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Brazil counts among the countries the hardest hit by the Covid-19 pandemic. A great deal has been said about the negative role played by President Bolsonaro's denialism, but relatively few studies have attempted to measure precisely what impact it actually had on the pandemic. Our paper conducts econometric estimates based on observational data at municipal level to quantitatively assess the 'Bolsonaro effect' over time from March 2020 to December 2022. To our knowledge, this paper presents the most comprehensive investigation of Bolsonaro's influence in the spread of the pandemic from two angles: considering Covid-19 mortality and two key transmission mitigation channels (social distancing and vaccination); and exploring the full pandemic cycle (2020–2022) and its dynamics over time. Controlling for a rich set of relevant variables, our results find a strong and persistent 'Bolsonaro effect' on the death rate: municipalities that were more pro-Bolsonaro recorded significantly more fatalities. Furthermore, evidence suggests that the president's attitude and decisions negatively influenced the population's behaviour. Firstly, pro-Bolsonaro municipalities presented a lower level of compliance with social distancing measures. Secondly, vaccination was relatively less widespread in places more in favour of the former president. Finally, our analysis points to longer-lasting and damaging repercussions. Regression results are consistent with the hypothesis that the 'Bolsonaro effect' impacted not only on Covid-19 vaccination, but has affected vaccination campaigns in general thereby jeopardizing the historical success of the National Immunization Program in Brazil. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic in Brazil has brought many challenges, particularly regarding the management of hospital capacity, and a new demand for healthcare that added to the preexisting demands, such as neoplasms, cardiovascular diseases and births. In this paper, we estimate the impact of the pandemic on the number of deaths and hospitalizations for other diseases. We construct a monthly panel data of deaths and hospitalizations for various causes by the municipality of residence and relate them to COVID-19 hospitalizations using regression models that control for municipalities fixed-effects and interactions between State and month fixed-effects. The standard errors are clustered at the municipality level. Our estimates imply that 100 more hospitalizations by COVID-19 is associated with a drop of 49 non-COVID-19 hospitalizations and an additional four deaths for other reasons (all measured per 100,000 pop.). The impact of intensive care units COVID-19 hospitalizations on mortality is larger. The groups most affected are the African Brazilians, less-educated and the elderly. Additional deaths occurred both at households and at hospitals. The main causes of additional deaths were diseases related to the circulatory and endocrine system. The decline in hospitalizations for other causes seems to be related to the overcrowding of hospitals in periods of surge in the COVID-19, alongside with the fall in the demand for care by the citizens who were afraid of COVID-19 infection. These mechanisms affected more strongly the vulnerable groups of the population. Our results highlight the importance of promoting the awareness of heightened risk of non-communicable chronic diseases during a health emergency context. This should be done preferably through already established channels with community outreach, such as the Family Health Program in Brazil. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has led to there being a worldwide socio-economic crisis, with major impacts on developing countries. Understanding the dynamics of the disease and its driving factors, on a small spatial scale, might support strategies to control infections. This paper explores the impact of the COVID-19 on neighborhoods of Recife, Brazil, for which we examine a set of drivers that combines socio-economic factors and the presence of non-stop services. A three-stage methodology was conducted by conducting a statistical and spatial analysis, including clusters and regression models. COVID-19 data were investigated concerning ten dates between April and July 2020. Hotspots of the most affected regions and their determinant effects were highlighted. We have identified that clusters of confirmed cases were carried from a well-developed neighborhood to socially deprived areas, along with the emergence of hotspots of the case-fatality rate. The influence of age-groups, income, level of education, and the access to essential services on the spread of COVID-19 was also verified. The recognition of variables that influence the spatial spread of the disease becomes vital for pinpointing the most vulnerable areas. Consequently, specific prevention actions can be developed for these places, especially in heterogeneous cities. [ABSTRACT FROM AUTHOR]

In this paper, we provide a retrospective cohort study with patients that have been hospitalized for general or intensive care unit admission due to COVID-19, between March 3 and July 29, 2020, in the state of Bahia, Brazil. We aim to correlate those patients' demographics, symptoms and comorbidities, with the risk of mortality from COVID-19, length of hospital stay, and time from diagnosis to definitive outcome. On the basis of a dataset provided by the Health Secretary of the State of Bahia, we selected 3,896 hospitalized patients from a total of 154,868 COVID-19 patients that included non-hospitalized patients and patients with invalid registration in the dataset. Then, we statistically analyzed whether there was a significant correlation between the patient record data and the COVID-19 pandemic, and our main findings reinforced by the use of a multivariable logistic regression were that older age (Odds Ratio [OR] = 1.03, 95% Confidence Interval [CI] = 1.03-1.04, p-value (p) <0.001), an initial symptom of shortness of breath (OR = 1.88, 95% CI = 1.60-2.20, p < 0.001), and the presence of comorbidities, mainly chronic kidney disease (OR = 2.41, 95% CI = 1.67-3.48, p < 0.001) are related to an increased risk of mortality from COVID-19. On the other hand, sore throat (OR = 0.74, 95% CI = 0.58-0.95, p = 0.02) and length of hospital stay (OR = 0.96, 95% CI = 0.58-0.95, p < 0.001) are more related to a reduced risk of mortality from COVID-19. Moreover, a multivariable linear regression conducted with statistically significant variables (p < 0.05) showed that age (OR = 0.97, 95% CI = 0.95-0.98, p < 0.001) and time from diagnosis to definitive outcome (OR = 1.67, 95% CI = 1.64-1.71, p < 0.001) are associated with the length of hospital stay. [ABSTRACT FROM AUTHOR]

Aim: To test the association between sociodemographic and social characteristics with COVID-19 cases and deaths in small and large Brazilian cities. Methods: This ecological study included COVID-19 data available in State Health Secretaries (managed by brasil.io API) and three national databases (IBGE, DATASUS and Embrapa). Temporal spread of COVID-19 in Brazil during the first year considered as outcome: a) days until 1st case in each city since 1st in the country; b) days until 1,000 cases/100,000 inhabitants since 1st case in each city; c) days until 1st death until 50 deaths/100,000 inhabitants. Covariates included geographic region, city social and environmental characteristics, housing conditions, job characteristics, socioeconomic and inequalities characteristics, and health services and coverage. The analysis were stratified by city size into small (<100,000 inhabitants) and large cities (≥100,00 inhabitants). Multiple linear regressions were performed to test associations of all covariates to adjust to potential confounders. Results: In small cities, the first cases were reported after 82.2 days and 1,000 cases/100,000 were reported after 117.8 days, whereas in large cities these milestones were reported after 32.1 and 127.7 days, respectively. For first death, small and large cities took 121.6 and 36.0 days, respectively. However, small cities were associated with more vulnerability factors to first case arrival in 1,000 cases/100,000 inhabitants, first death and 50 deaths/100,000 inhabitants. North and Northeast regions positively associated with faster COVID-19 incidence, whereas South and Southeast were least. Conclusion: Social and built environment characteristics and inequalities were associated with COVID-19 cases spread and mortality incidence in Brazilian cities. [ABSTRACT FROM AUTHOR]

The present study aims to analyze the trends in food price in Brazil with emphasis on the period of the Covid-19 pandemic (from March 2020 to March 2022). Data from the Brazilian Household Budget Survey and the National System of Consumer Price Indexes were used as input to create a novel data set containing monthly prices (R$/Kg) for the foods and beverages most consumed in the country between January 2018 and March 2022. All food items were divided according to the Nova food classification system. We estimated the mean price of each food group for each year of study and the entire period. The monthly price of each group was plotted to analyze changes from January 2018 to March 2022. Fractional polynomial models were used to synthesize price changes up to 2025. Results of the present study showed that in Brazil unprocessed or minimally processed foods and processed culinary ingredients were more affordable than processed and ultra-processed foods. However, trend analyses suggested the reversal of the pricing pattern. The anticipated changes in the prices of minimally processed food relative to ultra-processed food, initially forecasted for Brazil, seem to reflect the impact of the Covid-19 pandemic on the global economy. These results are concerning as the increase in the price of healthy foods aggravates food and nutrition insecurity in Brazil. Additionally, this trend encourages the replacement of traditional meals for the consumption of unhealthy foods, increasing a health risk to the population. [ABSTRACT FROM AUTHOR]

Background: Accurate estimates of the COVID-19 pandemic's indirect impacts are crucial, especially in low- and middle-income countries. This study aims to update estimates of excess maternal deaths in Brazil during the first two years of the COVID-19 pandemic. Methods: This was an exploratory mixed ecological study using the counterfactual approach. The observed maternal deaths were gathered from the Mortality Information System (SIM) for the period between March 2015 and February 2022. Expected deaths from March 2020 to February 2022 were estimated using quasipoisson generalized additive models, considering quadrimester, age group, and their interaction as predictor variables. Analyses were performed in R version 4.1.2, RStudio, version 2023.03.1+446 and carried out with support from the "mgcv" and "plot_model" libraries. Results: A total of 5,040 maternal deaths were reported, with varying excess mortality across regions and age groups, resulting in 69% excess maternal mortality throughout Brazil during the first two years of the pandemic. The Southeast region had 50% excess mortality throughout the first two years and 76% excess in the second year. The North region had 69% excess mortality, increasing in the second year, particularly among women aged 20–34. The Northeast region showed 80% excess mortality, with a significant increase in the second year, especially among women aged 35–49. The Central-West region had 75% excess mortality, higher in the second year and statistically significant among women aged 35–49. The South region showed 117% excess mortality, reaching 203% in the second year among women aged 20–34, but no excess mortality in the 10–19 age category. Conclusions: Over two years, Brazil saw a significant impact on maternal excess deaths, regardless of region and pandemic year. The highest peak occurred between March and June 2021, emphasizing the importance of timely and effective epidemic responses to prevent avoidable deaths and prepare for new crises. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has had a negative impact on socioeconomic and public health conditions of the population. Aim: To measure the temporal evolution of COVID-19 cases in cities near the countryside outside metropolitan areas of northeastern Brazil and the impact of the primary care organization in its containment. Methods: This is a time-series study, based on the first three months of COVID-19 incidence in northeastern Brazil. Secondary data were used, the outcome was number of COVID-19 cases. Independent variables were time, coverage and quality score of basic health services, and demographic, socioeconomic and social isolation variables. Generalizable Linear Models with first order autoregression were applied. Results: COVID-19 spreads heterogeneously in cities near the countryside of Northeastern Brazilian cities, showing associations with the city size, socioeconomic and organizational indicators of services. The Family Health Strategy seems to mitigate the speed of progression and burden of the disease, in addition to measures such as social isolation and closure of commercial activities. Conclusion: The spread of COVID-19 reveals multiple related factors, which require coordinated intersectoral actions in order to mitigate its problems, especially in biologically and socially vulnerable populations. [ABSTRACT FROM AUTHOR]

Background: The emergence of SARS-CoV-2 variants led to subsequent waves of COVID-19 worldwide. In many countries, the second wave of COVID-19 was marked by record deaths, raising the concern that variants associated with that wave might be more deadly. Our aim was to compare outcomes of critically-ill patients of the first two waves of COVID-19. Methods: This retrospective cohort included critically-ill patients admitted between March-June 2020 and April-July 2021 in the largest academic hospital in Brazil, which has free-access universal health care system. We compared admission characteristics and hospital outcomes. The main outcome was 60‐day survival and we built multivariable Cox model based on a conceptual causal diagram in the format of directed acyclic graph (DAG). Results: We included 1583 patients (1315 in the first and 268 in the second wave). Patients in the second wave were younger, had lower severity scores, used prone and non-invasive ventilatory support more often, and fewer patients required mechanical ventilation (70% vs 80%, p<0.001), vasopressors (60 vs 74%, p<0.001), and dialysis (22% vs 37%, p<0.001). Survival was higher in the second wave (HR 0.61, 95%CI 0.50–0.76). In the multivariable model, admission during the second wave, adjusted for age, SAPS3 and vaccination, was not associated with survival (aHR 0.85, 95%CI 0.65–1.12). Conclusions: In this cohort study, patients with COVID-19 admitted to the ICU in the second wave were younger and had better prognostic scores. Adjusted survival was similar in the two waves, contrasting with record number of hospitalizations, daily deaths and health system collapse seen across the country in the second wave. Our findings suggest that the combination of the burden of severe cases and factors such as resource allocation and health disparities may have had an impact in the excess mortality found in many countries in the second wave. [ABSTRACT FROM AUTHOR]

Since the first case of COVID-19, Brazil has undergone infection waves with distinct characteristics. The description of new variants has alerted the emergence of more contagious or virulent viruses. The variant of concern Gamma emerged in Brazil and caused an epidemic wave, but its spread outside the country was limited. We report the clinical-epidemiological profile of hospitalized patients with COVID-19 by comparing two periods. A retrospective cohort study was performed. The primary outcome was to assess individuals with COVID-19 admitted in wards and intensive care units at the academic hospital of the Federal University of Parana (CHC-UFPR) between March 2020 and July 2021, correlating demographic, clinical-epidemiologic, and survival data with the most prevalent viral variant found in each period. We used Kaplan-Meier analysis to estimate the probability of survival and ROC curves to evaluate laboratory tests to find a cutoff point for poor outcomes. Data from 2,887 individuals were analyzed, 1,495 and 1,392 from the first and second periods, respectively. Hospitalization predominated among males in both periods, and the median age was significantly lower in the second one. The frequency of comorbidities was similar. Various demographic factors, clinical assessments, and laboratory tests were examined in relation to greater severity. When comparing the two periods, we observed predominance of the Wild virus during the first wave and the Gamma variant during the second, with no significant difference in outcomes. The findings suggest that despite the association of many factors with increased severity, the temporal variation between the two periods did not result in a notable divergence in the measured outcomes. The COVID-19 pandemic has lasted for a long time, with periods marked by peaks of cases, often caused by the emergence of viral variants, resulting in higher infection rates and rapid dissemination but, for variant Gamma, no apparent greater virulence. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze levels of fatigue and resilience of Brazilian graduate students during the COVID-19 pandemic and to determine whether there is an association between fatigue and resilience and sociodemographic and academic factors. Data were analyzed using descriptive and inferential statistics, and it was discovered that the variables associated with higher levels of resilience were age; having children; being retired; receiving income above five minimum wages; having had greater problems in other phases of the research schedule; coming from private universities; being from the north of Brazil; studying the area of Health; and having their research schedule unaffected during the pandemic. On the other hand, lack of resilience was associated with not having children; being less well-off financially; being younger; being a woman; studying in a public university; and having to postpone part of the research during the pandemic. The conclusion of the study indicated the need for graduate programs to design strategies to deal with fatigue and promote resilience in Master's and PhD students. [ABSTRACT FROM AUTHOR]

Modeling time series has been a particularly challenging aspect due to the need for constant adjustments in a rapidly changing environment, data uncertainty, dependencies between variables, volatile fluctuations, and the need to identify ideal hyperparameters. The present study presents a Framework capable of making projections from time series related to cases and deaths by COVID-19 in the Amazonian state of Pará, in Brazil. For the first time, deep learning models such as TCN, TRANSFORMER, TFT, N-BEATS, and N-HiTS were assessed for this purpose. The ARIMA statistical model was also used in post-processing for residual adjustment and short-term smoothing of the generated forecasts. The Framework generates probabilistic forecasts, with multivariate support, considering the following variables: daily cases per day of the first symptom, cases published daily, the occurrence of deaths, deaths published daily, and percentage of daily vaccination. The generated predictions are statistically evaluated by determining the best model for 7-day moving average projections using evaluating metrics such as MSE, RMSE, MAPE, sMAPE, r2, Coefficient of Variation, and residual analysis. As a result, the generated projections showed an average error of 5.4% for Cases Publication, 8.0% for Cases Symptoms, 11.12% for Deaths Publication, and 4.6% for Deaths Occurrence, with the N-HiTS and N-BEATS models obtaining better results. In general terms, the use of deep learning models to predict cases and deaths from COVID-19 has proven to be a valuable practice for analyzing the spread of the virus, which allows health managers to better understand and respond to this kind of pandemic outbreak. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation (AF) is a major risk factor for stroke. To enable improvements to AF diagnosis and follow-up care, understanding current patient pathways and barriers to optimal care are essential. We investigated the patient care pathways and their drivers, and the impact of the COVID-19 pandemic on patient pathways in a middle-income country setting, Brazil. Methods: This mixed-methods study in São Paulo, included adults (≥18y) with AF from 13 primary/secondary healthcare facilities. Surveys using baseline, follow-up (administered ≥two months after baseline) and COVID-19 questionnaires (quantitative), and three focus group discussions (FGDs) were conducted. Minimum sample size for the quantitative component was 236 and we aimed to reach saturation with at least three FGDs for the qualitative component. Descriptive statistics were used for quantitative data and a content analysis was used for qualitative data to identify themes related to AF diagnosis and follow-up care. Results: 267 participants completed the baseline questionnaire: 25% were diagnosed in primary care, 65% in an emergency or inpatient department. At follow-up (n = 259), 31% visited more than one facility for AF care, and 7% had no follow-up. Intervals between international normalised ratio (INR) tests were increased during the pandemic, and the number of healthcare visits and availability of medication were reduced. Seventeen patients participated in three FGDs and revealed that AF diagnosis often occurred following a medical emergency and patients often delay care-seeking due to misconceptions about AF symptoms. Long waiting times, doctor/patient interactions and health system factors, such as doctor availability and the referral system, influence where participants visited for follow-up care. Conclusions: Lack of public awareness and underdeveloped primary healthcare lead to delayed diagnosis, which impacts clinical outcomes and excess patient and healthcare system costs. Health system, care-provider, and pandemic factors disrupt timely and effective continuity of care. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the primary health care (PHC) attributes and associated factors during the COVID-19 pandemic using the perspective of users. Methods: This cross-sectional, quantitative study included 422 PHC users from 96 Family Health Teams in a city in Brazil. The assessment used the Primary Care Assessment Tool (PCATool) and a structured questionnaire on the sociodemographic and epidemiological characteristics of users and basic health units (BHU). The Person's chi-square test was used to analyze the association between high overall scores in PCATool and characteristics of users and BHU. Crude and adjusted prevalence ratios (PR) with a 95% confidence interval were also calculated. Poisson regression and Rao Scott's Chi-square test were used to estimate crude PR. Results: Most users were aged 30 to 39 years (26.3%), women (75.4%), registered at the BHU for over ten years (59.5%), and had incomplete secondary education (30.6%). The mean of PHC essential attributes and overall scores were low (6.10 ± 0.81 and 5.78 ± 0.77, respectively). "First-contact care–use" received the highest score (9.22 ± 1.62), while "first-contact care–accessibility" received the lowest (2.82 ± 0.90). High overall scores were associated with an average employment time of professionals (doctors and nurses) at the BHU (PR = 1.31; 95% CI 1.17–1.48; p < 0.001) and lower educational level of users (PR = 1.71; 95% CI 1.54–1.90; p < 0.001. Conclusion: "First-contact care–use" was the best evaluated, while "first-contact care–accessibility" was the worst. High scores were associated with a lower educational level of users and BHU with more experienced professionals. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic in Brazil affected mental health among healthcare workers. To objective of this study was to evaluate the mental health of healthcare workers in in the central-west region of the Brazil, estimating the prevalence of mental health disorders, and investigating associated factors, perceptions of safety, and self-perceptions about mental health in times of the COVID-19 pandemic. The questionnaire was divided into two parts that included general information and perceptions about the work process and identified symptoms using the Depression Anxiety Stress Scale-21 (DASS-21), and multiple linear regression analysis was conducted. A total of 1,522 healthcare workers participated in the survey. Overall prevalence of symptoms was calculated for depression (58.7%), anxiety (59.7%), and stress (61.7%). Physicians had 3.75 times greater risk of depression (1.59–8.85, 95% CI). Independent variables associated with depression symptoms were not feeling safe with the way services were organized (1.12:1.03–1.21, 95% CI) and self-perception of poor mental health (8.06: 4.03–16.10% CI). Working in management was protective, and married professionals had 12% lower risk of exhibiting symptoms of depression (0.79–0.99, 95% CI). Participants with self-perception of poor mental health had 4.63 greater risk for symptoms of anxiety (2.58–8.31, 95% CI). Protective factors were not having sought support for mental health (0.90: 0.82–0.99, 95% CI), having a graduate degree (0.71: 0.54–0.94, 95% CI), and not having been diagnosed with COVID-19 (0.90: 0.83–0.98, 95% CI). Perception of poor mental health was associated with 6.95-fold greater chance of developing stress symptoms. Protective factors from stress were having a degree in dentistry (0.81: 0.68–0.97, 95% CI), residing in Mato Grosso do Sul (0.91: 0.85–0.98, 95% CI), and not having sought mental health support services (0.88: 0.82–0.95, 95% CI). The prevalence of mental health disorders is high among healthcare workers, and is associated with professional category, organization of services provided, and self-perception of poor mental health, reinforcing the need for preventative measures. [ABSTRACT FROM AUTHOR]

We estimated the impact of the COVID-19 pandemic on mortality in Brazil for 2020 and 2021 years. We used mortality data (2015–2021) from the Brazilian Health Ministry for forecasting baseline deaths under non-pandemic conditions and to estimate all-cause excess deaths at the country level and stratified by sex, age, ethnicity and region of residence, from March 2020 to December 2021. We also considered the estimation of excess deaths due to specific causes. The estimated all-cause excess deaths were 187 842 (95% PI: 164 122; 211 562, P-Score = 16.1%) for weeks 10-53, 2020, and 441 048 (95% PI: 411 740; 470 356, P-Score = 31.9%) for weeks 1-52, 2021. P-Score values ranged from 1.4% (RS, South) to 38.1% (AM, North) in 2020 and from 21.2% (AL and BA, Northeast) to 66.1% (RO, North) in 2021. Differences among men (18.4%) and women (13.4%) appeared in 2020 only, and the P-Score values were about 30% for both sexes in 2021. Except for youngsters (< 20 years old), all adult age groups were badly hit, especially those from 40 to 79 years old. In 2020, the Indigenous, Black and East Asian descendants had the highest P-Score (26.2 to 28.6%). In 2021, Black (34.7%) and East Asian descendants (42.5%) suffered the greatest impact. The pandemic impact had enormous regional heterogeneity and substantial differences according to socio-demographic factors, mainly during the first wave, showing that some population strata benefited from the social distancing measures when they could adhere to them. In the second wave, the burden was very high for all but extremely high for some, highlighting that our society must tackle the health inequalities experienced by groups of different socio-demographic statuses. [ABSTRACT FROM AUTHOR]

Trust in institutions is a key driver to shape population attitudes and behavior, such as compliance of non-pharmaceutical interventions (NPI). During the COVID-19 pandemic, this was fundamental and its compliance was supported by governmental and non-governmental institutions. Nevertheless, the situation of political polarization in some countries with decentralized health systems increased the difficulty of such interventions. This study analyzes the association between non-pharmaceutical interventions' compliance and individual perception regarding institutions' performance during the COVID-19 pandemic in Brazil. A web survey was conducted in Brazil between November 2020 and February 2021. Bivariate analysis and ordered logit regressions were performed to assess the association between NPIs compliance and perceived institutions' performance. Results suggest a negative association between NPIs' compliance and Federal Government and Ministry of health perceived performance, which may reflect the political positioning of the respondents. Moreover, we find a positive association between NPI compliance and the perceived performance of the remaining institutions (state government, federal supreme court, national congress, WHO, media and SUS). Our contribution goes beyond the study of a relationship between non-pharmaceutical interventions' compliance and institutions' performance, by pointing out the importance of subnational and local governmental spheres in a decentralized health system, as well as highlighting the importance of social communication based on health organizations' information and scientific institutions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has impacted public and private health systems around the world, impairing good practices in women's health care. However, little is known about the experiences, knowledge, and feelings of Brazilian women in this period. The objective was to analyze the experiences of women, seen at maternity hospitals accredited by the Brazilian Unified Health System (SUS, acronym in Portuguese), regarding health care during pregnancy, childbirth, and postpartum periods, their interpersonal relationships, and perceptions and feelings about the pandemic. This was a qualitative, exploratory research, carried out in three Brazilian municipalities with women hospitalized in 2020, during pregnancy, childbirth, or postpartum period, with COVID-19 or not. For data collection, semi-structured individual interviews (in person, by telephone, or by digital platform) were conducted, recorded and transcribed. The content analysis of thematic modalities was displayed as per the following axes: i) Knowledge about the disease; ii) Search for health care in prenatal, childbirth, and postpartum periods; iii) Experience of suffering from COVID-19; iv) Income and work; and v) Family dynamics and social support network. A total of 46 women were interviewed in São Luís-MA, Pelotas-RS, and Niterói-RJ. Use of media was important to convey information and fight fake news. The pandemic negatively impacted access to health care in the prenatal, childbirth, and postpartum periods, contributing to worsening of the population's social and economic vulnerabilities. Women experienced diverse manifestations of the disease, and psychic disorders were very frequent. Social isolation during the pandemic disrupted the support network of these women, who found social support strategies in communication technologies. Women-centered care–including qualified listening and mental health support–can reduce the severity of COVID-19 cases in pregnant, parturient, and postpartum women. Sustainable employment and income maintenance policies are essential to mitigate social vulnerabilities and reduce risks for these women. [ABSTRACT FROM AUTHOR]

What are the effects of right-wing populism in the struggle against COVID-19? We explore data from Brazil, a country whose populist radical right-wing president was among the prominent denialists regarding the effects of the pandemic. Using cross-sectional and weekly-panel data for 5,570 municipalities during 2020, we present evidence that social distancing was weakened, and the number of cases and deaths were higher in places where the president had received greater electoral support during the 2018 presidential elections. Placebo tests using traditional right-wing vote and data on Severe Acute Respiratory Syndrome (SARS) before the pandemic outbreak indicate that the former does not correlate with health outcomes, and the populist share of the vote does not correlate with the latter. Hence, we find strong indications that right-wing populism relates to a poor response to the disease. [ABSTRACT FROM AUTHOR]

Background: Knowledge about the epidemiology and risk factors surrounding COVID-19 contributes to developing better health strategies to combat the disease. Objective: This study aimed to establish a survival analysis and identify the risk factors for patients with COVID-19 in an upper middle-income city in Brazil. Methods: A retrospective cohort study was conducted with 280 hospitalized patients with COVID-19. The eCOVID platform provided data to monitor COVID-19 cases and help the communication between professionals. Results: Age ≥ 65 years was associated with decreased survival (54.8%), and females had a lower survival rate than males (p = 0.01). Regarding risk factors, urea concentration (p<0.001), hospital length of stay (p = 0.002), oxygen concentration (p = 0.005), and age (p = 0.02) were associated with death. Conclusion: Age, hospital length of stay, high blood urea concentration, and low oxygen concentration were associated with death by COVID-19 in the studied population. These findings corroborate with studies conducted in research centers worldwide. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic was severely aggravated in Brazil due to its politicization by the country's federal government. However, the impact of diffuse political forces on the fatality of an epidemic is notoriously difficult to quantify. Here we introduce a method to measure this effect in the Brazilian case, based on the inhomogeneous distribution throughout the national territory of political support for the federal government. This political support is quantified by the voting rates in the last general election in Brazil. This data is correlated with the fatality rates by COVID-19 in each Brazilian state as the number of deaths grows over time. We show that the correlation between fatality rate and political support grows as the government's misinformation campaign is developed. This led to the dominance of such political factor for the pandemic impact in Brazil in 2021. Once this dominance is established, this correlation allows for an estimation of the total number of deaths due to political influence as 350±70 thousand up to the end of 2021, corresponding to (57±11)% of the total number of deaths. [ABSTRACT FROM AUTHOR]

Purpose: Medical residents' mental health is currently an issue of concern for medical educators worldwide. The COVID-19 pandemic has raised the greatest concerns given the psychological effects of this scenario on medical residents on the frontlines of the pandemic. To assess the psychological impact of the COVID-19 pandemic on physicians in residency training, the collective symptoms of burnout, depression and anxiety are used to identify the residents' beliefs and clinical practices related to COVID-19 patients and their behaviors concerning disease prevention. Method: This observational study involved 3071 medical residents from all regions of Brazil. An online questionnaire assessed the presence of burnout using the Oldenburg Burnout Inventory, depressive symptoms using the Patient Health Questionaire-9, anxiety symptoms using the Generalized Anxiety Disorder-7, and COVID-19 Impact Questions to assess the residents' beliefs and clinical practices related to COVID-19 patients. Exploratory analyses, logistic regression and multinomial regression analysis were performed in this investigation. Results: Moderate and severe depressive symptoms were the most common (67.7%) followed by anxiety symptoms (52.8%) and burnout (48.6%). The difference between residents with or without contact with COVID-19 patients was significant increased when analyzing different aspects of clinical practice, behavior, substance use and mental health. Conclusions: These results suggest an increase in depression and anxiety symptoms among medical residents dealing with COVID-19, upstaging previous concerns about medical residents' mental health. The prevalence of burnout is similar to that of a nonpandemic scenario. Considering the severity of the pandemic scenario and the overburden of healthcare services, medical residents' mental health deserves special care. [ABSTRACT FROM AUTHOR]

Background: Despite substantial evidence on the effectiveness of non-pharmaceutical interventions (NPIs), there is still limited evidence on the individual effects of different types of NPIs on social distancing, especially in low- and middle-income countries. Methods: We used panel data analysis to evaluate the effects of mandatory social distancing rules on social distancing. We obtained data on six different categories of mandatory restrictions implemented in Brazil, by date and state, from state government gazettes (diários oficiais). We then defined a social distancing rules index (SDI) to measure the strictness of social distancing rules, assigning each a value of 2, 1, or 0 depending on whether restrictions were full, partial, or very limited/non-existent at every given time. A separate variable was defined for masking mandates. We tested whether the following variables were associated to social distancing: SDI, masking mandates, COVID-19 incidence, population socioeconomic status, and political orientation. Data is for each day between March 11th and November 10th, 2020 in the 27 Brazilian states (N = 6615). Findings: Social distancing increased when social distancing rules were stricter, and decreased when the use of face masks became mandatory. The effects of different types of restrictions varied: suspending in-person classes and gatherings, religious/sport/cultural activities had a greater effect than other types of restrictions. Also, the effect of social distancing rules on people's behaviour decreased over time, especially when rules were stricter. Interpretation: Mandatory social distancing rules must be adopted to increase social distancing. Stricter rules have a higher impact, but result in decreased compliance over time. Policymakers should prioritize more targeted policies. [ABSTRACT FROM AUTHOR]

The emergence of the COVID-19 pandemic resulted in an unprecedented need for RT-qPCR-based molecular diagnostic testing, placing a strain on the supply chain and the availability of commercially available PCR testing kits and reagents. The effect of limited molecular diagnostics-related supplies has been felt across the globe, disproportionally impacting molecular diagnostic testing in developing countries where acquisition of supplies is limited due to availability. The increasing global demand for commercial molecular diagnostic testing kits and reagents has made standard PCR assays cost prohibitive, resulting in the development of alternative approaches to detect SARS-CoV-2 in clinical specimens, circumventing the need for commercial diagnostic testing kits while mitigating the high-demand for molecular diagnostics testing. The timely availability of the complete SARS-CoV-2 genome in the beginning of the COVID-19 pandemic facilitated the rapid development and deployment of specific primers and standardized laboratory protocols for the molecular diagnosis of COVID-19. An alternative method offering a highly specific manner of detecting and genotyping pathogens within clinical specimens is based on the melting temperature differences of PCR products. This method is based on the melting temperature differences between purine and pyrimidine bases. Here, RT-qPCR assays coupled with a High Resolution Melting analysis (HRM-RTqPCR) were developed to target different regions of the SARS-CoV-2 genome (RdRp, E and N) and an internal control (human RNAse P gene). The assays were validated using synthetic sequences from the viral genome and clinical specimens (nasopharyngeal swabs, serum and saliva) of sixty-five patients with severe or moderate COVID-19 from different states within Brazil; a larger validation group than that used in the development to the commercially available TaqMan RT-qPCR assay which is considered the gold standard for COVID-19 testing. The sensitivity of the HRM-RTqPCR assays targeting the viral N, RdRp and E genes were 94.12, 98.04 and 92.16%, with 100% specificity to the 3 SARS-CoV-2 genome targets, and a diagnostic accuracy of 95.38, 98.46 and 93.85%, respectively. Thus, HRM-RTqPCR emerges as an attractive alternative and low-cost methodology for the molecular diagnosis of COVID-19 in restricted-budget laboratories. [ABSTRACT FROM AUTHOR]

Reinfection and multiple viral strains are among the latest challenges in the current COVID-19 pandemic. In contrast, epidemic models often consider a single strain and perennial immunity. To bridge this gap, we present a new epidemic model that simultaneously considers multiple viral strains and reinfection due to waning immunity. The model is general, applies to any viral disease and includes an optimal control formulation to seek a trade-off between the societal and economic costs of mitigation. We validate the model, with and without mitigation, in the light of the COVID-19 epidemic in England and in the state of Amazonas, Brazil. The model can derive optimal mitigation strategies for any number of viral strains, whilst also evaluating the effect of distinct mitigation costs on the infection levels. The results show that relaxations in the mitigation measures cause a rapid increase in the number of cases, and therefore demand more restrictive measures in the future. [ABSTRACT FROM AUTHOR]

Urban seismology has gained scientific interest with the development of seismic ambient noise monitoring techniques and also for being a useful tool to connect society with the Earth sciences. The interpretation of the sources of seismic records generated by sporting events, traffic, or huge agglomerations arouses the population's curiosity and opens up a range of possibilities for new applications of seismology, especially in the area of urban monitoring. In this contribution, we present the analysis of seismic records from a station in the city of Brasilia during unusual episodes of silencing and noisy periods. Usually, cultural noise is observed in high-fequency bands. We showed in our analysis that cultural noise can also be observed in the low-frequency band, when high-frequency signal is attenuated. As examples of noisy periods, we have that of the Soccer World Cup in Brazil in 2014, where changes in noise are related to celebrations of goals and the party held by FIFA in the city, and the political manifestations in the period of the Impeachment trial in 2016, which reached the concentration of about 300,000 protesters. The two most characteristic periods of seismic silence have been the quarantine due to the COVID-19 pandemic in 2020, and the trucker strike that occurred across the country in 2018, both drastically reducing the movement of people in the city. [ABSTRACT FROM AUTHOR]

In Dec 2020 Brazil became one of the worldwide epicenters of the COVID-19 pandemic with more than 7.2M reported cases. Brazil has a large territory with unequal distribution of healthcare resources including physicians. Resource limitation has been one of the main factors hampering Brazil's response to the COVID-19 crisis. Telemedicine has been an effective approach for COVID-19 management as it allows to reduce the risk of cross-contamination and provides support to remote rural locations. Here we present the analyses of teleconsultations from a countrywide telemedicine service (TelessáudeRS-UFRGS, TRS), that provides physician-to-physician remote support during the COVID-19 pandemic in Brazil. We performed a descriptive analysis of the teleconsultation incoming calls and a text analysis from the call transcripts. Our findings indicate that TRS teleconsultations in Brazil experienced an exponential increment of 802.% during a period of 6 days, after the first death due to COVID-19 was reported. However, the number of teleconsultations cases decreased over time, despite the number of reported COVID-19 cases continuously increasing. The results also showed that physicians in low-income municipalities, based on GDP per capita, are less likely to consult the telemedicine service despite facing higher rates of COVID-19 cases. The text analysis of call transcripts from medical teleconsultations showed that the main concern of physicians were "asymptomatic" patients. We suggest an immediate reinforcement of telehealth services in the regions of lower income as a strategy to support COVID-19 management. [ABSTRACT FROM AUTHOR]

This work presents a practical proposal for estimating health system utilization for COVID-19 cases. The novel methodology developed is based on the dynamic model known as Susceptible, Infected, Removed and Dead (SIRD). The model was modified to focus on the healthcare system dynamics, rather than modeling all cases of the disease. It was tuned using data available for each Brazilian state and updated with daily figures. A figure of merit that assesses the quality of the model fit to the data was defined and used to optimize the free parameters. The parameters of an epidemiological model for the whole of Brazil, comprising a linear combination of the models for each state, were estimated considering the data available for the 26 Brazilian states. The model was validated, and strong adherence was demonstrated in most cases. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the discourses of patients who were diagnosed with multidrug-resistant tuberculosis, the perception of why they acquired this health condition and barriers to seeking care in a priority city in Brazil during the COVID-19 pandemic. This was an exploratory qualitative study, which used the theoretical-methodological framework of the Discourse Analysis of French matrix, guided by the Consolidated Criteria for Reporting Qualitative Research. The study was conducted in Ribeirão Preto, São Paulo, Brazil. Seven participants were interviewed who were undergoing treatment at the time of the interview. The analysis of the participants' discourses allowed the emergence of four discursive blocks: (1) impact of the social determinants in the development of multidrug-resistant tuberculosis, (2) barriers to seeking care and difficulties accessing health services, (3) perceptions of the side effects and their impact on multidrug-resistant tuberculosis treatment, and (4) tuberculosis and COVID-19: a necessary dialogue. Through discursive formations, these revealed the determinants of multidrug-resistant tuberculosis. Considering the complexity involved in the dynamics of multidrug-resistant tuberculosis, advancing in terms of equity in health, that is, in reducing unjust differences, is a challenge for public policies, especially at the current moment in Brazil, which is of accentuated economic, political and social crisis. The importance of psychosocial stressors and the lack of social support should also be highlighted as intermediary determinants of health. The study has also shown the situation of COVID-19, which consists of an important barrier for patients seeking care. Many patients reported fear, insecurity and worry with regard to returning to medical appointments, which might contribute to the worsening of tuberculosis in the scenario under study. [ABSTRACT FROM AUTHOR]

Background: There has been a rapid increase in the number of cases of COVID-19 in Latin America, Africa, Asia and many countries that have an insufficient number of physicians and other health care personnel, and the need for the inclusion of medical students on health teams is a very important issue. It has been recommended that medical students work as volunteers, undergo appropriate training, not undertake any activity beyond their level of competence, and receive continuous supervision and adequate personal protective equipment. However, the motivation of medical students must be evaluated to make volunteering a more evidence-based initiative. The aim of our study was to evaluate the motivation of medical students to be part of health teams to aid in the COVID-19 pandemic. Methods and findings: We developed a questionnaire specifically to evaluate medical students' perceptions about participating in the care of patients with suspected infection with coronavirus during the COVID-19 pandemic. The questionnaire had two parts: a) one part with questions on individual characteristics, year in medical school and geographic location of the medical school and b) a second part with twenty-eight statements assessed on a 5-point Likert scale (totally agree, agree, neither agree nor disagree, disagree and totally disagree). To develop the questionnaire, we performed consensus meetings with a group of faculty and medical students. The questionnaire was sent to student organizations of 257 medical schools in Brazil and answered by 10,433 students. We used multinomial logistic regression models to analyze the data. Statements associated with greater odds ratios for participation of medical students in the COVID-19 pandemic were related to a sense of purpose or duty ("It is the duty of the medical student to put himself or herself at the service of the population in the pandemic"), altruism ("I am willing to take risks by participating in practice in the context of the pandemic"), and perception of good performance and professional identity ("I will be a better health professional for having experienced the pandemic"). Males were more prone than females to believe that only interns should participate in the care of patients with COVID-19 (odds ratio 1.36 [coefficient interval 95%:1.24–1.49]) and that all students should participate (OR 1.68 [CI:1.4–1.91]). Conclusions: Medical students are more motivated by a sense of purpose or duty, altruism, perception of good performance and values of professionalism than by their interest in learning. These results have implications for the development of volunteering programs and the design of health force policies in the present pandemic and in future health emergencies. [ABSTRACT FROM AUTHOR]

The first case of the novel coronavirus in Brazil was notified on February 26, 2020. After 21 days, the first case was reported in the second largest State of the Brazilian Amazon. The State of Pará presented difficulties in combating the pandemic, ranging from underreporting and a low number of tests to a large territorial distance between cities with installed hospital capacity. Due to these factors, mathematical data-driven short-term forecasting models can be a promising initiative to assist government officials in more agile and reliable actions. This study presents an approach based on artificial neural networks for the daily and cumulative forecasts of cases and deaths caused by COVID-19, and the forecast of demand for hospital beds. Six scenarios with different periods were used to identify the quality of the generated forecasting and the period in which they start to deteriorate. Results indicated that the computational model adapted capably to the training period and was able to make consistent short-term forecasts, especially for the cumulative variables and for demand hospital beds. [ABSTRACT FROM AUTHOR]

We analyze the trade-offs between health and the economy during the period of social distancing in São Paulo, the state hardest hit by the COVID-19 pandemic in Brazil. We use longitudinal data with municipal-level information and check the robustness of our estimates to several sources of bias, including spatial dependence, reverse causality, and time-variant omitted variables. We use exogenous climate shocks as instruments for social distancing since people are more likely to stay home in wetter and colder periods. Our findings suggest that the health benefits of social distancing differ by levels of municipal development and may have vanished if the COVID-19 spread was not controlled in neighboring municipalities. In turn, we did not find evidence that municipalities with tougher social distancing performed worse economically. Our results also highlight that estimates that do not account for endogeneity may largely underestimate the benefits of social distancing on reducing the spread of COVID-19. [ABSTRACT FROM AUTHOR]

As of mid-August 2020, Brazil was the country with the second-highest number of cases and deaths by the COVID-19 pandemic, but with large regional and social differences. In this study, using data from the Brazilian Ministry of Health, we analyze the spatial patterns of infection and mortality from Covid-19 across small areas of Brazil. We apply spatial autoregressive Bayesian models and estimate the risks of infection and mortality, taking into account age, sex composition of the population and other variables that describe the health situation of the spatial units. We also perform a decomposition analysis to study how age composition impacts the differences in mortality and infection rates across regions. Our results indicate that death and infections are spatially distributed, forming clusters and hotspots, especially in the Northern Amazon, Northeast coast and Southeast of the country. The high mortality risk in the Southeast part of the country, where the major cities are located, can be explained by the high proportion of the elderly in the population. In the less developed areas of the North and Northeast, there are high rates of infection among young adults, people of lower socioeconomic status, and people without access to health care, resulting in more deaths. [ABSTRACT FROM AUTHOR]

Background: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work accommodation policies. Non-clinical sociodemographic features are important explanatory variables of COVID-19 outcomes, revealing existing disparities in large health care systems. Methods and findings: We use nation-wide multicenter data of COVID-19 patients in Brazil to predict mortality and ventilator usage. The dataset contains hospitalized patients who tested positive for COVID-19 and had either recovered or were deceased between March 1 and June 30, 2020. A total of 113,214 patients with 50,387 deceased, were included. Both interpretable (sparse versions of Logistic Regression and Support Vector Machines) and state-of-the-art non-interpretable (Gradient Boosted Decision Trees and Random Forest) classification methods are employed. Death from COVID-19 was strongly associated with demographics, socioeconomic factors, and comorbidities. Variables highly predictive of mortality included geographic location of the hospital (OR = 2.2 for Northeast region, OR = 2.1 for North region); renal (OR = 2.0) and liver (OR = 1.7) chronic disease; immunosuppression (OR = 1.7); obesity (OR = 1.7); neurological (OR = 1.6), cardiovascular (OR = 1.5), and hematologic (OR = 1.2) disease; diabetes (OR = 1.4); chronic pneumopathy (OR = 1.4); immunosuppression (OR = 1.3); respiratory symptoms, ranging from respiratory discomfort (OR = 1.4) and dyspnea (OR = 1.3) to oxygen saturation less than 95% (OR = 1.7); hospitalization in a public hospital (OR = 1.2); and self-reported patient illiteracy (OR = 1.1). Validation accuracies (AUC) for predicting mortality and ventilation need reach 79% and 70%, respectively, when using only pre-admission variables. Models that use post-admission disease progression information reach accuracies (AUC) of 86% and 87% for predicting mortality and ventilation use, respectively. Conclusions: The results highlight the predictive power of socioeconomic information in assessing COVID-19 mortality and medical resource allocation, and shed light on existing disparities in the Brazilian health care system during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The current outbreak of the coronavirus disease 2019 (COVID-19) is an unprecedented example of how fast an infectious disease can spread around the globe (especially in urban areas) and the enormous impact it causes on public health and socio-economic activities. Despite the recent surge of investigations about different aspects of the COVID-19 pandemic, we still know little about the effects of city size on the propagation of this disease in urban areas. Here we investigate how the number of cases and deaths by COVID-19 scale with the population of Brazilian cities. Our results indicate small towns are proportionally more affected by COVID-19 during the initial spread of the disease, such that the cumulative numbers of cases and deaths per capita initially decrease with population size. However, during the long-term course of the pandemic, this urban advantage vanishes and large cities start to exhibit higher incidence of cases and deaths, such that every 1% rise in population is associated with a 0.14% increase in the number of fatalities per capita after about four months since the first two daily deaths. We argue that these patterns may be related to the existence of proportionally more health infrastructure in the largest cities and a lower proportion of older adults in large urban areas. We also find the initial growth rate of cases and deaths to be higher in large cities; however, these growth rates tend to decrease in large cities and to increase in small ones over time. [ABSTRACT FROM AUTHOR]

Brazil detected community transmission of COVID-19 on March 13, 2020. In this study we identified which areas in the country were the most vulnerable for COVID-19, both in terms of the risk of arrival of cases, the risk of sustained transmission and their social vulnerability. Probabilistic models were used to calculate the probability of COVID-19 spread from São Paulo and Rio de Janeiro, the initial hotspots, using mobility data from the pre-epidemic period, while multivariate cluster analysis of socio-economic indices was done to identify areas with similar social vulnerability. The results consist of a series of maps of effective distance, outbreak probability, hospital capacity and social vulnerability. They show areas in the North and Northeast with high risk of COVID-19 outbreak that are also highly socially vulnerable. Later, these areas would be found the most severely affected. The maps produced were sent to health authorities to aid in their efforts to prioritize actions such as resource allocation to mitigate the effects of the pandemic. In the discussion, we address how predictions compared to the observed dynamics of the disease. [ABSTRACT FROM AUTHOR]