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The COVID-19 pandemic has brought increased attention to the existing gender asymmetries in academia, which have been extensively studied in the literature. Using the analytical lens of "gendered academic citizenship", this paper takes a micropolitical perspective to examine how the pandemic has impacted the dynamics of academic work, specifically focusing on the often-overlooked aspect of everyday interactions in the work environment. Through qualitative and quantitative analysis of survey data collected from 1750 lecturers and researchers in Portuguese higher education and research institutions, the study uncovers that women, especially those who are younger, single, have specific caregiving responsibilities, and are in the early stages of their careers, were more vulnerable to experiencing "everyday" microaggressions such as silencing, exclusion, belittlement, being ignored, lack of validation, and invisibility compared to men during the pandemic. These findings suggest that, while the marginalization of women in academia is a longstanding issue, the virtual work model has created a platform for the expression of subtle forms of disempowerment and discrimination against women. These dynamics are perpetuated within the micropolitics of organizations, shaping subjective feelings of belonging and circulating differential levels of recognition within academic institutions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic had an enormous impact on the tourism sector. Economies with a large weight of external tourism were especially affected, as was the case with the Azores region. This paper aims to analyse the level of this crisis and the resilience of tourism recreation companies specializing in canyoning in the Azores region, and whether these reactions led to more sustainable business models. The adopted methodology considered the analysis of recent statistical data on tourism and the available information on COVID-19 pandemic-related impacts. In parallel, questionnaires were applied to all tourism recreation companies in Portugal, and semi-structured interviews were conducted with all the canyoning providers in the Azores region. Results show that all companies survived the crisis, and some have made significant changes to their business models. Furthermore, some degree of success was observed in how services adapted to new demand characteristics, given the small size of most of these businesses and the specialization of their products. [ABSTRACT FROM AUTHOR]

The heavy economic, social, and psychological toll of pandemic lockdowns around the world and their disproportionate effect on women are widely acknowledged, but different socioeconomic backgrounds and contexts may influence the degree to which stay-at-home measures impact their lives. Additionally, knowing that violence against women tends to increase during times of crisis, we are testing if the additional burden of victimization represents an added load to the perceived social impacts of the lockdown. Using 2021 survey data from a random sample of 1541 Portuguese women, the paper explores, through logistic regression models, the social impact of the lockdown on the lives of women, its socioeconomic determinants, and the role played by violence against women during the pandemic. The results show that the COVID-19 pandemic lockdown did not equally affect all facets of women's social lives, and women with higher education status and that experienced income reductions due to the measures taken to control the pandemic are more prone to experience a more severe negative impact of the lockdown on the various facets of their lives. Additionally, having been a victim during the pandemic partially mediates the effect of education and income reduction on the social outcomes of the lockdown. [ABSTRACT FROM AUTHOR]

The use of artificial neural networks (ANNs) is a great contribution to medical studies since the application of forecasting concepts allows for the analysis of future diseases propagation. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures and massive vaccination campaigns. There were two proposed methodologies in making predictions 28 days ahead for the number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy, the United Kingdom, and Germany. A case study of the results of massive immunization in Israel was also considered. The data input of cases, deaths, and daily ICU patients was normalized to reduce discrepant numbers due to the countries’ size and the cumulative vaccination values by the percentage of population immunized (with at least one dose of the vaccine). As a comparative criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best methodology, targeting other possibilities of use for the method proposed. The best architecture achieved a general MAE for the 1-to-28-day ahead forecast, which is lower than 30 cases, 0.6 deaths, and 2.5 ICU patients per million people. [ABSTRACT FROM AUTHOR]

In this paper, we present an age-structured SEIR model that uses contact patterns to reflect the physical distance measures implemented in Portugal to control the COVID-19 pandemic. By using these matrices and proper estimates for the parameters in the model, we were able to ascertain the impact of mitigation strategies employed in the past. Results show that the March 2020 lockdown had an impact on disease transmission, bringing the effective reproduction number ( R (t) ) below 1. We estimate that there was an increase in the transmission after the initial lift of the measures on 6 May 2020 that resulted in a second wave that was curbed by the October and November measures. December 2020 saw an increase in the transmission reaching an R (t) = 1.45 in early January 2021. Simulations indicate that the lockdown imposed on the 15 January 2021 might reduce the intensive care unit (ICU) demand to below 200 cases in early April if it lasts at least 2 months. As it stands, the model was capable of projecting the number of individuals in each infection phase for each age group and moment in time. [ABSTRACT FROM AUTHOR]