguous or transit position. This research also validated the strong impact of national borders.

In recent years, there has been a growing amount of discussion on the use of big data to prevent and treat pandemics. The current research aimed to use CiteSpace (CS) visual analysis to uncover research and development trends, to help academics decide on future research and to create a framework for enterprises and organizations in order to plan for the growth of big data-based epidemic control. First, a total of 202 original papers were retrieved from Web of Science (WOS) using a complete list and analyzed using CS scientometric software. The CS parameters included the date range (from 2011 to 2022, a 1-year slice for co-authorship as well as for the co-accordance assessment), visualization (to show the fully integrated networks), specific selection criteria (the top 20 percent), node form (author, institution, region, reference cited, referred author, journal, and keywords), and pruning (pathfinder, slicing network). Lastly, the correlation of data was explored and the findings of the visualization analysis of big data pandemic control research were presented. According to the findings, "COVID-19 infection" was the hottest cluster with 31 references in 2020, while "Internet of things (IoT) platform and unified health algorithm" was the emerging research topic with 15 citations. "Influenza, internet, China, human mobility, and province" were the emerging keywords in the year 2021-2022 with strength of 1.61 to 1.2. The Chinese Academy of Sciences was the top institution, which collaborated with 15 other organizations. Qadri and Wilson were the top authors in this field. The Lancet journal accepted the most papers in this field, while the United States, China, and Europe accounted for the bulk of articles in this research. The research showed how big data may help us to better understand and control pandemics.

This paper conducts an analysis of the impact of COVID-19 and digital transformation (DT) on the financial performance of European listed companies. Using a panel data regression model from 2015 to 2021, the study analyzed the financial performance of 2179 companies. The sample of companies was chosen based on the availability of financial statements and aimed to examine the effects of COVID-19 and DT on financial performance, as measured by return on assets (ROA). The study used a fixed-effect model and checked for robustness by introducing return on equity (ROE) as a dependent variable. The results indicated that COVID-19 had a negative significant impact on financial performance, while DT had a positive significant impact, consistent with previous research. This study provides valuable insights into the impacts of the COVID-19 pandemic and DT on the financial performance of listed companies. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, most workers had to work from home due to the successive lockdowns across European countries. This constraint posed significant challenges to many workers and companies regarding working conditions and work–life balance. Framed by the job demands–resources model (JD–R), the goal of this paper is to examine the association of perceived organizational support (POS) and individual resilience (IR) with work–life balance (WLB) during the COVID-19 pandemic across European countries. This goal is complemented by assessing the role of work-from-home (WFH) as a mediator. Based on a quantitative approach, data were extracted from the second round of the survey "Living, Working, and COVID-19" from Eurofound. A series of regressions using SEM-PLS tested the hypothesis. Findings reveal that WFH negatively influences WLB. POS positively influences WFH and negatively influences WLB when mediated by WFH. IR negatively influences WFH and positively influences WLB when mediated by WFH. These results have essential theoretical implications related to the relations between individual and organizational resources and WLB and practical implications for the management of WFH, namely, the importance of providing adequate organizational resources and promoting the development of individual resources. [ABSTRACT FROM AUTHOR]

COVID-19 represents the greatest health crisis in recent human history. To date, it is still difficult to estimate its impact on mortality. This paper investigates the excess crude mortality in 27 European countries. The differences between the values observed in 2020 and 2021 with those predicted by a joinpoint regression model were evaluated. A multi-regression analysis was implemented to assess the relationship between health variables and excess mortality. Europe experienced a marked and surprising (S-value > 52) increase in crude mortality during 2020 (Δ% = +10.0%, 95% CI: [2.5; 18.7]) and 2021 (Δ% = +12.1%, 95% CI: [4.3; 21.2]). The difference between average excesses of Eastern and Western countries was not surprising (S < 2) and had little relevance (ΔE-W = −2.4, 95% CI: [−2; 7]) during 2020 but was more pronounced (S = 15, ΔE-W = +17.2, 95% CI: [11.0; 23.5]) during 2021. Excess crude mortality increased in 2021 (Δ% = +65%, 95% CI: [12.6; 118], S = 5.9). Evidence has been found for a surprising and marked negative linear relationship between COVID-19 vaccinations and excess mortality ("2021 excess mortality = A + BX4", with "A = 58 ± 7, S = 28" and "B = −0.65 ± 0.10, S = 22, Radj2 = 0.65, 95% CI: [0.38; 0.82]). In light of the current literature, these findings provide solid evidence of the substantial role of COVID-19 in the unexpected and marked excess mortality recorded in Europe. COVID-19 vaccinations have appeared to be one of the main determinants for reducing mortality. Future research should explore these aspects in more detail. [ABSTRACT FROM AUTHOR]

The massive impact caused by the COVID-19 pandemic has left no one indifferent, becoming an unprecedented challenge. The use of protections such as sanitary masks has become increasingly common, restrictions in our daily lives, such as social distancing or confinements, have had serious consequences on the economy and our welfare state. Although the measures imposed throughout the world follow the same pattern, they have been applied with different criteria depending on the country. Over extended periods of time, people tend to change their perception of an event and its magnitude, or in other words, they stop being so concerned despite the seriousness of the matter. In this paper, we introduce a new metric to quantify the degree of emotional concern of people being affected by a topic, and we confirm how populations from different countries follow this trend of downplaying the effect of the pandemic and reach a state of indifference. To do this, we propose a method to analyze the social media stream over time extracting the different emotional states from the Russel Circumplex plane and computing the shifting created by the tragic event—the pandemic. We complete this metric by incorporating searching behavior to reflect not only push contents but also pull inquiries. The resulting metric establishes a relationship between the pandemic and the emotional response by defining the degree of Emotional Concern. Although the method can be applied to any location with a significant and varied amount of geo-localized social media streams, the scope of this paper covers the most representative cities in Europe. [ABSTRACT FROM AUTHOR]

(1) Background: Italy accounts for more than 150,000 deaths due to the COVID-19 pandemic, leading the top rank in SARS-CoV-2-caused deceases in Europe. A survey on the different ways by which the COVID-19 pandemic emergency was managed in the foreign European countries compared to Italy is the purpose of this paper. (2) Methods: A literature search and various mathematical algorithms to approach a rank scoring scale were used to describe in detail the different approaches used by European countries to manage the COVID-19 pandemic emergency. (3) Results: The study showed that Italy stands at the bottom ranking for COVID-19 management due to its high mortality rate. Possible causes of the observed huge numbers of hospitalization and deaths were (a) the demographic composition of the European country; (b) its decentralized healthcare system organization; (c) the role of correct pharmacology in the early stages before hospitalization. Post-mortem examinations were of paramount importance to elucidate the etiopathogenesis of COVID-19 and to tailor a suitable and proper therapy in the early symptomatic stages of COVID-19, preventing hospitalization. (4) Conclusions: Factors such as the significant impact on elderly people, the public health organization prevalently state-owned and represented mainly by hospitals, and criticism of the home therapy approach toward SARS-CoV-2-infected people, may have concurred in increasing the number of COVID-19 deaths in Italy.

Coronavirus disease 2019 (COVID-19) has resulted in approximately 5 million deaths around the world with unprecedented consequences in people's daily routines and in the global economy. Despite vast increases in time and money spent on COVID-19-related research, there is still limited information about the factors at the country level that affected COVID-19 transmission and fatality in EU. The paper focuses on the identification of these risk factors using a machine learning (ML) predictive pipeline and an associated explainability analysis. To achieve this, a hybrid dataset was created employing publicly available sources comprising heterogeneous parameters from the majority of EU countries, e.g., mobility measures, policy responses, vaccinations, and demographics/generic country-level parameters. Data pre-processing and data exploration techniques were initially applied to normalize the available data and decrease the feature dimensionality of the data problem considered. Then, a linear ε-Support Vector Machine (ε-SVM) model was employed to implement the regression task of predicting the number of deaths for each one of the three first pandemic waves (with mean square error of 0.027 for wave 1 and less than 0.02 for waves 2 and 3). Post hoc explainability analysis was finally applied to uncover the rationale behind the decision-making mechanisms of the ML pipeline and thus enhance our understanding with respect to the contribution of the selected country-level parameters to the prediction of COVID-19 deaths in EU.

Since the beginning of the COVID-19 pandemic in March 2020, national and international authorities started to develop and update datasets to provide data to researchers, journalists and health care providers as well as public opinion. These data became one of the most important sources of information, which are updated daily and analysed by scientists in order to investigate and predict the spread of this epidemic. Despite this positive reaction from both national and international authorities in providing aggregated information on the diffusion of COVID-19, different challenges have been underlined in previously published studies. Different papers have discussed strengths and weaknesses of these types of datasets by focusing on different quality perspectives, which include the statistical methods adopted to analyse them; the lack of standards and models in the adoption of data for their management and distribution; and the analysis of different data quality characteristics. These studies have analysed datasets at the general level or by focusing the attention on specific indicators such as the number of cases or deaths. This paper further investigates issues and opportunities in the diffusion of these datasets under two main perspectives. At the general level, it analyses how data are organized and distributed to scientific and non-scientific communities. Moreover, it further explores the indicators adopted to describe the spread of the COVID-19 epidemic while also highlighting the level of detail used to describe them in terms of gender, age ranges and territorial units. The paper focuses on six European countries: Belgium, France, Germany, Italy, Spain and UK.

The present study uses the analysis of the EU's regional performance structure based on clusters to test the versatility of the regional administrative capacity in relation to three disruptive global phenomena: the economic crisis, the coronavirus epidemic and the phenomenon of refugee migration to Europe. We defined a regional performance model based on maintaining sustainability indicators in the 240 EU regions. The objectives of the study are aimed primarily at a structured assessment of regional administrative capacity in the initial version, based on statistical indicators, and in the current version, after the outbreak of the pandemic, based on quantifying the impact of the disturbing factors. Secondly, the objectives of the study are to evaluate the reaction of the administrative units according to their ability to respond to the economic problems in the region, in the sense of improving the performance of the regional economies. The methods used in this paper will be empirical (the study of the specialized literature), analytical and will contain econometric modelling and statistical processing of the data. The results of the study will allow the identification of the necessary traits to train a leader in regional performance, traits that will be useful to European decision makers in adjusting the EU regional policy. Moreover, the need to redefine the EU in terms of performance will be substantiated once again. The study is current and is based on the latest Eurostat information, pertinent tables and diagrams.

The COVID-19 pandemic severely impacted the function of medical facilities and rehabilitation services worldwide, including toxin services delivering Botulinum toxin treatments for neuromuscular conditions such as spasticity, dystonia, and sialorrhea. The aim of this paper is to understand how toxin services have dealt with the situation and what strategies have been adopted to continue services. The recommendations are based on a virtual round table held with toxin services experts from different European countries who shared their experiences and discussed the best practices. The challenges for toxin services were reviewed based on the experts' experiences and on relevant literature from 2020 and 2021. A set of recommendations and best practices were compiled, focusing firstly on guidance for clinical practice, including assessing patients' health and risk status and the urgency of their treatment. Secondly, it was discussed how patients on botulinum toxin therapy can be cared for and supported during the pandemic, and how modern technology and tele-medicine platforms can be generally used to optimize effectiveness and safety of toxin treatments. The technological advances prompted by the COVID-19 crisis can result in better and more modern patient care in the future.

From 7 November 2020, Greece adopted a second nationwide lockdown policy to mitigate the transmission of SARS-CoV-2 (the first took place from 23 March to 4 May 2020), just as the second wave of COVID-19 was advancing, as did other European countries. To secure the full benefits of mass vaccination, which started in early January 2021, it is of utmost importance to complement it with mid-term non-pharmaceutical interventions (NPIs). The objective was to minimize human losses and to limit social and economic costs. In this paper a two-phase stochastic dynamic network compartmental model (a pre-vaccination SEIR until 15 February 2021 and a post-vaccination SVEIR from 15 February 2021 to 30 June 2021) is developed. Three scenarios are assessed for the first phase: (a) A baseline scenario, which lifts the national lockdown and all NPIs in January 2021; (b) a "semi-lockdown" scenario with school opening, partial retail sector operation, universal mask wearing, and social distancing/teleworking in January 2021; and (c) a "rolling lockdown" scenario combining a partial lifting of measures in January 2021 followed by a third nationwide lockdown in February 2021. In the second phase three scenarios with different vaccination rates are assessed. Publicly available data along with some first results of the SHARE COVID-19 survey conducted in Greece are used as input. The results regarding the first phase indicate that the "semi-lockdown" scenario clearly outperforms the third lockdown scenario (5.7% less expected fatalities); the second phase is extremely sensitive on the availability of sufficient vaccine supplies and high vaccination rates.

Given the limited evidence of school closure effectiveness in containing the pandemic and the consequences for young people, reopening schools with appropriate measures is essential. This overview aimed to describe the main measures planned for the 2020-2021 academic year within the WHO European Region. A rapid systematic review of scientific databases was also performed. The websites of the government, Ministry of Health, and Ministry of Education of European Region countries were searched through 1 October for official documents about the prevention and management of suspected cases/confirmed cases in primary and secondary schools. To find further suggestions, a rapid systematic review was conducted through 20 October searching Pubmed, Scopus, and Embase. There were 23 official documents. France, Luxembourg, Malta, Ireland, Italy, Portugal, the UK, Spain, and San Marino were considered. Performing the rapid review, 855 records were identified and 7 papers were finally selected. The recommendations mostly agreed. However, there was no consensus on the criteria for the return to school of students that tested positive, and the flexibility between attendance at school and remote education for high-risk children often varied. School closure was commonly considered as the very last resort for COVID-19 control. Studies are required to evaluate the impact of different recommendations during this autumn term.

Background: The COVID-19 pandemic has necessitated changes in European healthcare systems, with a significant proportion of COVID-19 cases being managed on an outpatient basis in primary healthcare (PHC). To alleviate the burden on healthcare facilities, many European countries developed contact-tracing apps and symptom checkers to identify potential cases. As the pandemic evolved, the European Union introduced the Digital COVID-19 Certificate for travel, which relies on vaccination, recent recovery, or negative test results. However, the integration between these apps and PHC has not been thoroughly explored in Europe. Objective: To describe if governmental COVID-19 apps allowed COVID-19 patients to connect with PHC through their apps in Europe and to examine how the Digital COVID-19 Certificate was obtained. Methodology: Design and setting: Retrospective descriptive study in PHC in 30 European countries. An ad hoc, semi-structured questionnaire was developed to collect country-specific data on primary healthcare activity during the COVID-19 pandemic and the use of information technology tools to support medical care from 15 March 2020 to 31 August 2021. Key informants belong to the WONCA Europe network (World Organization of Family Doctors). The data were collected from relevant and reliable official sources, such as governmental websites and guidelines. Main outcome measures: Patient's first contact with health system, governmental COVID-19 app (name and function), Digital COVID-19 Certification, COVID-19 app connection with PHC. Results: Primary care was the first point of care for suspected COVID-19 patients in 28 countries, and 24 countries developed apps to complement classical medical care. The most frequently developed app was for tracing COVID-19 cases (24 countries), followed by the Digital COVID-19 Certificate app (17 countries). Bulgaria, Italy, Serbia, North Macedonia, and Romania had interoperability between PHC and COVID-19 apps, and Poland and Romania's apps considered social needs. Conclusions: COVID-19 apps were widely created during the first pandemic year. Contact tracing was the most frequent function found in the registered apps. Connection with PHC was scarcely developed. In future pandemics, connections between health system levels should be guaranteed to develop and implement effective strategies for managing diseases. [ABSTRACT FROM AUTHOR]

The share of the elderly population is growing worldwide as life expectancy increases. Immunosenescence and comorbidities increase infectious diseases' morbidity and mortality in older adults. Here, we aimed to summarize the latest findings on vaccines for the elderly against herpes zoster, influenza, respiratory syncytial virus (RSV), COVID-19, and pneumococcal disease and to examine vaccine recommendation differences for this age group in Europe and the United States. PubMed was searched using the keywords "elders" and "vaccine" alongside the disease/pathogen in question and paraphrased or synonymous terms. Vaccine recommendations were also sought in the European and US Centers for Disease Control and Prevention databases. Improved vaccines, tailored for the elderly, mainly by using novel adjuvants or by increasing antigen concentration, are now available. Significant differences exist between immunization policies, especially between European countries, in terms of the recipient's age, number of doses, vaccination schedule, and implementation (mandatory or recommended). Understanding the factors that influence the immune response to vaccination in the elderly may help to design vaccines that offer long-term protection for this vulnerable age group. A consensus-based strategy in Europe could help to fill the gaps in immunization policy in the elderly, particularly regarding vaccination against RSV and pneumococcus. [ABSTRACT FROM AUTHOR]

The current pandemic is sustained in dichotomies and distancing, as most of us awkwardly have recently experienced. Moreover, COVID-19 has definitely put the spotlight on social inequalities that are underpinning our society and it has highlighted the escalation of the state surveillance capability and new forms of oppression too. The discrimination ingrained in our societies, built on a historically defined regime of racialized oppression and structural disadvantage of racialized citizens and migrants, was produced well before the coronavirus, but it is now casting a different shade, reinforcing forms of exclusions, highlighting the pandemic as a political issue. Hence, this paper addresses a range of political perspectives of the lived experiences in and through social space with examples of narratives in language which capture the everyday political experiences of the pandemic within Europe. The kind of language used and its profound effect on the growing discourse regarding COVID-19 is the main focus in this paper. I here explore the intertwining of language and politics during the pandemic and bring out the countervailing narratives that seem to be in constant tension. I then ask where this takes us, not only in terms of scholarship and expansion of knowledge, but also with a pragmatic edge to it, trying to figure out how is it possible for us to achieve some sort of cognitive shift in our approach in order to learn from this challenge and from this new perspective. Methodologically, as well as looking at existing data, references to attitudes in general are made. A theoretical discussion on migration and language, and the kind of intersection between them, is offered, from the point of view of critical theory, before pointing to the metaphors used, the implications they allow, and how all these fit together, in the form of a concluding discussion. Metaphor or not, the power of language in its ramifications of articulations about the pandemic and the idea of distance underlines COVID-19 as a deeply political issue. [ABSTRACT FROM AUTHOR]

The European Insurance and Occupational Pensions Authority suggests that as the coronavirus disease 2019 (COVID-19) pandemic has caused significant disruption to the economy, businesses, and people's lives, national supervisory authorities should mitigate the pandemic's impact on the European insurance sector. The functioning of insurance companies is in danger as they must balance a drastic increase in the number of claims with their capital and solvency stability. In this study, we evaluate the effects of the COVID-19 pandemic on insurance companies using European insurance companies' financial statement data from 2010 to 2020. The results unambiguously demonstrate that the pandemic has negatively affected the functioning of the insurance sector. In particular, the return on assets decreased in German and Italian insurance companies during the pandemic. Furthermore, the solvency ratio decreased in the Belgian, French, and German insurance sectors. Conversely, the Polish insurance sector was unaffected. Moreover, we did not find any effects on the Z-score ratio in our sample. Lastly, the value of receivables owed to Belgian insurance companies increased. Based on this evidence, we argue that European legislators should discuss how to manage the probable financial problems of insurance companies during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Vaccination plays a pivotal role in the control of infectious disease outbreaks. Hesitancy/refusal of the vaccine by immigrants poses a serious threat to their and society's health. We reviewed studies regarding COVID-19 vaccine uptake in Europe by first-generation immigrants. A systematic review (PROSPERO: CRD42023432142), conducted until 31 October 2023 using Web of Science, PubMed, and Scopus, identified 295 potential articles. Of these, 16 conducted on 2,009,820 immigrants in nine European countries met the eligibility criteria. Most studies were of medium/high quality according to the Newcastle–Ottawa Scale adapted for observational studies. Factors that affected the uptake or hesitancy/refusal to vaccinate, with particular regard to gender, age, and country of origin, were examined. The meta-analysis of eight studies revealed that the pooled estimated prevalence of COVID-19 vaccine uptake in first-generation immigrants was 71.3% (95% CI: 70.0–72.5%), corresponding to 13.3% less than the host country population (95% CI: 10.2–16.4%). Limitations of included studies and this review were deeply discussed, highlighting the need for further research on the effect of acculturation on second-generation immigrants. European governments need to ensure equal availability of COVID-19 and other health-saving vaccines to all immigrants in the future by overcoming cultural barriers, building trust in institutions, and improving communication. [ABSTRACT FROM AUTHOR]

This paper provides a summary of mass COVID-19 testing of almost the entire population in Slovakia by antigen tests. We focused on the results delivered by two testing rounds and analyzed the benefits and weaknesses of such type of testing. We prepared mathematical models to critically examine the effectiveness of the testing, and we also estimated the number of potentially sick people that would become infected by those marked as positives by antigen tests. Our calculations have proven that antigen testing in hotspots can flatten the curve of daily newly reported cases significantly, but in regions with low-risk of COVID-19, the benefit of such testing is questionable. As for the regions with low infection rates, we could only estimate the proportion of true and false-positive cases because the national health authority had not validated the results by RT-PCR tests. Therefore, this work can serve as an introductory study on the first nationwide testing by antigen tests in Europe. [ABSTRACT FROM AUTHOR]

Drug side effects (DSEs) or adverse drug reactions (ADRs) are a major concern in the healthcare industry, accounting for a significant number of annual deaths in Europe alone. Identifying and predicting DSEs early in the drug development process is crucial to mitigate their impact on public health and reduce the time and costs associated with drug development. Objective: In this study, our primary objective is to predict multiple drug side effects using 2D chemical structures, especially for COVID-19, departing from the conventional approach of relying on 1D chemical structures. We aim to develop a novel model for DSE prediction that leverages the CNN-based transfer learning architecture of ResNet152V2. Motivation: The motivation behind this research stems from the need to enhance the efficiency and accuracy of DSE prediction, enabling the pharmaceutical industry to identify potential drug candidates with fewer adverse effects. By utilizing 2D chemical structures and employing data augmentation techniques, we seek to revolutionize the field of drug side-effect prediction. Novelty: This study introduces several novel aspects. The proposed study is the first of its kind to use 2D chemical structures for predicting drug side effects, departing from the conventional 1D approaches. Secondly, we employ data augmentation with both conventional and diffusion-based models (Pix2Pix), a unique strategy in the field. These innovations set the stage for a more advanced and accurate approach to DSE prediction. Results: Our proposed model, named CHEM2SIDE, achieved an impressive average training accuracy of 0.78. Moreover, the average validation and test accuracy, precision, and recall were all at 0.73. When evaluated for COVID-19 drugs, our model exhibited an accuracy of 0.72, a precision of 0.79, a recall of 0.72, and an F1 score of 0.73. Comparative assessments against established transfer learning and machine learning models (VGG16, MobileNetV2, DenseNet121, and KNN) showcased the exceptional performance of CHEM2SIDE, marking a significant advancement in drug side-effect prediction. Conclusions: Our study introduces a groundbreaking approach to predicting drug side effects by using 2D chemical structures and incorporating data augmentation. The CHEM2SIDE model demonstrates remarkable accuracy and outperforms existing models, offering a promising solution to the challenges posed by DSEs in drug development. This research holds great potential for improving drug safety and reducing the associated time and costs. [ABSTRACT FROM AUTHOR]

Universal history is characterized by continuous evolution, in which civilizations are born and die. This evolution is associated with multiple factors, among which the role of microorganisms is often overlooked. Viruses and bacteria have written or decisively contributed to terrible episodes of history, such as the Black Death in 14th century Europe, the annihilation of pre-Columbian American civilizations, and pandemics such as the 1918 Spanish flu or the current COVID-19 pandemic caused by the coronavirus SARS-CoV-2. Nevertheless, it is clear that we could not live in a world without these tiny beings. Endogenous retroviruses have been key to our evolution and for the regulation of gene expression, and the gut microbiota helps us digest compounds that we could not otherwise process. In addition, we have used microorganisms to preserve or prepare food for millennia and more recently to obtain drugs such as antibiotics or to develop recombinant DNA technologies. Due to the enormous importance of microorganisms for our survival, they have significantly influenced the population genetics of different human groups. This paper will review the role of microorganisms as "villains" who have been responsible for tremendous mortality throughout history but also as "friends" who help us survive and evolve. [ABSTRACT FROM AUTHOR]

The recent COVID-19 pandemic affected various aspects of life. Several studies established the consequences of pandemic lockdown on air quality using satellite remote sensing. However, such studies have limitations, including low spatial resolution or incomplete spatial coverage. Therefore, in this paper, we propose a machine learning-based scheme to solve the pre-mentioned limitations by training an optimized space-time extra trees model for each year of the study period. The results have shown that our trained models reach a prediction accuracy up to 95% when predicting the missing values in the MODIS MCD19A2 Aerosol Optical Depth (AOD) product. The outcome of the mentioned scheme was a geo-harmonized atmospheric dataset for aerosol optical depth at 550 nm with 1 km spatial resolution and full coverage over Europe. As an application, we used the proposed machine learning based prediction approach in AOD levels analysis. We compared the mean AOD levels between the lockdown period from March to June in 2020 and the mean AOD values of the same period for the past 5 years. We found that AOD levels dropped over most European countries in 2020 but increased in several eastern and western countries. The Netherlands had the most significant average decrease in AOD levels (19%), while Spain had the highest average increase (10%). Moreover, we analyzed the relationship between the relative percentage difference of AOD and four meteorological variables. We found a positive correlation between AOD and relative humidity and a negative correlation between AOD and wind speed. The value of the proposed prediction scheme is further emphasized by taking into consideration that the reconstructed dataset can be used for future air quality studies concerning Europe. [ABSTRACT FROM AUTHOR]

The aging of human populations, including those in Europe, is an indisputable fact. The challenge for the future is not simply prolonging human life at any cost or by any means but rather extending self-sufficiency and quality of life. Even in the most advanced societies, the eternal questions remain. Who will take care of the older generations? Will adult children's own circumstances be sufficient to support family members as they age? For a range of complex reasons, including socioeconomic conditions, adult children are often unable or unwilling to assume responsibility for the care of older family members. For this reason, it is imperative that aging adults maintain their independence and self-care for as long as possible. Movement is an important part of self-sufficiency. Moreover, movement has been shown to improve patients' clinical status. At a time when the coronavirus pandemic is disrupting the world, older people are among the most vulnerable. Our paper explores current knowledge and offers insights into the significant benefits of movement for the elderly, including improved immunity. We discuss the biochemical processes of aging and the counteractive effects of exercise and endogenous substances, such as vitamin D. [ABSTRACT FROM AUTHOR]

Air pollution has a strong impact on human health, from respiratory and severe pulmonary diseases to heart attack and cancer. During the 3 years of the COVID-19 pandemic, several peaks of mortality occurred, which could be related to particulate matter (PM) pollution events. The possible effects of PM (PM10 and PM2.5, with diameters less than 10 and 2.5 µm, respectively) on COVID-19 mortality have now been established. To better understand this relationship at the European level for the period 2020–2022, data from 16 representative locations in Europe (81 million people) with PM2.5 levels (µg·m−3) ranging from low to high values were analyzed using statistical methods. The analysis confirms a temporal relation between the peaks of PM2.5 exposure and COVID-19 mortality. The best correlation was obtained considering the history of exposure to PM2.5 pollution during a 2-month integration time coupled with a one-week delay for the COVID-19 mortality. Although the trend of COVID-19 mortality vs. PM2.5 levels varies among locations, the global trend was similar, giving an estimated mean value of a 40 ± 20% mortality increase per µg·m−3 PM2.5 increase. The stronger the positive (negative) gradient of the PM peak, the stronger the positive (negative) gradient of the COVID-19 mortality. These results indicate that a succession of PM pollution peaks could be more dangerous than permanent exposure to moderate pollution levels. Finally, PM number concentrations should be used in the future rather than the PM2.5 mass concentrations (µg·m−3), with the consideration of PM composition to better evaluate the effect of submicron particles on human health, particularly for other respiratory diseases. These results must be considered in the management of future pandemics. [ABSTRACT FROM AUTHOR]

In some NUTS 2 (Nomenclature of Territorial Units for Statistics) regions of Europe, the COVID-19 pandemic has triggered an increase in mortality by several dozen percent and only a few percent in others. Based on the data on 189 regions from 19 European countries, we identified factors responsible for these differences, both intra- and internationally. Due to the spatial nature of the virus diffusion and to account for unobservable country-level and sub-national characteristics, we used spatial econometric tools to estimate two types of models, explaining (i) the number of cases per 10,000 inhabitants and (ii) the percentage increase in the number of deaths compared to the 2016–2019 average in individual regions (mostly NUTS 2) in 2020. We used two weight matrices simultaneously, accounting for both types of spatial autocorrelation: linked to geographical proximity and adherence to the same country. For the feature selection, we used Bayesian Model Averaging. The number of reported cases is negatively correlated with the share of risk groups in the population (60+ years old, older people reporting chronic lower respiratory disease, and high blood pressure) and the level of society's belief that the positive health effects of restrictions outweighed the economic losses. Furthermore, it positively correlated with GDP per capita (PPS) and the percentage of people employed in the industry. On the contrary, the mortality (per number of infections) has been limited through high-quality healthcare. Additionally, we noticed that the later the pandemic first hit a region, the lower the death toll there was, even controlling for the number of infections. [ABSTRACT FROM AUTHOR]

Substantial reductions in human and economic activities such as road traffic for several months in 2020 were one of the consequences of the Coronavirus pandemic. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown across 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5), as well as on land surface temperature (LST) and the surface urban heat island intensity (SUHII) using satellite, modeled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change in the variables under study. In general, the results indicate a substantial decrease in NO2 concentrations in most of the studied cities compared with the reference period of 2015–2019. However, reductions could not be attributed to mobility changes such as less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown in accordance with the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar to the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is having a strong influence in all areas of society, like wealth, economy, travel, lifestyle habits, and, amongst many others, financial and energy markets. The influence in standard energies, like crude oil, and renewable energies markets has been twofold: from one side, the predictability of volatility has strongly decreased; secondly, the linkages of the price time series have been modified. In this paper, by using DCC-GARCH and Price Leadership Share methodology, we can investigate the changes in the influences between standard energies and renewable energies markets by analyzing one-minute time series of West Texas Intermediate crude oil futures contract (WTI), the Brent crude oil futures contract (BRENT), the STOXX Europe 600 oil & gas index (SXEV), and the European renewable energy index (ERIX). Our results confirm volatility spillover between the time series. However, when assessing the accuracy of the predictability of the DCC-GARCH model, the results show that the model fails its prediction in the period of higher instability. Besides, we found that price leadership has been strongly influenced by the virus spreading stages. These results have been obtained by dividing the period between September 2019 and January 2021 into 6 subperiods according to the pandemic stages. [ABSTRACT FROM AUTHOR]

In light of the advancing energy transition and an increasing amount of intermittent renewable energy to be integrated, flexibility from distributed energy resources will be key. In this paper, the Italian UVAM (Unità Virtuali Abilitate Miste, i.e., virtually aggregated mixed units) project, one of the biggest pilots in Europe to serve this purpose, is critically reviewed and mapped after two years of operation. The pilot is analyzed on a global level as well as the individual participant level. Based on the extensive analysis of actual market data, different strategies of participating companies to obtain capacity in accordance with the pilot project's design are identified. Furthermore, the specific bidding strategies of individual participating units on the balancing market are outlined. Alongside this, the overall pilot project's market integration, in terms of offered and accepted bids, is depicted. The thorough data analysis, therefore, serves as an input and fundamental building block for future electricity market modeling. Comprehending specific data from the coronavirus disease 2019 (COVID-19) pandemic, provides insights for future high renewable-energy scenarios. Based on the analysis findings, valuable deliverables are devised for both policy-makers and decision-makers who aim to leverage the flexibility potential of distributed resources. [ABSTRACT FROM AUTHOR]

Background: A rising number of monkeypox cases have been detected in Europe and several Western nations. Evaluating the fear associated with monkeypox is crucial to determine the necessity for tailored education and prevention programs for specific populations. This study explores the psychological and social factors linked to the fear response to monkeypox. Methods: Nine self-report measures were completed by 333 participants (212 women, 110 men, and 11 individuals identifying as other genders) from the general Italian population, investigating different psychosocial variables. Results: The findings revealed that higher levels of monkeypox fear were linked to identifying as LGB+ or having close associations with the LGBTQI+ community, being single, having lower education levels, placing greater importance on religion, receiving more COVID-19 vaccine doses, having a lower current quality of life, and attributing increased impairment to the COVID-19 pandemic. Psychologically, higher levels of monkeypox fear were associated with higher levels of epistemic credulity, close-mindedness, anxiety, difficulty expressing emotions, and difficulty processing them. Conversely, lower levels of monkeypox fear were related to the belief that the media exaggerated the risks associated with monkeypox epidemics. A partial mediation model was presented and tested. Conclusions: Collecting and utilizing this data can help design targeted education and prevention programs to overcome the fear of monkeypox and promote healthier behaviors. [ABSTRACT FROM AUTHOR]

To manage mass vaccination without impacting medical resources dedicated to care, we proposed a new model of Mass Vaccination Centers (MVC) functioning with minimum attending staffing requirements. The MVC was under the supervision of one medical coordinator, one nurse coordinator, and one operational coordinator. Students provided much of the other clinical support. Healthcare students were involved in medical and pharmaceutical tasks, while non-health students performed administrative and logistical tasks. We conducted a descriptive cross-sectional study to describe data concerning the vaccinated population within the MVC and the number and type of vaccines used. A patient satisfaction questionnaire was collected to determine patient perception of the vaccination experience. From 28 March to 20 October 2021, 501,714 vaccines were administered at the MVC. A mean rate of 2951 ± 1804 doses were injected per day with a staff of 180 ± 95 persons working every day. At peak, 10,095 injections were given in one day. The average time spent in the MVC was 43.2 ± 15 min (time measured between entry and exit of the structure). The average time to be vaccinated was 26 ± 13 min. In total, 4712 patients (1%) responded to the satisfaction survey. The overall satisfaction with the organization of the vaccination was 10 (9–10) out of 10. By using one attending physician and one nurse to supervise a staff of trained students, the MVC of Toulouse optimized staffing to be among the most efficient vaccination centers in Europe. [ABSTRACT FROM AUTHOR]

Background: While passive immunotherapy has been considered beneficial for patients with severe respiratory viral infections, the treatment of COVID-19 cases with convalescent plasma produced mixed results. Thus, there is a lack of certainty and consensus regarding its effectiveness. This meta-analysis aims to assess the role of convalescent plasma treatment on the clinical outcomes of COVID-19 patients enrolled in randomized controlled trials (RCTs). Methods: A systematic search was conducted in the PubMed database (end-of-search: 29 December 2022) for RCTs on convalescent plasma therapy compared to supportive care\standard of care. Pooled relative risk (RR) and 95% confidence intervals were calculated with random-effects models. Subgroup and meta-regression analyses were also performed, in order to address heterogeneity and examine any potential association between the factors that varied, and the outcomes reported. The present meta-analysis was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: A total of 34 studies were included in the meta-analysis. Per overall analysis, convalescent plasma treatment was not associated with lower 28-day mortality [RR = 0.98, 95% CI (0.91, 1.06)] or improved 28-day secondary outcomes, such as hospital discharge [RR = 1.00, 95% CI (0.97, 1.03)], ICU-related or score-related outcomes, with effect estimates of RR = 1.00, 95% CI (0.98, 1.05) and RR = 1.06, 95% CI (0.95, 1.17), respectively. However, COVID-19 outpatients treated with convalescent plasma had a 26% less risk of requiring hospital care, when compared to those treated with the standard of care [RR = 0.74, 95% CI (0.56, 0.99)]. Regarding subgroup analyses, COVID-19 patients treated with convalescent plasma had an 8% lower risk of ICU-related disease progression when compared to those treated with the standard of care (with or without placebo or standard plasma infusions) [RR = 0.92, 95% CI (0.85, 0.99)] based on reported outcomes from RCTs carried out in Europe. Finally, convalescent plasma treatment was not associated with improved survival or clinical outcomes in the 14-day subgroup analyses. Conclusions: Outpatients with COVID-19 treated with convalescent plasma had a statistically significantly lower risk of requiring hospital care when compared to those treated with placebo or the standard of care. However, convalescent plasma treatment was not statistically associated with prolonged survival or improved clinical outcomes when compared to placebo or the standard of care, per overall analysis in hospitalized populations. This hints at potential benefits, when used early, to prevent progression to severe disease. Finally, convalescent plasma was significantly associated with better ICU-related outcomes in trials carried out in Europe. Well-designed prospective studies could clarify its potential benefit for specific subpopulations in the post-pandemic era. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic led to many European countries imposing lockdown measures and limiting people's movement during spring 2020. During the summer 2020, these strict lockdown measures were gradually lifted while in autumn 2020, local restrictions started to be re-introduced as a second wave emerged. After initial restrictions on visitors accessing many Nature Protected Areas (PAs) in Europe, management authorities have had to introduce measures so that all users can safely visit these protected landscapes. In this paper, we examine the challenges that emerged due to COVID-19 for PAs and their deeper causes. By considering the impact on and response of 14 popular European National and Nature Parks, we propose tentative longer-term solutions going beyond the current short-term measures that have been implemented. The most important challenges identified in our study were overcrowding, a new profile of visitors, problematic behavior, and conflicts between different user groups. A number of new measures have been introduced to tackle these challenges including information campaigns, traffic management, and establishing one-way systems on trail paths. However, measures to safeguard public health are often in conflict with other PA management measures aiming to minimize disturbance of wildlife and ecosystems. We highlight three areas in which management of PAs can learn from the experience of this pandemic: managing visitor numbers in order to avoid overcrowding through careful spatial planning, introducing educational campaigns, particularly targeting a new profile of visitors, and promoting sustainable tourism models, which do not rely on large visitor numbers. [ABSTRACT FROM AUTHOR]

The burden of COVID-19 remains unchanged for immunocompromised patients who do not respond to vaccines. Unfortunately, Omicron sublineages are resistant to monoclonal antibodies authorized in Europe so far, and small chemical antivirals have contraindications and toxicities that have not been studied in these patients. We report here the successful treatment of COVID-19 pneumonia lasting for 4 months after the transfusion of COVID-19 convalescent plasma (CCP) in a patient with severe immunosuppression due to both chronic lymphocytic leukemia and venetoclax treatment. The patient achieved a complete clinical, radiological and virological response after six transfusions (600 mL each) of high-titer CCP collected from triple-vaccinated and convalescent donors. This dramatic case adds to the mounting evidence of CCP efficacy in immunocompromised patients, provided that high-titer and large volumes are infused. [ABSTRACT FROM AUTHOR]

The aim of this study is to understand the effect of the recent novel coronavirus pandemic on investor herding behavior in global stock markets. Utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, we examine the association between pandemic-induced market uncertainty and herding behavior in a set of 49 global stock markets. More specifically, we study the pattern of cross-sectional market behavior and examine whether the pandemic-induced uncertainty drives directional similarity across the global stock markets that cannot be explained by the standard asset pricing models. Utilizing a time-varying variation of the static herding model, we first identify periods during which herding is detected. We then employ probit models to examine the possible association between pandemic-induced uncertainty and the formation of herding. Our findings show a strong association between herd formation in stock markets and COVID-19 induced market uncertainty. The herding effect of COVID-19 induced market uncertainty is particularly strong for emerging stock markets as well as European PIIGS stock markets that include some of the hardest hit economies in Europe by the pandemic. The findings establish a direct link between the recent pandemic and herd formation among market participants in global financial markets. Considering the evidence that herding behavior can drive security prices away from equilibrium values supported by fundamentals and further contribute to price fluctuations in financial markets, our findings have significant implications for policy makers and investors in their efforts to monitor investor sentiment and mitigate mis-valuations that might occur as a result. Furthermore, the evidence on the behavioral pattern of stock investors in relation to infectious diseases uncertainty can be useful in studying price discovery in stock markets and might help market participants in forming hedging strategies to mitigate downside risk in their investment portfolios. [ABSTRACT FROM AUTHOR]

The impact of the SARS-CoV-2 (COVID-19) on the world has been partially controlled through different measures of social isolation and prophylaxis. Two new SEIR (Susceptible-Exposed-Infected-Recovered) models are proposed in order to describe this spread through different countries of Europe. In both models the infectivity of the asymptomatic period during the exposed stage of the disease will be taken into account. The different transmission rates of the SEIR models are calculated by considering the different locations and, more importantly, the lockdown measures implemented in each region. A new classification of these intervention measures will be set and their influence on the values of the transmission rates will be estimated through regression analysis. [ABSTRACT FROM AUTHOR]

While many articles have analyzed the effectiveness of the policies that aimed to limit the spread of COVID-19, very little research work has examined the determinants that drove these policies. Therefore, we proposed to study the determinants that led government authorities to implement more or less restrictive policies to limit the spread of the pandemic. Using the COVID-19 stringency index, we highlighted a positive effect of the incidence rate on the stringency level. Patient capacity in intensive care units was also a key variable. This is indicative of the capacity of countries to have a sufficient and appropriate health system to absorb such pandemic crises. On the other hand, we show that epidemiological data regarding the risk of excess mortality (diabetes, cancer, and cardiovascular pathologies) had a negative effect. We conclude by recalling the importance of policy coordination between countries when it comes to lowering the stringency levels of measures, in order to avoid a resurgence of the epidemic. [ABSTRACT FROM AUTHOR]

In the process of vaccination against COVID-19, the problem of parents who do not want to vaccinate their school-age children has been evident. A conflict arises between two fundamental rights: the right to ideological freedom, privacy, and physical integrity of parents and minors who do not opt for vaccination; and the right to health of the rest of the children who attend the same school, provoking a social debate on the need to introduce regulatory changes that favor the mandatory imposition of vaccination in certain cases. This research offers an observational study through a cross-sectional design of a quantitative nature, in which one thousand people belonging to the education, health, and economy sectors from seventy-six countries of five continents have participated. The instrument used was a previously validated questionnaire: VACUNASEDUCA. It was considered essential to know the awareness of vaccination processes of professionals from essential social sectors. Therefore, the objectives were: to reflect on the measures of mandatory vaccination, to know the importance of teachers being able to demand a regulated vaccination card from students, to study the need for regulation by administrations of compliance with vaccines, and to analyze the importance of health education. It has been shown that women and those under thirty years of age are the least in favor of compulsory vaccination, with the health sector being the most defending of their demand, and with Europe with the lowest means. It is concluded that mandatory vaccination could be an acceptable tactical option to prevent high-risk situations. [ABSTRACT FROM AUTHOR]

The main research question concerned the identification of changes in the COVID-19 epidemiological situation using fuzzy clustering methods. This research used cross-sectional time series data obtained from the European Centre for Disease Prevention and Control. The identification of country types in terms of epidemiological risk was carried out using the fuzzy c-means clustering method. We also used the entropy index to measure the degree of fuzziness in the classification and evaluate the uncertainty of epidemiological states. The proposed approach allowed us to identify countries' epidemic states. Moreover, it also made it possible to determine the time of transition from one state to another, as well as to observe fluctuations during changes of state. Three COVID-19 epidemic states were identified in Europe, i.e., stabilisation, destabilisation, and expansion. The methodology is universal and can also be useful for other countries, as well as the research results being important for governments, politicians and other policy-makers working to mitigate the effects of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

At the moment of writing this communication, the health crisis derived from the COVID-19 pandemic has affected more than 120 million cases, with 40 million corresponding to Europe. In total, the number of deaths is almost 3 million, but continuously rising. Although COVID-19 is primarily a respiratory disease, SARS-CoV-2 infects also endothelial cells in the pulmonary capillaries. This affects the integrity of the endothelium and increases vascular permeability. In addition, there are serious indirect consequences, like disruption of endothelial cells' junctions leading to micro-bleeds and uncontrolled blood clotting. The impact of COVID-19 in people with rare chronic cardiovascular diseases is unknown so far, and interesting to assess, because the virus may cause additional complications in these patients. The aim of the present work was to study the COVID-19 infection among the patients with Hereditary Hemorrhagic Telangiectasia (HHT). A retrospective study was carried out in a 138 HHT patients' sample attending an Ear Nose and Throat (ENT) reference consult. The evaluation of the COVID-19 infection in them reveals milder symptoms; among the 25 HHT patients who were infected, only 3 cases were hospitalized, and none of them required ICU or ventilation assistance. The results are discussed in the light of macrophage immune response. [ABSTRACT FROM AUTHOR]

The agricultural use of good quality sludge represents a value-added route to ensure growth sustainability in Europe, where raw material availability, for example, for phosphorus, is insufficient to meet demand. However, the possible presence of pathogens, pharmaceuticals and heavy metals requires specific regulations to minimize sludge-related health issues and environmental risks. The current regulation on sludge agricultural use applied by many EU countries is here presented and compared, highlighting scarce harmonization of the legislative framework among Member States. Actual issues, such as the fate of emerging micropollutants and microplastics in sludge-amended soils, and public health concerns regarding sludge spreading during the COVID-19 epidemic, are considered, too. [ABSTRACT FROM AUTHOR]

Cities generate about 85% of the EU's GDP. As such, they are key players in shaping and providing technological and social innovations but also environmental impact. Thus, they must urgently engage in unprecedented systemic transformational and bold transitions towards sustainability and climate neutrality. The contribution—taking into account that the concepts of community resilience and urban transition have changed as a consequence of COVID-19—critically discusses innovative frameworks and funding opportunities that Horizon Europe will put in place to boost sustainable urban areas in Europe, driving a transition to 100 Positive Energy Districts and 100 climate-neutral cities by 2030. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) pandemic has disrupted modern societies and their economies. The resurgence in COVID-19 cases as part of the second wave is observed across Europe and the Americas. The scientific response has enabled a complete structural characterization of the Severe Acute Respiratory Syndrome—novel Coronavirus 2 (SARS-CoV-2). Among the most relevant proteins required by the novel coronavirus to facilitate the cell entry mechanism is the spike protein. This protein possesses a receptor-binding domain (RBD) that binds the cellular angiotensin-converting enzyme 2 (ACE2) and then triggers the fusion of viral and host cell membranes. In this regard, a comprehensive characterization of the structural stability of the spike protein is a crucial step to find new therapeutics to interrupt the process of recognition. On the other hand, it has been suggested that the participation of more than one RBD is a possible mechanism to enhance cell entry. Here, we discuss the protein structural stability based on the computational determination of the dynamic contact map and the energetic difference of the spike protein conformations via the mapping of the hydration free energy by the Poisson–Boltzmann method. We expect our result to foster the discussion of the number of RBD involved during recognition and the repurposing of new drugs to disable the recognition by discovering new hotspots for drug targets apart from the flexible loop in the RBD that binds the ACE2. [ABSTRACT FROM AUTHOR]