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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]

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. [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]

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]

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]

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]

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]

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]

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]

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]

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: 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]

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]

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]

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]

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]