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Web Geographic Information Systems (WebGISs) were widely used to monitor COVID-19 cases and deaths during the pandemic. Furthermore, geotechnologies were also very useful in education, public management, tourism, and other areas. Although there are WebGISs with a high level of sophistication, most are simple, consisting of geovisualizers of cases, deaths, and vaccinations. This study develops a WebGIS that offers information about age, comorbidities, and tests, which can be analyzed from specific points such as hospitals, main access roads, regions, or neighborhoods. Although it is not a highly sophisticated solution, the WebGIS developed in this study is especially useful for municipal governments in developing countries like Brazil that do not have patient health data in geographic databases. The WebGIS developed in this study offers public managers essential information for developing effective public policies to combat the COVID-19 pandemic and other epidemiological phenomena such as dengue and malaria. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, regions were affected by a combination of economic crises: weak demand and constrained supply. Several studies have sought to analyse the heterogeneous effects of supply and demand shocks on the labour market, economic growth, and the environment. This study has a different focus, estimating both direct and indirect effects of demand and supply shocks adopted during the pandemic in Brazil and Chile. Afterwards, the paper compares the degree of regional absorption (leakage) of income resulting from each of these shocks, applying an interregional input–output model for each country. The results of this study show that income absorption by the poorest regions is relatively greater in the case of a supply shock. It can be said, therefore, that this type of shock improves the retention of income generated in the poorest regions, favouring the development of these localities and the reduction in regional inequalities. The main reason for this result is that supply policies have restricted essential sectors to a lesser extent, and these sectors are generally less concentrated in large urban centres in both Brazil and Chile. In other words, much of the interregional leakage is driven by the demand for non-essential products, mainly in the richest urban economy centres. Finally, the geographical dimension of regional inequalities leads to the economic benefit of prosperous areas in the country when shocks occur in vulnerable regions, highlighting the centre–periphery pattern in both countries. [ABSTRACT FROM AUTHOR]

As the main methods of the coronavirus disease (COVID-19) transmission are air and physical contact, actions to mitigate and suppress its spread must be developed in order to change population dynamics and provide efficient control strategies. Here, these actions are described as a simple heuristic framework to establish public policies. Two control systems were studied: the first organized in the form of an algorithm stratified into three levels and the second as a minimization problem similar to optimal control strategies, applied to both social distancing and vaccination. The possible effects of these actions are modeled and applied to an extension of the Susceptible - Infected - Removed (SIR) compartmental model. The control system is developed, which is organized in the form of an algorithm stratified into three levels. These levels intend to represent social distancing strategies implemented by sanitary authorities around the globe, representing stronger or weaker grades of isolation intensity according to the ability of the healthcare system to cope with symptomatic individuals. The algorithm control is applied in a simulation, and the results give evidence of the effectiveness of the procedures adopted against the coronavirus. The model dynamics are analyzed and validated with simulations considering parameters obtained from epidemiological data from Brazil and Uruguay and in a more detailed way for three Brazilian states: São Paulo, Minas Gerais and Rio de Janeiro. The model was validated using cumulative data on cases and deaths. For cases of death, the results were satisfactory, while for case data, the response was reasonable, considering the possibility of adding delays or variations in parameters in the model. In addition, the effective reproduction number was proposed for the cities studied in Brazil, the result being relevant because it has a qualitative behavior similar to that published by official centers. This paper also discusses the implementation and optimization of social distancing and vaccination control strategies, considering different parameters and their effects on reducing the number of cases and deaths. Model simulations present promising results for developing strategies to attack COVID-19 dissemination. [ABSTRACT FROM AUTHOR]

Brazil experienced some of the highest rates of COVID-19 globally. This was complicated by the fact that 35 million of its citizens have limited access to water, a primary resource necessary to stem the spread of infectious diseases. In many cases, civil society organizations (CSOs) stepped into this void left by responsible authorities. This paper explores how CSOs in Rio de Janeiro helped populations struggling with access to water, sanitation, and hygiene (WASH) during the pandemic, and what coping strategies are transferable to similar contexts. In-depth interviews ( n = 15) were conducted with CSO representatives in the metropolitan region of Rio de Janeiro. Thematic analysis of the interviews revealed that COVID-19 exacerbated pre-existing social inequities among vulnerable populations, undermining their ability to protect their health. CSOs provided emergency relief aid but faced the counterproductive actions of public authorities who promoted a narrative that diminished the risks of COVID-19 and the importance of non-pharmacological interventions. CSOs fought this narrative by promoting sensitization among vulnerable populations and partnering with other stakeholders in networks of solidarity, playing a vital role in the distribution of health-promoting services. These strategies are transferrable to other contexts where state narratives oppose public health understandings, particularly for extremely vulnerable populations.

The aim of this paper is to describe the profile of maternal mortality of COVID-19 in the state of Ceará, Brazil, in the period 2020. Ecological, exploratory, cross-sectional study, with secondary data from the Influenza Epidemiological Surveillance Information System, were made available by the Obstetric Observatory Brazilian COVID-19. A total of 485 pregnant and postpartum women were included, and the analysis considered the notifications from the year 2020. The variables of interest and the outcome (death/cure by COVID-19) were analyzed in a descriptive way. Most pregnant and postpartum women were between 20 and 35 years old, brown/white skin color and residing in an urban area. The proportion of deaths was 5.8% in the year 2020. In that period, the rates of hospitalization in the ward increased by 95.5%, 12.6% of hospitalization in the Unit of Intensive Care (ICU), and 7.2% needed invasive ventilatory support. Maternal mortality from COVID-19 suggests an emergency in terms of the development of health actions and policies due to the aggravation and risks due to this disease.

Since the onset of the coronavirus disease, COVID-19 pandemic, concern arose for those who might be at higher risk of a worse COVID-19 prognosis, such as those with cystic fibrosis (CF). In this context, we evaluated the features of hospitalized patients with CF due to severe acute respiratory infection (SARI) in Brazil and we also performed a systematic review including all the studies published from the beginning of the first case of COVID-19 (17 November 2019) to the date of this search (23 May 2022) which included, concomitantly, patients with CF and COVID-19 in the worldwide population. In our Brazilian data, we evaluated the period from December 2019 to March 2022, and we included 33 demographical and clinical patients' features. We classified the patients into groups: (G1) SARI due to another viral infection than severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (23; 5.4%), (G2) SARI due to an unknown etiological agent (286; 67.1%), and (G3) SARI due to SARS-CoV-2 infection (117; 27.5%). The individuals in G3 tended to be older, especially over 50 years old, and presented a higher prevalence of dyspnea, peripheral capillary oxygen saturation (SpO2) <95%, and cardiopathy. The highest prevalence for intensive care unit (ICU) treatment (52; 44.4%) and invasive mechanical ventilation (29; 24.8%) was for patients in G3. Almost half of the patients in G3 died (51; 43.6%); in contrast, none in G1 died. However, we observed 43 (15.0%) deaths in G2. In addition, 12 (4.2%) and one (0.9%) death not associated with SARI occurred, respectively, in the G2 and G3. The patients who died due to SARS-CoV-2 infection had a higher frequency of SpO2 <95% (46; 90.2%), ICU treatment (34; 66.7%), and invasive mechanical ventilation (27; 52.9%) when compared to those who recovered. The systematic review comprised a total of 31 papers published as observational studies. These studies comprised 661,386 patients in total, including children, adults, and elderly age groups. However, only 19,150 (2.9%) patients were diagnosed with CF and, from these patients, 2523 (0.4%) were diagnosed with both CF and COVID-19. It was observed that the most common outcome was the need for hospitalization (n = 322 patients with CF), and the need for oxygen support (n = 139 patients with CF). One hundred patients with CF needed intensive care units, fifty patients needed non-invasive mechanical ventilation support, and only three patients were described as receiving invasive mechanical ventilation support. Deaths were described in 38 patients with CF. Importantly, lung-transplanted patients with CF represented an increased risk of death in one publication; in accordance, another study described that lung transplantation and moderate to severe lung disease were independent risk factors for severe outcomes after SARS-CoV-2 infection. In contrast with the literature, in conclusion, Brazilian patients in G3 presented a severe phenotype, even though most of the other studies did not observe worse outcomes in patients with CF and COVID-19. [ABSTRACT FROM AUTHOR]

Acknowledging the extreme risk COVID-19 poses to humans, this paper attempted to analyze and compare case fatality rates, identify the existence of learning curves for COVID-19 medical treatments, and examine the impact of vaccination on fatality rate reduction. Confirmed cases and deaths were extracted from the "Daily Situation Report" provided by the World Health Organization. The results showed that low registration and low viral test rates resulted in low fatality rates, and the learning curve was significant for all countries except China. Treatment for COVID-19 can be improved through repeated experience. Vaccinations in the U.K. and U.S.A. are highly effective in reducing fatality rates, but not in other countries. The positive impact of vaccines may be attributed to higher vaccination rates. In addition to China, this study identified the existence of learning curves for the medical treatment of COVID-19 that can explain the effect of vaccination rates on fatalities. [ABSTRACT FROM AUTHOR]

Since the COVID-19 pandemic emerged, vaccination has been the core strategy to mitigate the spread of SARS-CoV-2 in humans. This paper analyzes the impact of COVID-19 vaccination on hospitalizations and deaths in the state of Rio Grande do Norte, Brazil. We analyzed data from 23,516 hospitalized COVID-19 patients diagnosed between April 2020 and August 2021. We excluded the data from patients hospitalized through direct occupancy, unknown outcomes, and unconfirmed COVID-19 cases, resulting in data from 12,635 patients cross-referenced with the immunization status during hospitalization. Our results indicated that administering at least one dose of the immunizers was sufficient to significantly reduce the occurrence of moderate and severe COVID-19 cases among patients under 59 years. Considering the partially or fully immunized patients, the mean age is similar between the analyzed groups, despite the occurrence of comorbidities and higher than that observed among not immunized patients. Thus, immunized patients present lower Unified Score for Prioritization (USP) levels when diagnosed with COVID-19. Our data suggest that COVID-19 vaccination significantly reduced the hospitalization and death of elderly patients (60+ years) after administration of at least one dose. Comorbidities do not change the mean age of moderate/severe COVID-19 cases and the days required for the hospitalization of these patients.

Populism has been at the center of recent debates in political science and international relations scholarship. Recognized as a contested concept and framed as a new global phenomenon, populism emerged in the context of liberal democracies, where political actors inflate social antagonisms by putting the people against the elite. Facing a global health crisis where a sense of threat, uncertainty, and emergency has pushed normal politics into the realm of politics of crisis, populists have actively engaged in creating a spectacularization of failure—of science, institutions, experts, governments—vis-à-vis the new Coronavirus, and in creating doubts about and devaluing scientists, experts and governments. Issues such as mask mandates, lockdown measures, compulsory vaccination, medicine effectiveness, and vaccine certificates became politicized. That is, they have been taken from normal politics and made contingent and controversial in order to deepen already existing political divisions and polarization. Exploring the case of Germany and Brazil, we will show how populists tried to use the pandemic to forge divisions between the people and the elite (represented by scientists, health experts, and the press). This conceptual-empirical paper wishes to make a contribution to the debate on how populists brought scientific public health issues into their black-and-white, antagonistic vision of society and hence instrumentalized COVID-19 for their own political gain. [ABSTRACT FROM AUTHOR]

This paper aims to present aspects related to corporate governance, organisational resilience and sustainable practices developed by Brazilian companies during the COVID-19 pandemic. The methodological strategy included documentary research to identify sustainability reports published by companies listed on the Ibovespa index, which were examined through the content analysis technique. The results allowed light to be shed on opportunities for improvement concerning sustainability and corporate governance. Regarding organisational resilience, risk management is central for the development of sustainability practices by organisations. The support to society related to the COVID-19 pandemic was evidenced mainly through the donation of financial resources, equipment and hospital supplies. Practices related to reducing energy consumption and minimising waste generation were those most associated with environmental aspects. The actions identified were mapped according to their relations with the SDGs. Managers can benefit from the information presented in this study to enhance organisational sustainability and resilience, while researchers can use it as a starting point for future studies. [ABSTRACT FROM AUTHOR]

Since December 2019, with the discovery of a new coronavirus, humanity has been exposed to a large amount of information from different media. Information is not always true and official. Known as an infodemic, false information can increase the negative effects of the pandemic by impairing data readability and disease control. The paper aims to find similar patterns of behavior of the Brazilian population during 2021 in two analyses: with vaccination data of all age groups and using the age group of 64 years or more, representing 13% of the population, using the multivariate analysis technique. Infodemic vaccination information and pandemic numbers were also used. Dendrograms were used as a cluster visualization technique. The result of the generated clusters was verified by two algorithms: the cophenetic correlation coefficient, which obtained satisfactory results above 0.7, and the elbow method, which corroborated the number of clusters found. In the result of the analysis with all age groups, more homogeneous divisions were perceived among Brazilian states, while the second analysis resulted in more heterogeneous clusters, recalling that at the start of vaccinations they could have had fear, doubts, and significant belief in the infodemic. [ABSTRACT FROM AUTHOR]

Propolis has gained wide popularity over the last decades in several parts of the world. In parallel, the literature about propolis composition and biological properties increased markedly. A great number of papers have demonstrated that propolis from different parts of the world is composed mainly of phenolic substances, frequently flavonoids, derived from plant resins. Propolis has a relevant role in increasing the social immunity of bee hives. Experimental evidence indicates that propolis and its components have activity against bacteria, fungi, and viruses. Mechanisms of action on bacteria, fungi, and viruses are known for several propolis components. Experiments have shown that propolis may act synergistically with antibiotics, antifungals, and antivirus drugs, permitting the administration of lower doses of drugs and higher antimicrobial effects. The current trend of growing resistance of microbial pathogens to the available drugs has encouraged the introduction of propolis in therapy against infectious diseases. Because propolis composition is widely variable, standardized propolis extracts have been produced. Successful clinical trials have included propolis extracts as medicine in dentistry and as an adjuvant in the treatment of patients against COVID-19. Present world health conditions encourage initiatives toward the spread of the niche of propolis, not only as traditional and alternative medicine but also as a relevant protagonist in anti-infectious therapy. Production of propolis and other apiary products is environmentally friendly and may contribute to alleviating the current crisis of the decline of bee populations. Propolis production has had social-economic relevance in Brazil, providing benefits to underprivileged people. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is a serious threat to all of us. It has caused an unprecedented shock to the world's economy, and it has interrupted the lives and livelihood of millions of people. In the last two years, a large body of literature has attempted to forecast the main dimensions of the COVID-19 outbreak using a wide set of models. In this paper, I forecast the short- to mid-term cumulative deaths from COVID-19 in 12 hard-hit big countries around the world as of 20 August 2021. The data used in the analysis were extracted from the Our World in Data COVID-19 dataset. Both non-seasonal and seasonal autoregressive integrated moving averages (ARIMA and SARIMA) were estimated. The analysis showed that: (i) ARIMA/SARIMA forecasts were sufficiently accurate in both the training and test set by always outperforming the simple alternative forecasting techniques chosen as benchmarks (Mean, Naïve, and Seasonal Naïve); (ii) SARIMA models outperformed ARIMA models in 46 out 48 metrics (in forecasting future values), i.e., on 95.8% of all the considered forecast accuracy measures (mean absolute error [MAE], mean absolute percentage error [MAPE], mean absolute scaled error [MASE], and the root mean squared error [RMSE]), suggesting a clear seasonal pattern in the data; and (iii) the forecasted values from SARIMA models fitted very well the observed (real-time) data for the period 21 August 2021–19 September 2021 for almost all the countries analyzed. This article shows that SARIMA can be safely used for both the short- and medium-term predictions of COVID-19 deaths. Thus, this approach can help government authorities to monitor and manage the huge pressure that COVID-19 is exerting on national healthcare systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the influence of holidays and community mobility on the transmission rate and death count of COVID-19 in Brazil. We identify national holidays and hallmark holidays to assess their effect on disease reports of confirmed cases and deaths. First, we use a one-variate model with the number of infected people as input data to forecast the number of deaths. This simple model is compared with a more robust deep learning multi-variate model that uses mobility and transmission rates (R0, Re) from a SEIRD model as input data. A principal components model of community mobility, generated by the principal component analysis (PCA) method, is added to improve the input features for the multi-variate model. The deep learning model architecture is an LSTM stacked layer combined with a dense layer to regress daily deaths caused by COVID-19. The multi-variate model incremented with engineered input features can enhance the forecast performance by up to 18.99% compared to the standard one-variate data-driven model.

The new betacoronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the cause of COVID-19, and has spread rapidly around the world, reaching more than 200 countries, around 364 million people and causing more than 5 million deaths according to the World Health Organization, so this paper reports a fatal case of SARS-CoV-2 infection in a young pregnant woman with heart disease, without vertical transmission. A 26 years old patient at 28th week of pregnancy with regular prenatal care, presented dry cough, high fever, and severe respiratory distress. Due to her clinical symptoms, she sought medical care at a cardiology hospital in Northern Brazil. The medical conditions she presented were heart disease, rheumatic fever history and had no recent record of national or international travel. She was hospitalized and after clinical stabilization, she was referred for an emergency cesarean intervention. The young mother and the newborn were transferred to the intensive care unit after surgery, where diagnostic tests for respiratory viral infections, including SARS-CoV-2, were performed. The mother tested positive, while her newborn was negative for SARS-CoV-2 demonstrating no vertical transmission of SARS-CoV-2 in this severe case. This study reveals that despite the mother's initially mild symptoms, she progressed to severe clinical conditions resulting in death, although no vertical transmission was observed. This report highlights the relevance of comorbidities for the unfavorable clinical course of COVID-19. [ABSTRACT FROM AUTHOR]

In this paper, we group South American countries based on the number of infected cases and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Peru, Paraguay, Uruguay, and Venezuela. The data used are collected from a database of Johns Hopkins University, an institution that is dedicated to sensing and monitoring the evolution of the COVID-19 pandemic. A statistical analysis, based on principal components with modern and recent techniques, is conducted. Initially, utilizing the correlation matrix, standard components and varimax rotations are calculated. Then, by using disjoint components and functional components, the countries are grouped. An algorithm that allows us to keep the principal component analysis updated with a sensor in the data warehouse is designed. As reported in the conclusions, this grouping changes depending on the number of components considered, the type of principal component (standard, disjoint or functional) and the variable to be considered (infected cases or deaths). The results obtained are compared to the k-means technique. The COVID-19 cases and their deaths vary in the different countries due to diverse reasons, as reported in the conclusions.

This paper studies the interplay between social distancing and the spread of the COVID-19 disease-a global pandemic that has affected most of the world's population. Our goals are to (1) to observe the correlation between the strictness of social distancing policies and the spread of disease and (2) to determine the optimal adoption level of social distancing policies. The earliest instances of the virus were found in China, and the virus has reached the United States with devastating consequences. Other countries severely affected by the pandemic are Brazil, Russia, the United Kingdom, Spain, India, Italy, and France. Although it is impossible to stop it, it is possible to slow down its spread to reduce its impact on the society and economy. Governments around the world have deployed various policies to reduce the virus spread in response to the pandemic. To assess the effectiveness of these policies, the system's dynamics of the society needs to be analyzed, which is generally not possible with mathematical linear equations or Monte Carlo methods because human society is a complex adaptive system with continuous feedback loops. Because of the challenges with the other methods, we chose agent-based methods to conduct our study. Moreover, recent agent-based modeling studies for the COVID-19 pandemic show significant promise in assisting decision-makers in managing the crisis by applying policies such as social distancing, disease testing, contact tracing, home isolation, emergency hospitalization, and travel prevention to reduce infection rates. Based on modeling studies conducted in Imperial College, increasing levels of interventions could slow the spread of disease and infection. We ran the model with six different percentages of social distancing while keeping the other parameters constant. The results show that social distancing affects the spread of COVID-19 significantly, in turn decreasing the spread of disease and infection rates when implemented at higher levels. We also validated these results by using the behavior space tool with ten experiments with varying social distancing levels. We conclude that applying and increasing social distancing policy levels leads to a significant reduction in infection spread and the number of deaths. Both experiments show that infection rates are reduced drastically when social distancing intervention is implemented between 80% to 100%.

The Coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health crisis with unmatched outcomes and effects. This pandemic has caused an infodemic of article publication in scientific journals. Dental journals have been active in the publication of COVID-19 related articles from the beginning of the pandemic. In this cross-sectional survey, we present an analysis of the scientific output of dental journals on COVID-19. The PubMed COVID-19 database was searched with the "Dental Journals" filter. Data including journal name, country, month of publication and number of citations were recorded. Science mapping analysis of the most used keywords was also performed. The search retrieved a total of 659 articles, of which 28 were excluded. Oral Diseases has published the most COVID-19 articles (15.1%), followed by the British Journal of Oral and Maxillofacial Surgery (8.6%) and the Journal of Dental Education (7.9%). Most of the articles were from researchers from the United States (168), United Kingdom (120) and Brazil (83). The number of citations of the published articles ranged from 0 to 406, with most articles (64.2%) having no citations. Science Mapping analysis revealed that the most used keywords were coronavirus infections, pandemics and humans. The dental community has been active in the publication of COVID-19 articles from the beginning of the pandemic. The papers published by dental journals explore issues such as the management of clinical practices during the outbreak, infection control in the dental setting, signs and symptoms of COVID-19 affecting the oral cavity, and the impact of the COVID-19 pandemic on educational and clinical programs.

São Paulo is the most populous state in Brazil, home to around 22% of the country's population. The total number of Covid-19-infected people in São Paulo has reached more than 1 million, while its total death toll stands at 25% of all the country's fatalities. Joining the Brazilian academia efforts in the fight against Covid-19, in this paper we describe a unified framework for monitoring and forecasting the Covid-19 progress in the state of São Paulo. More specifically, a freely available, online platform to collect and exploit Covid-19 time-series data is presented, supporting decision-makers while still allowing the general public to interact with data from different regions of the state. Moreover, a novel forecasting data-driven method has also been proposed, by combining the so-called Susceptible-Infectious-Recovered-Deceased model with machine learning strategies to better fit the mathematical model's coefficients for predicting Infections, Recoveries, Deaths, and Viral Reproduction Numbers. We show that the obtained predictor is capable of dealing with badly conditioned data samples while still delivering accurate 10-day predictions. Our integrated computational system can be used for guiding government actions mainly in two basic aspects: real-time data assessment and dynamic predictions of Covid-19 curves for different regions of the state. We extend our analysis and investigation to inspect the virus spreading in Brazil in its regions. Finally, experiments involving the Covid-19 advance in other countries are also given.

The persistence of symptoms for more than three months following infection with severe acute respiratory syndrome coronavirus 2 is referred to as "Long COVID". To gain a deeper understanding of the etiology and long-term progression of symptoms, this study aims to analyze the prevalence of Long COVID and its associated factors in a cohort of Brazilian adults and elders, twelve months after hospital discharge. An observational, prospective, and follow-up study was performed with a cohort of adults and older adults diagnosed with COVID-19 in 2020 in the State of Paraná, Brazil. Twelve months after hospital discharge, patients answered a phone questionnaire about the persistence of symptoms after three levels of exposure to COVID-19's acute phase (ambulatory, medical ward, and intensive care unit). According to the characteristics of participants, the prevalence of Long COVID-19 was calculated, and logistic regression analyses were conducted. We analyzed data from 1822 participants (980 adults [≥18–<60 years] and 842 older people [≥60 years]) across three exposure levels. The overall Long COVID prevalence was 64.2%. Long COVID was observed in 646 adults (55%; of which 326 were women) and 523 older people (45%; of which 284 were women). Females had a higher prevalence of long-term symptoms (52%) compared with men. The most common post-COVID-19 conditions in the 12-month follow-up were neurological (49.8%), followed by musculoskeletal (35.1%) and persistent respiratory symptoms (26.5%). Male individuals were less likely to develop Long COVID (aOR = 0.50). Other determinants were also considered risky, such as the presence of comorbidities (aOR = 1.41). Being an adult and having been hospitalized was associated with the development of Long COVID. The risk of developing Long COVID was twice as high for ward patients (aOR = 2.53) and three times as high for ICU patients (aOR = 3.56) when compared to non-hospitalized patients. Presenting clinical manifestations of digestive (aOR = 1.56), endocrine (aOR = 2.14), cutaneous (aOR = 2.51), musculoskeletal (aOR = 2.76) and psychological systems (aOR = 1.66) made adults more likely to develop Long COVID. Long COVID was present in a large proportion of people affected by the SARS-CoV-2 infection. Presence of Long COVID symptoms displayed a dose–response relationship with the level of disease exposure, with a greater prevalence of symptoms associated with the severe form in the acute period. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has posed unprecedented challenges to global health systems, particularly among vulnerable populations such as the elderly. Understanding the interplay between anthropometric markers, molecular profiles, and disease severity is crucial for effective clinical management and intervention strategies. We conducted a cohort study comprising 43 elderly COVID-19 patients admitted to São Lucas Hospital, PUCRS, Brazil. Anthropometric measurements, including calf circumference (CC) and abdominal circumference (AC), were assessed alongside molecular analyses of peripheral blood samples obtained within 48 h of hospital admission. Sociodemographic data were collected from electronic medical records for comprehensive analysis. Our findings revealed a possible relationship between overweight status, increased abdominal adiposity, and prolonged hospitalization duration, alongside heightened disease severity. We also found no significant correlations between BMI, vitamin D levels, and clinical outcomes. Elevated oxygen requirements were observed in both normal and overweight individuals, with the latter necessitating prolonged oxygen therapy. Molecular analyses revealed changes in the inflammatory profile regarding the outcome of the patients. Our study highlights the critical importance of both anthropometric and molecular markers in predicting disease severity and clinical outcomes in elderly individuals with COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused significant changes in society's dynamics, particularly affecting the landscape of education. Research in several areas may have been affected during periods of social restrictions. This study analyzed the curricula of 558 researchers across 27 graduate programs in physical education in Brazil to investigate the potential impact of the COVID-19 pandemic on scientific publications. Researchers' production from 2018 to 2022 underwent a comprehensive analysis, considering the total number of publications, Qualis rank, and journal impact factor. Data were analyzed using chi-squared and Kruskal-Wallis tests. Significance was set at 5%. Overall, the analyzed researchers published a total of 17,932 manuscripts from 2018 to 2022. During the COVID-19 pandemic, there was a decline of 16.4% in the number of articles published (p = 0.001). This decline was similar between men and women (p = 0.603) and was associated with a worsening in Qualis rank (p = 0.001). The number of studies published in journals with impact factors was also affected (p = 0.001). The findings suggest a potential impact of the COVID-19 pandemic on the scientific production of Brazilian researchers in the field of physical education. Funding agencies should consider the challenges associated with the COVID-19 pandemic before evaluating researchers and programs. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic offers an historic precedent to review and challenge the values of social, economic, environmental, and cultural belief systems. The concept of the "New Normal" and the experience of the global pandemic provide points of transition in thinking about our relationship to our planet and to each other. These include the fragility of contemporary economics, dependency on industrialized urban infrastructures, and reliance on top-down governance, vulnerability to climate disasters, dislocation from the natural world, societal inequalities, and the loss of cultural memory. The paper considers the potential role of systems thinking in attempting to manage societies' responses to the pandemic. To provide the methodological context in which some systems thinking can be applied to alleviate the pandemic, we conduct a focused literature review of systemic frameworks, and using examples from Brazil and England, the paper questions the validity of existing disaster management systems and proposes an integrated critical systems approach. Reflecting on these experiences, questions of systems criticality are further developed and considered in relation to critical recovery from disasters and as integral critical systems (ICS) to interrogate the intention of systems. Finally, the paper reflects upon the value of systems and the values embedded in systems that may or may not promote equitable well-being in recovery from disasters such as COVID-19. [ABSTRACT FROM AUTHOR]

Daily data on COVID-19 infections and deaths tend to possess weekly oscillations. The purpose of this work is to forecast COVID-19 data with partially cyclical fluctuations. A partially periodic oscillating ARIMA model is suggested to enhance the predictive performance. The model, optimized for improved prediction, characterizes and forecasts COVID-19 time series data marked by weekly oscillations. Parameter estimation and out-of-sample forecasting are carried out with data on daily COVID-19 infections and deaths between January 2021 and October 2022 in the USA, Germany, and Brazil, in which the COVID-19 data exhibit the strongest weekly cycle behaviors. Prediction accuracy measures, such as RMSE, MAE, and HMAE, are evaluated, and 95% prediction intervals are constructed. It was found that predictions of daily COVID-19 data can be improved considerably: a maximum of 55–65% in RMSE, 58–70% in MAE, and 46–60% in HMAE, compared to the existing models. This study provides a useful predictive model for the COVID-19 pandemic, and can help institutions manage their healthcare systems with more accurate statistical information. [ABSTRACT FROM AUTHOR]

More than 61% of all human pathogens are zoonotic, representing 75% of all emerging pathogens during the past decade. Albeit significant technological leaps in diagnostics development and disease surveillance, zoonotic emerging infectious diseases are evermore a matter of concern, particularly in modern days where global warming keeps providing ideal climatic conditions to the introduction of exotic infectious agents or disease vectors in new territories. Worryingly, the 2019 novel coronavirus epidemic acts as an extreme reminder of the role animal reservoirs play in public health, accounting for over 4,200,000 deaths worldwide until today. In this Special Issue, we approach a myriad of zoonotic infectious diseases and their complex mechanisms. This Special Issue is composed of three reviews on zoonotic diseases of African Lions, hemogregarine classification, and hepatitis E virus in Brazil, followed by one letter and one opinion piece that broadens the spectrum of disease emergence to mechanistic aspects of emerging non-communicable diseases. The Special Issue is completed by six research papers covering a wide array of emerging and re-emerging diseases of poultry, bovine, poultry and tortoises, of various nature such as parasitic, bacterial, and viral. This is a brief but assertive collection that showcases the need to address health at the animal–human–environment interface, in a One Health perspective. [ABSTRACT FROM AUTHOR]

Long COVID is a multisystem condition that has multiple consequences for the physical, mental, and social health of COVID-19 survivors. The impact of the long COVID condition remains unclear, particularly among middle-aged and older adults, who are at greater risk than younger people of persisting symptoms associated with COVID-19. Therefore, we aimed to understand the experiences of middle-aged and older people who had been hospitalized for COVID-19 and the repercussions of long-term COVID symptoms in their daily lives. A qualitative study was carried out, adopting the framework of the constructivist grounded theory (CGT) proposed by Kathy Charmaz. Fifty-six middle-aged and older adult participants from the southern region of Brazil were recruited. Data were gathered from semi-structured telephone interviews. Concomitantly a comparative analysis was performed to identify categories and codes using the MaxQDA® software (version 2022). Three subcategories were identified: (1) experiencing COVID-19 in the acute phase; (2) oscillating between 'good days' and 'bad days' in long COVID; and (3) (re)constructing identity. These concepts interact with each other and converge upon the central category of this study: recasting oneself to the uniqueness of the illness experience of long COVID. Our findings provided insights related to the disruption in the lives of long COVID-19 sufferers who still live with persistent symptoms of the disease, including physical, social, family, emotional and spiritual repercussions. Likewise, this study may aid in developing friendly and welcoming social environments, lowering stigma and prejudice towards patients with long COVID, and fostering prompt and suitable policy support and mental health care for these individuals. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study is to evaluate some mechanisms of the immune response of people infected with SARS-CoV-2 in both acute infection and early and late convalescence phases. Methods: This is a cohort study of 70 cases of COVID-19, confirmed by RT-PCR, followed up to 60 days. Plasma Samples and clinical data were. Viral load, blood count, indicators inflammation were the parameters evaluated. Cellular immune response was evaluated by flow cytometry and Luminex immunoassays. Results: In the severe group, hypertension was the only reported comorbidity. Non severe patients have activated memory naive CD4+ T cells. Critically ill patients have central memory CD4+ T cell activation. Severe COVID-19 patients have both central memory and activated effector CD8+ T cells. Non-severe COVID-19 cases showed an increase in IL1β, IL-6, IL-10 and TNF and severely ill patients had higher levels of the cytokines IL-6, IL-10 and CXCL8. Conclusions: The present work showed that different cellular responses are observed according to the COVID-19 severity in patients from Brazil an epicenter the pandemic in South America. Also, we notice that some cytokines can be used as predictive markers for the disease outcome, possibility implementation of strategies effective by health managers. [ABSTRACT FROM AUTHOR]

Brazil has the second-highest COVID-19 death rate worldwide, and Rio de Janeiro is among the states with the highest rate in the country. Although vaccine coverage has been achieved, it is anticipated that COVID-19 will transition into an endemic disease. It is concerning that the molecular mechanisms underlying clinical evolution from mild to severe disease, as well as the mechanisms leading to long COVID-19, are not yet fully understood. NMR and MS-based metabolomics were used to identify metabolites associated with COVID-19 pathophysiology and disease outcome. Severe COVID-19 cases (n = 35) were enrolled in two reference centers in Rio de Janeiro within 72 h of ICU admission, alongside 12 non-infected control subjects. COVID-19 patients were grouped into survivors (n = 18) and non-survivors (n = 17). Choline-related metabolites, serine, glycine, and betaine, were reduced in severe COVID-19, indicating dysregulation in methyl donors. Non-survivors had higher levels of creatine/creatinine, 4-hydroxyproline, gluconic acid, and N-acetylserine, indicating liver and kidney dysfunction. Several changes were greater in women; thus, patients' sex should be considered in pandemic surveillance to achieve better disease stratification and improve outcomes. These metabolic alterations may be useful to monitor organ (dys) function and to understand the pathophysiology of acute and possibly post-acute COVID-19 syndromes. [ABSTRACT FROM AUTHOR]

The contributions of emergent literacy skills to reading and writing development have been evidenced in different linguistic contexts. The worsening of the Brazil literacy scenario during the pandemic denoted the importance of a better understanding of these contributions' specificities in Brazilian Portuguese to support evidence-based mitigation strategies. This study aimed to analyze the associations between emergent literacy components (emergent writing, alphabet knowledge, vocabulary, and phonological awareness) and word/pseudoword reading and spelling performance in first grade students during COVID-19. A total of 42 children (Mage = 6.29 years, SD = 0.45, 52.4% female) participated remotely in this study. Correlations and multilinear regression analyses were conducted. The results show significant associations between emergent literacy components and reading and spelling performance. Stronger associations were found with specific emergent skills such as letter writing, spontaneous writing, letter-sound production, and alliteration. Regression models indicated that children's performance in early literacy skills explained 49% of the variance in reading and 55% of the variance in spelling. This study highlighted the role of emergent writing and alphabet knowledge as reading and spelling predictors during literacy acquisition in Brazilian Portuguese. Implications for educational context and directions for remediating the negative impact of the pandemic on learning were discussed. [ABSTRACT FROM AUTHOR]

Objective: To analyze the spatial pattern of the incidence of COVID-19 in association with social determinants of health (SDH) in the Northeast Region of Brazil during the first year of the pandemic. Methods: We conducted an ecological analytical study that included notifications made between 27 March 2020 and 27 March 2021. The data analysis used two global regression models: the ordinary least squares (OLS) and spatial lag model and the geographically weighted multiscale regression model (GWMSR). Results: We observed that the Gini index, illiteracy rate, percentages of people living below the poverty line, people in households who were vulnerable to poverty, and dependent elderly people are predictors of a higher incidence of COVID-19 in Northeast Brazil. Conclusions: Results of this study may contribute to generating new hypotheses for studies focusing on the syndemic process and for the formulation of intersectoral public policies targeting the population at greatest vulnerability to minimize the impact of the disease. [ABSTRACT FROM AUTHOR]

The study aimed to compare the impact of Role Blurring on mental health and Work-Life Integration in the Brazilian and Spanish populations during COVID-19. Role Blurring, which is related to resources and demands in the work context, affects coping with stressors arising from role overlapping and impacts individuals' perception of work overload and mental health. The sample consisted of 877 adults from Spain (n = 498) and Brazil (n = 372), and various statistical analyses were conducted to compare the groups. Results showed that Role Blurring is linked to symptoms of anxiety, depression, and stress, as well as suicidal ideation. Therefore, it is essential to promote working conditions that limit expectations on availability and favor disconnection from work during leisure time. Public policies that intervene, promote, and prevent psychosocial risk factors in emergent contexts are crucial to prevent suicidal ideation and attempts. Considering the high expected influence of Blurring as a focus of interventions can be reflected in the medium term in the indicators of well-being and satisfaction of companies, institutions and organizations. This can result in the reduction of health costs aimed at cushioning post-COVID-19 impacts on mental health. The study is relevant to understand the impact of the pandemic and technology on mental health and suggests the need for interventions to promote work-life balance and prevent psychosocial risks. [ABSTRACT FROM AUTHOR]

Estimating seroprevalence and vaccination coverage against COVID-19 is crucial to the development of well-targeted public health policies at the local level. Here, we estimated seroprevalence and vaccination coverage in a lower-middle-class population in Brazil. We conducted an observational, cross-sectional, population-based survey from 24 September to 19 December 2021. CMIA tests were used to detect anti-SARS-CoV-2 IgG against the N-protein. The overall seroprevalence was 24.15% (177/733), and vaccination coverage was 91.40% (670/733); 72.09% (483/670) were fully vaccinated. Among vaccinated participants, seroprevalence was 24.77% (95% CI 21.50–28.04; 166/670), with a prevalence ratio (PR) of 1.03 (95% CI 0.98–1.08; p-value 0.131). Among participants who received an mRNA vaccine with S-based epitope (485), seroprevalence was 16.29% (95% CI 13.04–19.85; 79/485). Among unvaccinated participants, seroprevalence was 17.46% (95% CI 10.04–28.62; 11/63). Finally, in spite of the political climate and other possible causes for vaccine hesitancy, the positive Brazilian culture towards vaccination might have curbed hesitancy. [ABSTRACT FROM AUTHOR]

Background: COVID-19 pandemic times forced health education to go online, and, due to this necessity, long-term difficulties in education such as bibliographic search in databases like PubMed might have worsened even when platforms such as PubMed provide helping mechanisms to the user. These difficulties or even complete lack of knowledge are, unfortunately, not well documented in the literature. Therefore, this study aimed to describe doubts, lack of knowledge and questions of researchers regarding bibliographic research in PubMed as well as to solve all of those doubts by developing a didactic e-book in relation to bibliographic research in PubMed. Methods: This cross-sectional and populational-based study was conducted between January and April 2021. In northern Brazil, a total of 105 dentistry undergraduate students (DUS) received an anonymous digital form (Google® Forms Platform) using a non-probabilistic "snowball" sampling technique. The digital form was composed of four blocks of dichotomous and multiple-choice questions. After signing the informed consent term, the DUS were divided into three groups according to their period/semester in the dentistry program during the study time (G1: 1st period/semester; G2: 5th period/semester and G3: 10th period/semester). A total of 25 questions referring to demographic, educational and knowledge data about how to do scientific research and how to use bibliographic search in PubMed were asked, and all data were presented as descriptive percentages and then analyzed using the Chi square and G tests. Results: From 105 (100%), G1 had 29/105 (27.6%); G2 had 37/105 (35.2%); G3 had 39/105 (37.2%), the average age was 22.34 years and most participants were female 85/105 (81%). Among our sample, 56/105 (53.4%) had not used any type of search strategy, and 96/105 (91.4%) used database research methods. The main database for literature search used was Scielo 92/105 (87.6%), and 63/105 (60%) had general questions or doubts about bibliographic research. All these data had statistical significance p < 0.0001. Conclusions: The results demonstrate a lack of knowledge and doubts in DUS from three different periods/semesters, and this collected information can help in the formation of didactic material to solve such doubts. [ABSTRACT FROM AUTHOR]

This study introduces a new method for identifying COVID-19 infections using blood test data as part of an anomaly detection problem by combining the kernel principal component analysis (KPCA) and one-class support vector machine (OCSVM). This approach aims to differentiate healthy individuals from those infected with COVID-19 using blood test samples. The KPCA model is used to identify nonlinear patterns in the data, and the OCSVM is used to detect abnormal features. This approach is semi-supervised as it uses unlabeled data during training and only requires data from healthy cases. The method's performance was tested using two sets of blood test samples from hospitals in Brazil and Italy. Compared to other semi-supervised models, such as KPCA-based isolation forest (iForest), local outlier factor (LOF), elliptical envelope (EE) schemes, independent component analysis (ICA), and PCA-based OCSVM, the proposed KPCA-OSVM approach achieved enhanced discrimination performance for detecting potential COVID-19 infections. For the two COVID-19 blood test datasets that were considered, the proposed approach attained an AUC (area under the receiver operating characteristic curve) of 0.99, indicating a high accuracy level in distinguishing between positive and negative samples based on the test results. The study suggests that this approach is a promising solution for detecting COVID-19 infections without labeled data. [ABSTRACT FROM AUTHOR]

In 2020 and 2021, the SARS-CoV-2 coronavirus spread rapidly across the world, causing the COVID-19 pandemic with millions of deaths. One of the measures to protect life was confinement, which negatively affected physical and mental health, especially of the older population. The aim of this study is to present and evaluate the methodological procedures of a telehealth and eHealth program "U3A in Motion", which was composed of videos of physical exercises and activities to promote the mental health and well-being of the older Brazilian population during the COVID-19 pandemic. The procedures included the planning, editing, and dissemination of videos through WhatsApp, and also on the YouTube platform, Instagram, and on a website. A total of 82 videos were created. The action reached 350 older adults from the local community in the northeast of Brazil, as well as being accessed by approximately 3000 other older adults from institutions in the southern region of Brazil. Based on the evaluation of activities through telephone interviews, it was found that older adults participating in the "U3A in Motion" program during confinement were highly motivated to access exercise activities, mainly via mobile phones, and reported a positive effect on physical and mental health. [ABSTRACT FROM AUTHOR]

Since COVID-19 was declared a pandemic, Brazil has become one of the countries most affected by this disease. A year into the pandemic, a second wave of COVID-19 emerged, with a rapid spread of a new SARS-CoV-2 lineage of concern. Several vaccines have been granted emergency-use authorization, leading to a decrease in mortality and severe cases in many countries. However, the emergence of SARS-CoV-2 variants raises the alert for potential new waves of transmission and an increase in pathogenicity. We compared the demographic and clinical data of critically ill patients infected with COVID-19 hospitalized in Rio de Janeiro during the first and second waves between July 2020 and October 2021. In total, 106 participants were included in this study; among them, 88% had at least one comorbidity, and 37% developed severe disease. Disease severity was associated with older age, pre-existing neurological comorbidities, higher viral load, and dyspnea. Laboratory biomarkers related to white blood cells, coagulation, cellular injury, inflammation, renal, and liver injuries were significantly associated with severe COVID-19. During the second wave of the pandemic, the necessity of invasive respiratory support was higher, and more individuals with COVID-19 developed acute hepatitis, suggesting that the progression of the second wave resulted in an increase in severe cases. These results can contribute to understanding the behavior of the COVID-19 pandemic in Brazil and may be helpful in predicting disease severity, which is a pivotal for guiding clinical care, improving patient outcomes, and defining public policies. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, a reduction in vaccination coverage of children and adolescents was observed in several countries. The aim of this study was to assess the impact of the pandemic, in the first two years, on human rotavirus vaccine (HRV) coverage in Brazil compared with previous years. The number of doses of HRV administered in the period from January 2015 to December 2021 and its annual vaccination coverage were analyzed. The vaccination coverage decreased to 77.3% in 2020 and to 70.4% in 2021, substantially lower than the minimum that would be expected (89.2%); the decline was more pronounced in the second year of the pandemic despite the fact that in this period, the circulation restrictions were already less tight. Of the five Brazilian macro-regions, the northeast had the largest decline, and the south had the smallest impact on coverage. At the municipal level, less than half of the Brazilian municipalities managed to achieve vaccination coverage above 90% in either pandemic year. Although there was already a downward trend in coverage in the pre-pandemic years, the present study shows that the values recorded in 2020 and 2021 were significantly lower. Monitoring of vaccination coverage in the coming years should be carried out continuously in order to avoid a possible resurgence of rotavirus-induced diarrhea. [ABSTRACT FROM AUTHOR]

Purpose: To determine the prevalence of SARS-CoV-2 in tear samples and to investigate whether it correlates with ocular findings and patients' prognosis in Brazil. Methods: Tears were collected using Schirmer strips (SS) and conjunctival swabs (CS) from patients hospitalized with laboratory-confirmed SARS-CoV-2 infection. Samples were analyzed using qRT-PCR. Demographic and clinical data, ocular symptoms, and Schirmer tests (ST) were collected from patients. Charlson Comorbidity Index (CCI) was used to rate comorbidities, and patients were monitored until hospital discharge or death. Results: There were 61 hospitalized patients, 33 of which were diagnosed with COVID-19. Within the confirmed COVID-19 patients, SARS-CoV-2 was detected in 18.2% (n = 6) of CS and 12.1% (n = 4) of SS samples. Subjective and objective parameters for dry eye syndrome (e.g., ST COVID-19: 8.3 ± 6.4mm, non-COVID-19: 8.9 ± 6.6mm, p > 0.05) were comparable between COVID-19 (n = 33) and non-COVID-19 patients (n = 28). Among the 16 COVID-19 patients exhibiting ocular symptoms, only tearing was reported significantly more frequently when tear samples were positive for SARS-CoV-2 (p < 0.05). Strikingly, patients whose tears tested positive for SARS-CoV-2 had significantly inferior CCI (pos.: 34.0 ± 31.8%, neg.: 67.6 ± 36.4%, p < 0.05) and higher mortality rates (pos.: 50.0%, neg.: 7.4%, p < 0.01). Conclusions: SARS-CoV-2 was detected with a prevalence of 18.2% on the ocular surface. Decreased CCI and increased mortality rate in the positive tear group suggests that viral detection may relate to prognosis and highlight the need of personal protective measures for healthcare professionals. Most of the patients, regardless of COVID-19 diagnosis, had low tear production and eye discomfort, possibly pointing to the need for artificial tear use during hospitalization. [ABSTRACT FROM AUTHOR]

Background: This study investigated the attitudes and practices of Brazilian adults regarding the mandatory COVID-19 vaccination and their hesitancy towards the vaccination of children. Methods: Between March and May 2022, Brazilian adults answered an online questionnaire distributed through social media. The SAGE-WG questionnaire was adapted to measure hesitancy to the vaccination of children. Results: Of the 1007 participants, 67.4% believed that adult COVID-19 vaccination should be mandatory. Just over half of the participants (51.5%) believed that parents and/or guardians should decide if their children should be vaccinated against COVID-19 or not and 9.1% were unsure. Individuals who were younger, non-religious and had higher awareness of COVID-19 risks and critics of the federal government's performance in combating the pandemic were more likely to agree with mandatory adult vaccination. However, less agreement among parents and/or guardians concerning children's vaccination was observed, with lower scores for hesitancy to the vaccination of children. Conclusion: In Brazil, there is still far from a consensus on mandatory COVID-19 vaccination for adults and a significant proportion of the population believes that parents and/or guardians should be free to decide on their children's vaccination. These views are associated with age, religion, knowledge of COVID-19 risks and political inclination. [ABSTRACT FROM AUTHOR]

Considering the imminence of new SARS-CoV-2 variants and COVID-19 vaccine availability, it is essential to understand the impact of the disease on the most vulnerable groups and those at risk of death from the disease. To this end, the odds ratio (OR) for mortality and hospitalization was calculated for different groups of patients by applying an adjusted logistic regression model based on the following variables of interest: gender, booster vaccination, age group, and comorbidity occurrence. A massive number of data were extracted and compiled from official Brazilian government resources, which include all reported cases of hospitalizations and deaths associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Brazil during the "wave" of the Omicron variant (BA.1 substrain). Males (1.242; 95% CI 1.196–1.290) aged 60–79 (3.348; 95% CI 3.050–3.674) and 80 years or older (5.453; 95% CI 4.966–5.989), and hospitalized patients with comorbidities (1.418; 95% CI 1.355–1.483), were more likely to die. There was a reduction in the risk of death (0.907; 95% CI 0.866–0.951) among patients who had received the third dose of the anti-SARS-CoV-2 vaccine (booster). Additionally, this big data investigation has found statistical evidence that vaccination can support mitigation plans concerning the current scenario of COVID-19 in Brazil since the Omicron variant and its substrains are now prevalent across the entire country. [ABSTRACT FROM AUTHOR]

The crisis that affected Brazil as a result of the coronavirus disease 2019 (COVID-19) pandemic impacted several businesses. However, the distribution of products sold by e-commerce is one business that had increased its demand on a large scale. The Southeastern Region of Brazil has a wide territorial extension, a high number of inhabitants, and difficulties with transport logistics. Thus, this work presents a solution for choosing a location for the installation of an e-commerce warehouse, considering three possible locations, in two different Brazilian states: Rio de Janeiro and Sao Paulo. Our main objective is to identify policies that allow a balance in the trade-off between risks and service levels. Specifically, we seek to decrease logistics costs and ensure improvements in services. The choice of a location for a warehouse is a decision problem that can be solved with multiple criteria decision-making (MCDM). Three methods of MCDM have been applied: Fuzzy Decision Approach (FDA), Multi-Attribute Utility Theory (MAUT), and Multi-Attribute Value Theory (MAVT). The reasons for the application of the MAUT and MAVT methods originate from their easy understanding and use, while the concepts of FDA address the consideration of uncertainty. To maintain the simplicity of MCDM application, the FDA model is symmetric, even with symmetrical and asymmetrical fuzzy sets. Important criteria were the distance from capital cities, distance to ports, distance to airports, distance to highways, and the costs of land. Three different locations were considered for the installation of the warehouse. All three methods, FDA, MAUT, and MAVT, resulted in Location 1 as the best location for the installation of the warehouse for the distribution of e-commerce products. A discussion on conceptual qualitative divergences and the small quantitative divergence of results is also included in the conclusions. [ABSTRACT FROM AUTHOR]

Limitations in the use of public spaces have impacted the frequency and duration of movement behaviours (physical activity, sedentary behaviour, sleep) and outdoor activities of children and adolescents. Whether pandemic-induced changes in movement behaviours are related to the health-related quality of life (HRQoL) of children and adolescents is unknown. The aim of the current study was to examine the association between meeting 24 h movement guidelines and HRQoL during the COVID-19 lockdown among children and adolescents. Data from 1099 3–17-year-old children and adolescents from Spain and Brazil were analysed. An online questionnaire was used to collect parent-reported information concerning physical activity, screen time, and sleep duration. For the assessment of HRQoL, the EQ-5D-Y proxy version was used. The highest prevalence of reported problems was related to the 'worries/sadness/unhappiness' factor, where 36.3% of participants declared to have at least 'some problems'. Participants meeting the 24 h guidelines had a higher HRQoL score compared with those who did not (91.9 ± 2.5 vs. 84.3 ± 0.5, respectively; p < 0.05). The current study shows that children and adolescents that met 24 h movement guidelines presented a higher HRQoL during the COVID-19 lockdown, providing support for the promotion of healthy movement behaviours—especially during a pandemic. [ABSTRACT FROM AUTHOR]

COVID-19 has brought several harmful consequences to the world from many perspectives, including social, economic, and well-being in addition to health issues. However, these harmful consequences vary in intensity in different regions. Identifying which cities are most vulnerable to COVID-19 and understanding which variables could be associated with the advance of registered cases is a challenge. Therefore, this study explores and builds a spatial decision model to identify the characteristics of the cities that are most vulnerable to COVID-19, taking into account social, economic, demographic, and territorial aspects. Hence, 18 features were separated into the four groups mentioned. We employed a model joining the dominance-based rough set approach to aggregate the features (multiple criteria) and spatial analysis (Moran index, and Getis and Ord) to obtain final results. The results show that the most vulnerable places have characteristics with high population density and poor economic conditions. In addition, we conducted subsequent analysis to validate the results. The case was developed in the northeast region of Brazil. [ABSTRACT FROM AUTHOR]

Several variants of SARS-CoV-2 have been identified in different parts of the world, including Gamma, detected in Brazil, Delta, detected in India, and the recent Omicron variant, detected in South Africa. The emergence of a new variant is a cause of great concern. This work considers an extended version of an SIRD model capable of incorporating the effects of vaccination, time-dependent transmissibility rates, mortality, and even potential reinfections during the pandemic. We use this model to characterise the Omicron wave in Brazil, South Africa, and Germany. During Omicron, the transmissibility increased by five for Brazil and Germany and eight for South Africa, whereas the estimated mortality was reduced by three-fold. We estimated that the reported cases accounted for less than 25 % of the actual cases during Omicron. The mortality among the nonvaccinated population in these countries is, on average, three to four times higher than the mortality among the fully vaccinated. Finally, we could only reproduce the observed dynamics after introducing a new parameter that accounts for the percentage of the population that can be reinfected. Reinfection was as high as 40 % in South Africa, which has only 29 % of its population fully vaccinated and as low as 13 % in Brazil, which has over 70 % and 80 % of its population fully vaccinated and with at least one dose, respectively. The calibrated models were able to estimate essential features of the complex virus and vaccination dynamics and stand as valuable tools for quantifying the impact of protocols and decisions in different populations. [ABSTRACT FROM AUTHOR]

Public health interventions to counter the COVID-19 pandemic have accelerated and increased digital adoption and use of the Internet for sourcing health information. Unfortunately, there is evidence to suggest that it has also accelerated and increased the spread of false information relating to COVID-19. The consequences of misinformation, disinformation and misinterpretation of health information can interfere with attempts to curb the virus, delay or result in failure to seek or continue legitimate medical treatment and adherence to vaccination, as well as interfere with sound public health policy and attempts to disseminate public health messages. While there is a significant body of literature, datasets and tools to support countermeasures against the spread of false information online in resource-rich languages such as English and Chinese, there are few such resources to support Portuguese, and Brazilian Portuguese specifically. In this study, we explore the use of machine learning and deep learning techniques to identify fake news in online communications in the Brazilian Portuguese language relating to the COVID-19 pandemic. We build a dataset of 11,382 items comprising data from January 2020 to February 2021. Exploratory data analysis suggests that fake news about the COVID-19 vaccine was prevalent in Brazil, much of it related to government communications. To mitigate the adverse impact of fake news, we analyse the impact of machine learning to detect fake news based on stop words in communications. The results suggest that stop words improve the performance of the models when keeping them within the message. Random Forest was the machine learning model with the best results, achieving 97.91% of precision, while Bi-GRU was the best deep learning model with an F1 score of 94.03%. [ABSTRACT FROM AUTHOR]

Underreporting of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is a global problem and might hamper Coronavirus Disease (COVID-19) epidemiological control. Taking this into consideration, we estimated possible SARS-CoV-2 infection underreporting in Brazil among patients with severe acute respiratory syndrome (SARS). An ecological study using a descriptive analysis of the SARS report was carried out based on data supplied by the Influenza Epidemiological Surveillance Information (SIVEP)-Flu (in Brazilian Portuguese, Sistema de Vigilância Epidemiológica da Gripe) in the period between January 2015 and March 2021. The number of SARS cases and related deaths after infection by SARS-CoV-2 or Influenzae was described. The estimation of underreporting was evaluated considering the relative increase in the number of cases with undefined etiological agent comparing 2020 to 2015–2019; and descriptive analysis was carried out including data from January–March/2021. In our data, SARS-CoV-2 infection and the presence of SARS with undefined etiological agent were associated with the higher number of cases and deaths from SARS in 2020/2021. SARS upsurge was six times over that expected in 2020, according to SARS seasonality in previous years (2015–2019). The lowest possible underdiagnosis rate was observed in the age group < 2 y.o. and individuals over 30 y.o., with ~50%; while in the age groups 10–19 and 20–29 y.o., the rates were 200–250% and 100%, respectively. For the remaining age groups (2–5 and 5–9 y.o.) underreporting was over 550%, except for female individuals in the age group 2–5 y.o., in which a ~500% rate was found. Our study described that the SARS-CoV-2 infection underreporting rate in Brazil in SARS patients is alarming and presents different indices, mainly associated with the patients' age groups. Our results, mainly the underreporting index according to sex and age, should be evaluated with caution. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 infection has received the attention of the scientific community due to its respiratory manifestations and association with evolution to severe acute respiratory syndrome (SARS-CoV-2). There are few studies characterizing SARS-CoV-2 in pediatric immunocompromised patients, such as liver transplanted patients. The aim of this study was to analyze the outcomes of the largest cohort of pediatric liver transplant recipients (PLTR) from a single center in Brazil who were infected with COVID-19 during the pandemic. Methods: Cross-sectional study. Primary outcomes: COVID-19 severity. The Cox regression method was used to determine independent predictors associated with the outcomes. Patients were divided into two groups according to the severity of COVID-19 disease: moderate–severe COVID and asymptomatic–mild COVID. Results: Patients categorized as having moderate–severe COVID-19 were younger (12.6 months vs. 82.1 months, p = 0.03), had a higher prevalence of transplantation from a deceased donor (50% vs. 4.3%, p = 0.02), and had a higher prevalence of COVID infection within 6 months after liver transplantation (LT) (75% vs. 5.7%, p = 0.002). The independent predictor of COVID-19 severity identified in the multivariate analysis was COVID-19 infection <6 months after LT (HR = 0.001, 95% CI = 0.001–0.67, p = 0.03). Conclusion: The time interval of less than 6 months between COVID-19 infection and LT was the only predictor of disease severity in pediatric patients who underwent liver transplantation. [ABSTRACT FROM AUTHOR]

New variants of SARS-CoV-2 are a major source of concern, especially for pregnant women and in the perinatal context. The primary aim of this study was to compare the severity of COVID-19 infection in pregnant women depending on strain predominance between wild-type Alpha and Gamma variants. The secondary aim was to study the impact of these strains on obstetrical and neonatal outcomes. We conducted a two-center international retrospective cohort study, which included two type III maternity hospitals, one in France and one in Brazil, comparing the first period corresponding to the wild-type strain and the second period corresponding to the predominance of the Alpha variant in France and the Gamma variant in Brazil. We included 151 pregnant women with symptomatic SARS-CoV-2 infection confirmed by RT-PCR. The rate of severe-to-critical infection, according to the WHO definition, was seven-fold higher in patients infected during the "variant period" than in patients infected during the "wild-type period" (aOR = 7.07, 95CI [2.50–21.6], p < 0.001). There were no statistical differences concerning composite obstetrical and neonatal outcomes between the different periods. While analyzing each variant separately, it was found that, in France, the risk of developing a severe-to-critical infection was three times greater during the Alpha period than during the wild-type period (OR = 3.25, 95CI [0.70–15.6], p = 0.13) and, in Brazil, the risk was twelve times greater during the Gamma period than during the wild-type period (OR = 11.8, 95CI [2.46–72.3], p = 0.003). The Alpha and Gamma variants of SARS-CoV-2 seem to be more dangerous in the obstetrical context. With the rapid emergence of new variants, it is necessary to accelerate vaccination to protect women and newborn children. [ABSTRACT FROM AUTHOR]

Genetic factors associated with COVID-19 disease outcomes are poorly understood. This study aimed to associate genetic variants in the SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, and ABO genes with the risk of severe forms of COVID-19 in Amazonian Native Americans, and to compare the frequencies with continental populations. The study population was composed of 64 Amerindians from the Amazon region of northern Brazil. The difference in frequencies between the populations was analyzed using Fisher's exact test, and the results were significant when p ≤ 0.05. We investigated 64 polymorphisms in 7 genes; we studied 47 genetic variants that were new or had impact predictions of high, moderate, or modifier. We identified 15 polymorphisms with moderate impact prediction in 4 genes (ABO, CXCR6, FYCO1, and SLC6A20). Among the variants analyzed, 18 showed significant differences in allele frequency in the NAM population when compared to others. We reported two new genetic variants with modifier impact in the Amazonian population that could be studied to validate the possible associations with COVID-19 outcomes. The genomic profile of Amazonian Native Americans may be associated with protection from severe forms of COVID-19. This work provides genomic data that may help forthcoming studies to improve COVID-19 outcomes. [ABSTRACT FROM AUTHOR]

This article, which integrates broader research, aims to identify the fake news patterns propagated in the process of disinformation about COVID-19 that were evaluated by the Brazilian fact-checking agencies Fato or Fake and Lupa. Aiming at this goal, we considered the strategies for spreading false information about the disease from January to September 2020. As a methodology, we used part of the procedures associated with media framing, focusing on the themes and labels of the checked information. Politics and death were the two main issues in misinformation assessed by the agencies, closely followed by themes related to cure and prevention. Personalities were particularly relevant at Lupa. The high frequency of the political issue reveals the ideological polarization that Brazil is experiencing, leading to global health crises such as the new coronavirus pandemic. [ABSTRACT FROM AUTHOR]