Can COVID-19 outbreak be anticipated by community pharmacy sales? A retrospective analysis

Background: In large-scale community transmission, such as severe acute respiratory syndrome of the COVID-19, monitoring geographic trends and estimating the transmission intensity is critical to support decisions on actions to be taken. Though major efforts are concentrated on testing the populations, the availability and timing of this data pose a clear limitation to realtime monitoring. Purpose(s): This study proposes a retrospective analysis to develop a novel methodology to detect and monitor the COVID-19 epidemiological activity using a selected subset of over-the-counter (OTC) products sold in community pharmacies in Portugal. Previous studies have successfully demonstrated this approach to different epidemiological outbreaks as individuals tend to self-manage the symptoms. Method(s): The subset of OTC products was selected considering therapeutic indication for symptoms of infection by SARS-CoV-2 and the trends observed for diagnosed cases in Portugal. The similarities between the trends of the subset of products and the daily new-suspected and new-confirmed cases of COVID-19, respectively, were assessed using lagged spearman correlation analysis. The trend of the subset of products selected presented high and statistically significant correlations to new-suspected and new-confirmed cases lagging 14-16 days (correl.>0.82;p<0.001). Highest correlation to both new-suspected and new-confirmed cases was found lagging 15 days (0.879 and 0.888, respectively;p<0.001). Conclusion(s): The study supports the use of the methodology presented to anticipate the trends of COVID-19 outbreaks in Portugal, both locally and nationwide, considering representativity of the presence of community pharmacies to the distribution of populations.

Sars-Cov- 2 Pandemic Impact in Rectal Cancer Patients in the South of Portugal (Algarve)

Aim: Since the early phases of the COVID-19 pandemic, health systems tried to adapt to ensure the continuity of care of oncological patients. This study aimed to describe the impact of SARS-CoV- 2 on rectal cancer screening and staging. Method(s): A two-year (March 2019 to March 2021) retrospective study concerning rectal cancer patients from a referral center was conducted. Patients clinical data from pre-COVID (March 2019 -February 2020) and COVID time (March 2020 -March 2021) was compared. Descriptive and inferential analysis was performed (Chi-Square test). Result(s): One hundred and sixty-five patients were discussed at the multidisciplinary meetings during the 2-year study period (mean age 69 years [+/- 11.1];M: 64%;F:36%). Upon comparative analysis both pre-COVID and COVID patients were found to have similar demographic characteristics, however during the pandemic a higher proportion of patients presented with low rectal cancers (36% vs. 42%;P = 0.1). Moreover, during the COVID period, fewer patients (minus 26%;npre-covid= 95 vs. ncovid = 70) were referred to the hospital, and a larger number of patients presented in Stage IV of the disease (17,9% (n = 17) in pre COVID period vs. 28,6% (n = 20) in COVID period (P = 0.07)). Lastly, the authors run a comparative sub-analysis between the above results and data from the 3 years prior to the pandemic (2017-2019) and still came across with lesser rectal cancer referrals during the pandemic year. Conclusion(s): Our data clearly shows that, during the COVID period, fewer patients received in-hospital care and a higher number were referred in Stage IV. This represents a red flag for the community and should alert the government to implement public health policies to reestablish colorectal cancer standard of care.

A RANDOMIZED CLINICAL TRIAL of 2-WEEK METHOTREXATE DISCONTINUATION in RHEUMATOID ARTHRITIS PATIENTS VACCINATED with INACTIVATED SARS-COV-2 VACCINE

Background: Patients with rheumatoid arthritis (RA) on methotrexate have reduced vaccine responses. Temporary discontinuation has improved immuno-genicity of anti-infuenza vaccine, but this strategy has not been evaluated in anti-SARS-CoV-2 vaccines. Objectives: To evaluate the effect on immunogenicity and safety of 2-week methotrexate (MTX) discontinuation after each dose of the Sinovac-CoronaVac vaccine versus MTX maintenance in rheumatoid arthritis (RA) patients. Methods: This was a single-center, prospective, randomized, investigator-blinded, intervention study (#NCT04754698, CoronavRheum), including adult RA patients (stable CDAI≤10, prednisone ≤7.5mg/day), randomized (1:1) to withdraw MTX (MTX-hold) for 2 weeks after each vaccine dose or maintain MTX (MTX-maintain), evaluated at D0, D28 and D69. Co-primary outcomes were anti-SARS-CoV-2 S1/S2 IgG seroconversion(SC) and neutralizing antibody (NAb) positivity at D69. Secondary outcomes were geometric mean titers (GMT) and fare rates. For immunogenicity analyses, we excluded patients with baseline positive IgG/NAb, and, for safety reasons, those who fared at D28 (CDAI>10) and did not withdraw MTX twice. Results: Randomization included 138 patients with 9 exclusions (5 COVID-19, 4 protocol violations). Safety evaluation included 60 (MTX-hold) and 69 (MTX-maintain) patients. Further exclusions: 27 patients [13 (21.7%) vs. 14 (20.3%), p=0.848] with positive baseline IgG/NAb and 10 patients (21.3%) in MTX-hold with CDAI>10 at D28. At D69, MTX-hold (n=37) had a higher rate of seroconversion than MTX-maintain (n=55) group [29 (78.4%) vs 30 (54.5%), p=0.019], with parallel augmentation in GMT [34.2 (25.2-46.4) vs 16.8 (11.9-23.6), p=0.006]. No differences were observed for NAb positivity [23 (62.2%) vs 27 (49.1%), p=0.217]. At D28 fare, rates were comparable in both groups (CDAI, p=0.122;DAS28-CRP, p=0.576), whereas CDAI>10 was more frequent in MTX-hold at D69 (p=0.024). Conclusion: We provide novel data that 2-week MTX withdrawal after each Sinovac-CoronaVac vaccine dose improves anti-SARS-CoV-2 IgG response. The increased fare rates after second MTX withdrawal may be attributed to the short-term interval between vaccine doses. This strategy requires close surveillance and shared decision making due to the possibility of fares.

Estimation of Reproduction Number for Covid-19 with Statistical Correction of Notifications Delay

The pandemic of Covid-19 began in Brazil in February 2020. To evaluate the evolution of pandemics some metrics can be estimated, such as the reproduction number, Rt, and the basic reproduction number, R0. Due to the delay in the notifications, these estimates may present a bias. Taking the reported data, besides a sample of individuals who reported the day of symptoms onset, it is possible to estimate delay probabilities and to perform a deconvolution to correct the notifications' delay. In this work, it was performed a corrected estimate of Rt. This estimate is done based on the curve of notifications corrected through deconvolution. The approach is applied in three country cities and in the capital of Minas Gerais state. The behavior of Rt concerning the Minas Consciente program was evaluated. It was observed that the corrected Rt was more suitable to measure the effect of the program when compared to the raw Rt. When it was determined a more rigid mobility and activities regime by the program, it was observed a decrease in the median of the variation of the Rt of the cities studied. © 2003-2012 IEEE.

Analyzing the Impact of Resampling Approaches on Chest X-Ray Images for COVID-19 Identification in a Local Hierarchical Classification Scenario

Researchers dealing with real-world data - such as in the healthcare domain - tend to face class imbalance issues. More specifically, publicly available datasets containing Chest X-Ray (CXR) of Pneumonia diseases (including COVID-19) usually have an imbalanced class distribution. This dataset imbalance causes automatic diagnosis systems to classify majority classes with much more accuracy than the minority ones. Several resampling algorithms were proposed in the past to deal with the class imbalance issue. Hierarchical classifiers have also been proposed to increase the predictive performance of classifiers, but there is little research in the literature verifying if using existing resampling algorithms with hierarchical classifiers are a good alternative to improve classification performance. This work proposes an experimental classification schema to investigate the effectiveness of using resampling algorithms in the identification of COVID-19 and other types of Pneumonia through CXR images. The proposed schema uses resampling algorithms to rebalance the class distribution, in a Local Hierarchical Classification scenario. The experimental evaluation, which is supported by inferential statistical analysis, showed that using specific resampling algorithms with Local Hierarchical Classifiers brings a statistically significant increase to the macro-averaged F1-Score, and improves the predictive performance for the minority classes.

Prediction of Bloodstream Infection Events and Infections of the Lower Respiratory Tract in ICU Patients: Expected and Unexpected Infections

Background. Bloodstream infection (BSI) - Central and Non-Central Line Associated - and infections of the lower respiratory tract (RESP) - pneumonia and non pneumonia lower respiratory infections - are some of the main causes of unexpected death in Intensive Care Units (ICUs). Although the leading causes of these infections are already known, risk prediction models can be used to identify unexpected cases. This study aims to investigate whether or not it is possible to build multivariate models to predict BSI and RESP events. Methods. Univariate and multivariate analysis using multiple logistic regression models were built to predict BSI and RESP events. ROC curve analysis was used to validate each model. Independent variables: 29 quantitative parameters and 131 categorical variables. BSI and RESP were identified using Brazilian Health Regulatory Agency protocols with data collected between January and November 2020 from a medical-surgical ICU in a Brazilian Hospital. Definitions: if an infection is 5% or less likely to occur according to the model used and it eventually occurs, it will be classified as "unexpected", or else, if an infection is 10% or less likely to occur, it will be classified as "probably unexpected". Otherwise, infections will be classified as "expected". Patients with a 30% or more risk for BSI or RESP will be classified as "high risk". Results. A total of 1,171 patients were accessed: 70 patients with BSI (95% confidence interval [CI], 3.1%-5%), 66 patients with RESP (95% CI, 2.9%-4.7%), 235 deaths (95% CI, 11.8%-14.9%). Of the 160 potential risk factors evaluated, logistic models for BSI and RESP identified respectively five and seven predictors (Tables 1 and 2, and Figure 1). Patients admitted to the ICU with Covid-19 had a three fold BSI risk and five times more RESP risk than patients without this diagnosis. Conclusion. The built models make possible the identification of the expected infections and the unexpected ones. Three main course of actions can be taken using these models and associated data: (1) Before the occurrence of BSI and RESP: to place high risk patients under more rigorous infection surveillance. (2) After the occurrence of BSI or RESP: to investigate "unexpected" infections. (3) At discharge: to identify high risk patients with no infections for further studies.

Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil

Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.

Teacher’ formation in the pandemic context: reconfigurations of teaching act by undergraduate students in supervised traineeship in emergency remote education

In this paper, we discuss teachers’ formation actions, more specifically the Supervised Traineeship, in the context of emergency remote education resulting from the new coronavirus pandemic (SARS-CoV-2). Our purpose is to understand how students-trainees (re)configure their teaching practices in the Supervised Traineeship in the modality of emergency remote teaching, both in the observation and conducting phases. To do so, we obtained five training reports from undergraduate students in English Language, analyzed using a qualitative-interpretative approach. As a theoretical foundation, we place ourselves, more broadly, in the field of Applied Linguistics and, specifically, in reflections on teaching work and its constituent elements, from the perspective of Sociodiscursive Interactionism. The results point to obstacles in the interaction among university teacher educator, teacher tutors, trainees and students of basic education, both due to the lack of technological resources and the difficulties of teachers and trainees to build ways and make available artifacts that can constitute learning instruments. This scenario, therefore, highlights the complexity and difficulties of emergency remote education in the process of formation and teaching performance of students in the context of the Supervised Traineeship. © 2021. All Rights Reserved.

Professional football in Portugal: preparing to resume after the COVID-19 pandemic. (Special Issue: COVID-19 and the soccer world: early impressions and initial responses.)

This article offers a theoretical reflection on how the First Portuguese Football League is preparing to return to competition, after the suspension and mandatory confinement, as well as the security measures adopted in response to the pandemic caused by the new coronavirus. Despite the paper is descriptive and theoretical, our discussion draws particularly on documentary analysis of mass media/journalist reports, official almanacs, and academic works. A first purpose of this paper, therefore, is to address the way in which professional football is financially exposed and vulnerable to the main sponsors, who seek to exert power and influence. Second, we seek to explore the increasing asymmetrical power relations of the broadcaster's rights that are increasingly using strategies for wielding power than act a business partner. The implications arising from the study are considered for sport-governing bodies and clubs, in addition to future research directions.

An Evaluation of Segmentation Techniques for Covid-19 Identification in Chest X-Ray

COVID-19 is a highly contagious disease caused by the SARS-CoV-2 virus. Due to its high impact on society, several efforts have been made to design practical ways to support COVID-19 diagnosis. In this context, automated solutions based on chest x-rays (CXR) images and deep learning are among the popular ones. Although these techniques achieved exciting results in the literature, the use of regions that do not support pneumonia diagnosis, i.e., regions outside the lung area, may bias the recognition model. A strategy to avoid this issue is to use segmentation techniques to isolate the lung area before the classification process. In this work, we investigate the impact of three CNN segmentation architectures on COVID-19 identification: U-Net, MultiResUnet, and BCDU-NET. We also investigate which portions of the CXR most influence each model’s predictions, using Explainable Artificial Intelligence. The BCDU-NET architecture achieved a Jaccard Index of 0.91 and a Dice Coefficient of 0.95. In the best scenario, lung segmentation improved the COVID-19 identification F1-Score by about 6.6%. © 2021, Springer Nature Switzerland AG.

Towards integrating quality in theoretical models of acceptance: An extended proposed model applied to e-learning services

The use of e-learning services is growing in different contexts, especially in the COVID-19 pandemic. This study aims to examine students’ acceptance of and intention to use Learning Management Systems (LMSs) for university education in Brazil using the extended technology acceptance model, unified theory of acceptance and use of technology (UTAUT), integrating quality construct adapted from the Service Quality Evaluation Model (ServQual). Examining a large sample (n = 1237) of students in Brazil through questionnaires, we investigate the behaviour of the users concerning the factors that influence the technology acceptance and the intention of the use in an e-learning system. Results show that intention to use an LMS is affected by the facilitating conditions (skilful, workable and easy to use), social influence (remarkable, preference for use and relevance), habit (routine, enjoyable and entertaining) and quality (reliable, tangibility, responsiveness and assurance), but not for effort expectancy (agility, knowledge and productivity). Our research findings suggest fostering replicate the model in different universities and countries understanding potential differences. Practitioner notes What is already known about this topic E-learning is growing, and its success is directly related to students’ intention and retention of users. Unified theory of acceptance and use of technology (UTAUT) is an approved model that explains new system adoption and use. There are several tools to evaluate the quality of e-learning. ServQual is an approved model that explains the perceived quality service. What this paper adds The results of this research proved that facility conditions, social influence, habit and quality were the key and fundamental characteristics of Learning Management Systems. This paper provides advice for decision makers in universities who want to integrate quality in Learning Management Systems. A new validated model extending the UTAUT and ServQual models applied for acceptance, adoptions and use intention for e-learning services. E-learning resources should include quality content beyond technology facilities to increase students’ adoption and use intention successfully. Implications for practice and/or policy The paper concludes with advice for decision makers in universities who want to implement or maintain an e-learning programme. Managers must pay attention not only to the Learning Management Systems’ information technology attributes (eg, ease of use of the systems, fast access, speed of access and navigation of the systems, training, etc) but also to how to improve quality in e-learning resources like manuals, an online FAQ, forums, professor support to strengthen the acceptance and e-learning adoption. Facility conditions, social influence, habit and quality are important constructs that support students’ Learning Management System use intention. © 2021 British Educational Research Association

Perspectives on interaction with dead users' profiles on Facebook

With the Covid-19 pandemic, death has become an increasingly present and visible phenomenon on social networks. On Facebook, there is not a homogeneous treatment of death among deceased users' profiles: some remain active, whereas others are turned into memorials, but the criteria for this transformation are not clear. In both cases, privacy settings limit the interaction. These different possibilities give rise to different interactions and reactions among users. This paper addresses how dead users' profiles, multiplied due to the current pandemic, have been treated by Facebook's social-technical system, in comparison to possible posthumous interactions in the physical world. Our main objective is to understand to what extent Facebook's technical system supports or restricts social interactions concerning users' deaths. We carried out a qualitative exploratory analysis of data from 54 Facebook profiles belonging to people who passed away between June 2020 and March 2021. Among other results, we noticed: that Facebook fails to publicize the criteria for transforming active profiles into memorials and who are their heir contacts;that there is a difference in the amount and frequency of interactions between profiles transformed into memorials and those that remain active;and that profiles' privacy settings interfere with social interaction. This situation directly influences the ways other users relate or not with such profiles, which is an object of paramount importance in Human-Computer Interaction studies, especially when considering interaction as existence. © 2021 ACM.

Let's work together, especially in the pandemic: finding ways to encourage problem-focused voice behavior among passionate employees

Purpose: This study seeks to unravel the relationship between employees' passion for work and their engagement in problem-focused voice behavior by identifying a mediating role of their efforts to promote work-related goal congruence and a moderating role of their perceptions of pandemic threats to the organization. Design/methodology/approach: The research hypotheses were tested with quantitative data collected through a survey instrument administered among 158 employees in a large Portuguese-based organization that operates in the food sector, in the midst of the coronavirus disease 2019 (COVID-19) pandemic. The Process macro was applied to assess the moderated mediation dynamic that underpins the proposed theoretical framework. Findings: Employees' positive work-related energy enhances their propensity to speak up about organizational failures because they seek to find common ground with their colleagues with respect to the organization's goals and future. The mediating role of such congruence-promoting efforts is particularly prominent to the extent that employees dwell on the threats that a pandemic holds for their organization. Practical implications: The study pinpoints how HR managers can leverage a negative situation—employees who cannot keep the harmful organizational impact of a life-threatening virus out of their minds—into productive outcomes, by channeling positive work energy, derived from their passion for work, toward activities that bring organizational problems into the open. Originality/value: This study adds to HR management research by unveiling how employees' attempts to gather their coworkers around a shared work-related mindset can explain how their passion might spur reports of problem areas, as well as explicating how perceived pandemic-related threats activate this process. © 2021, Emerald Publishing Limited.

Waste-based biorefinery proposition as alternative to the sugarcane Vinasse destination from Brazilian sugar-energy sector

Brazil occupies the position of second largest ethanol producer in the world, largely using hydrated ethanol in flexible-fuel vehicles and fuel mixtures with addition of anhydrous ethanol to gasoline. In the Brazilian harvest of 2019/2020 were processed 642.6 million tons of sugarcane. Sugarcane cultivation promotes the production of several residues from the field to industrial processing, being bagasse and vinasse the most expressive in quantitative terms. To make it possible to implement a waste biorefinery, previous characterization studies are necessary to indicate their potential and the possibility to integrate industrial and biotechnological processes. Thus, the present study aimed to present an overview of the Brazilian sugar-energy sector, encouraging the implementation of sugarcane vinasse biorefineries and expanding the ethanol productive chain sustainability, using fermentative routes, microalgae cultivation and complementary processes. In addition, the study presents the perspectives of ethanol supply on the post-COVID-19 and the importance of the Brazilian Biofuels Policy (RenovaBio) as a strategic tool for the biofuels supply and for the emission of carbon credits, with features adaptable to other countries. © 2021, ETA-Florence Renewable Energies. All rights reserved.

A call for standardised age-disaggregated health data

The 2030 Sustainable Development Goals agenda calls for health data to be disaggregated by age. However, age groupings used to record and report health data vary greatly, hindering the harmonisation, comparability, and usefulness of these data, within and across countries. This variability has become especially evident during the COVID-19 pandemic, when there was an urgent need for rapid cross-country analyses of epidemiological patterns by age to direct public health action, but such analyses were limited by the lack of standard age categories. In this Personal View, we propose a recommended set of age groupings to address this issue. These groupings are informed by age-specific patterns of morbidity, mortality, and health risks, and by opportunities for prevention and disease intervention. We recommend age groupings of 5 years for all health data, except for those younger than 5 years, during which time there are rapid biological and physiological changes that justify a finer disaggregation. Although the focus of this Personal View is on the standardisation of the analysis and display of age groups, we also outline the challenges faced in collecting data on exact age, especially for health facilities and surveillance data. The proposed age disaggregation should facilitate targeted, age-specific policies and actions for health care and disease management.

Decision factors for remote work adoption: Advantages, disadvantages, driving forces and challenges

Facing one of the most challenging pandemics for organizational modus operandi (COVID-19), organizations are struggling for operational and strategic support. The adoption of remote work (RW) is increasing. For economic reasons, competitive advantage, or even as a pandemic response (business continuity plan), RW is a domain worth further investigation. However, the literature lacks insight regarding RW adoption. A design science research methodology was adopted, including a systematic literature review to elicit RW advantages, disadvantages, challenges and driving forces, as well as their relation. To evaluate and demonstrate findings, 129 qualitative interviews were performed with RW professionals. In the end, 57 decision factors were elicited, and 16 relations were validated. The authors concluded that cost-reduction and flexibility to promote work–life balance is the most positive outputs, while communication and technical problems, as well as management issues, are what most concerns professionals. Moreover, positive relations are more recognized among professionals over negative ones. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

COVID-19 detection through X-Ray chest images

The new COVID-19 virus has proven to be a real threat to the humanity. In this work we propose a machine learning approach to identify cases of infected patients through X-Ray images of their lungs. Due to the scarceness of the available data and limited computational power, we come up with two approaches: i) Build a custom Convolutional Neural Network (CNN) from scratch, with large data set of historical not COVID-19 pulmonary X-Rays. Tune the final layers with COVID-19 X-Ray images;ii) Apply transfer learning through pretrained CNN models (ResNet, VGG, DenseNet) and fine tuning with COVID-19 data. The second approach allowed us to reach around 90% accuracy on this challenging task. © 2020 IEEE.