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Patients with cancer were excluded from pivotal randomized clinical trials of COVID-19 vaccine products, and available observational evidence on vaccine effectiveness (VE) focused mostly on mild, and not severe COVID-19, which is the ultimate goal of vaccination for high-risk groups. Here, using primary care electronic health records from Catalonia, Spain (SIDIAP), we built two large cohorts of vaccinated and matched control cancer patients with a primary vaccination scheme (n = 184,744) and a booster (n = 108,534). Most patients received a mRNA-based product in primary (76.2%) and booster vaccination (99.9%). Patients had 51.8% (95% CI 40.3%-61.1%) and 58.4% (95% CI 29.3%-75.5%) protection against COVID-19 hospitalization and COVID-19 death respectively after full vaccination (two-doses) and 77.9% (95% CI 69.2%-84.2%) and 80.2% (95% CI 63.0%-89.4%) after booster. Compared to primary vaccination, the booster dose provided higher peak protection during follow-up. Calibration of VE estimates with negative outcomes, and sensitivity analyses with slight different population and COVID-19 outcomes definitions provided similar results. Our results confirm the role of primary and booster COVID-19 vaccination in preventing COVID-19 severe events in patients with cancer and highlight the need for the additional dose in this population., (© 2024. The Author(s).)

Coronavirus Anxiety Scale (CAS) is a widely used measure that captures somatic symptoms of coronavirus-related anxiety. In a large-scale collaboration spanning 60 countries ( N = 21,513), we examined the CAS's measurement invariance and assessed the convergent validity of CAS scores in relation to the fear of COVID-19 (FCV-19S) and the satisfaction with life (SWLS-3) scales. We utilized both conventional exact invariance tests and alignment procedures, with results revealing that the single-factor model fit the data well in almost all countries. Partial scalar invariance was supported in a subset of 56 countries. To ensure the robustness of results, given the unbalanced samples, we employed resampling techniques both with and without replacement and found the results were more stable in larger samples. The alignment procedure demonstrated a high degree of measurement invariance with 9% of the parameters exhibiting noninvariance. We also conducted simulations of alignment using the parameters estimated in the current model. Findings demonstrated reliability of the means but indicated challenges in estimating the latent variances. Strong positive correlations between CAS and FCV-19S estimated with all three different approaches were found in most countries. Correlations of CAS and SWLS-3 were weak and negative but significantly differed from zero in several countries. Overall, the study provided support for the measurement invariance of the CAS and offered evidence of its convergent validity while also highlighting issues with variance estimation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).total = 21,513), we examined the CAS's measurement invariance and assessed the convergent validity of CAS scores in relation to the fear of COVID-19 (FCV-19S) and the satisfaction with life (SWLS-3) scales. We utilized both conventional exact invariance tests and alignment procedures, with results revealing that the single-factor model fit the data well in almost all countries. Partial scalar invariance was supported in a subset of 56 countries. To ensure the robustness of results, given the unbalanced samples, we employed resampling techniques both with and without replacement and found the results were more stable in larger samples. The alignment procedure demonstrated a high degree of measurement invariance with 9% of the parameters exhibiting noninvariance. We also conducted simulations of alignment using the parameters estimated in the current model. Findings demonstrated reliability of the means but indicated challenges in estimating the latent variances. Strong positive correlations between CAS and FCV-19S estimated with all three different approaches were found in most countries. Correlations of CAS and SWLS-3 were weak and negative but significantly differed from zero in several countries. Overall, the study provided support for the measurement invariance of the CAS and offered evidence of its convergent validity while also highlighting issues with variance estimation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Objectives: In 2020, Brazil experienced two concurrent public health challenges related to respiratory disease: wildfires and increased mortality due to the coronavirus (COVID-19) pandemic. Smoke from these wildfires contributed to a variety of air pollutants, including fine particulate matter (PM 2.5 ). The present study aims to investigate the effects of environmental and socio-economic factors on COVID-19 hospitalisation in the Pantanal., Study Design: Ecological retrospective study., Methods: We applied a multilevel negative binomial model to relate monthly hospitalisation data with environmental variables., Results: We showed that monthly PM 2.5 concentration levels had the greatest influence on the increase in hospitalisations by COVID-19 in the elderly (23 % increase). The Gini index, a coefficient that reflects income inequalities, also had a positive association with COVID-19 hospitalisations (18 % increase). Higher temperatures and humidity were protective factors, showing a 15 % and 14 % decrease in hospitalisations, respectively. The results of the present study suggest that high PM 2.5 exposure contributed to the increase in COVID-19 hospitalisations, as did the social inequalities of each municipality., Conclusions: The present study highlights the importance of gathering evidence supported by multiple information sources to guide decision-making and identify populations needing better public health systems., (Copyright © 2023 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

Objective: To investigate the relationship between covid-19 hospital mortality and risk factors, innovating by considering contextual and individual factors and spatial dependency and using data from the city of São Paulo, Brazil., Methods: The study was performed with a spatial hierarchical retrospective cohort design using secondary data (individuals and contextual data) from hospitalized patients and their geographic unit residences. The study period corresponded to the first year of the pandemic, from February 25, 2020 to February 24, 2021. Mortality was modeled with the Bayesian context, Bernoulli probability distribution, and the integrated nested Laplace approximations. The demographic, distal, medial, and proximal covariates were considered., Results: We found that per capita income, a contextual covariate, was a protective factor (odds ratio: 0.76 [95% credible interval: 0.74-0.78]). After adjusting for income, the other adjustments revealed no differences in spatial dependence. Without income inequality in São Paulo, the spatial risk of death would be close to one in the city. Other factors associated with high covid-19 hospital mortality were male sex, advanced age, comorbidities, ventilation, treatment in public healthcare settings, and experiencing the first covid-19 symptoms between January 24 and February 24, 2021., Conclusions: Other than sex and age differences, geographic income inequality was the main factor responsible for the spatial differences in the risk of covid-19 hospital mortality. Investing in public policies to reduce socioeconomic inequities, infection prevention, and other intersectoral measures should focus on lower per capita income, to control covid-19 hospital mortality.

It is crucial to understand why people comply with measures to contain viruses and their effects during pandemics. We provide evidence from 35 countries (N total  = 12,553) from 6 continents during the COVID-19 pandemic (between 2021 and 2022) obtained via cross-sectional surveys that the social perception of key protagonists on two basic dimensions-warmth and competence-plays a crucial role in shaping pandemic-related behaviors. Firstly, when asked in an open question format, heads of state, physicians, and protest movements were universally identified as key protagonists across countries. Secondly, multiple-group confirmatory factor analyses revealed that warmth and competence perceptions of these and other protagonists differed significantly within and between countries. Thirdly, internal meta-analyses showed that warmth and competence perceptions of heads of state, physicians, and protest movements were associated with support and opposition intentions, containment and prevention behaviors, as well as vaccination uptake. Our results have important implications for designing effective interventions to motivate desirable health outcomes and coping with future health crises and other global challenges., (© 2022. The Author(s).)

Visceral adiposity is a risk factor for severe COVID-19, and a link between adipose tissue infection and disease progression has been proposed. Here we demonstrate that SARS-CoV-2 infects human adipose tissue and undergoes productive infection in fat cells. However, susceptibility to infection and the cellular response depends on the anatomical origin of the cells and the viral lineage. Visceral fat cells express more ACE2 and are more susceptible to SARS-CoV-2 infection than their subcutaneous counterparts. SARS-CoV-2 infection leads to inhibition of lipolysis in subcutaneous fat cells, while in visceral fat cells, it results in higher expression of pro-inflammatory cytokines. Viral load and cellular response are attenuated when visceral fat cells are infected with the SARS-CoV-2 gamma variant. A similar degree of cell death occurs 4-days after SARS-CoV-2 infection, regardless of the cell origin or viral lineage. Hence, SARS-CoV-2 infects human fat cells, replicating and altering cell function and viability in a depot- and viral lineage-dependent fashion., (© 2022. The Author(s).)

Background: Capacity strain negatively impacts patient outcome, and the effects of patient surge are a continuous threat during the COVID-19 pandemic. Evaluating changes in mortality over time enables evidence-based resource planning, thus improving patient outcome. Our aim was to describe baseline risk factors associated with mortality among COVID-19 hospitalized patients and to compare mortality rates over time., Methods: We conducted a retrospective cohort study in the largest referral hospital for COVID-19 patients in Sao Paulo, Brazil. We investigated risk factors associated with mortality during hospitalization. Independent variables included age group, sex, the Charlson Comorbidity Index, admission period according to the stage of the first wave of the epidemic (early, peak, and late), and intubation., Results: We included 2949 consecutive COVID-19 patients. 1895 of them were admitted to the ICU, and 1473 required mechanical ventilation. Median length of stay in the ICU was 10 (IQR 5-17) days. Overall mortality rate was 35%, and the adjusted odds ratios for mortality increased with age, male sex, higher Charlson Comorbidity index, need for mechanical ventilation, and being admitted to the hospital during the wave peak of the epidemic. Being admitted to the hospital during the wave peak was associated with a 33% higher risk of mortality., Conclusions: In-hospital mortality was independently affected by the epidemic period. The recognition of modifiable operational variables associated with patient outcome highlights the importance of a preparedness plan and institutional protocols that include evidence-based practices and allocation of resources., Competing Interests: Dr Ferreira received speaker fees from Medtronic, outside of the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

The beta distribution is routinely used to model variables that assume values in the standard unit interval, (0, 1). Several alternative laws have, nonetheless, been proposed in the literature, such as the Kumaraswamy and simplex distributions. A natural and empirically motivated question is: does the beta law provide an adequate representation for a given dataset? We test the null hypothesis that the beta model is correctly specified against the alternative hypothesis that it does not provide an adequate data fit. Our tests are based on the information matrix equality, which only holds when the model is correctly specified. They are thus sensitive to model misspecification. Simulation evidence shows that the tests perform well, especially when coupled with bootstrap resampling. We model state and county Covid-19 mortality rates in the United States. The misspecification tests indicate that the beta law successfully represents Covid-19 death rates when they are computed using either data from prior to the start of the vaccination campaign or data collected when such a campaign was under way. In the latter case, the beta law is only accepted when the negative impact of vaccination reach on death rates is moderate. The beta model is rejected under data heterogeneity, i.e., when mortality rates are computed using information gathered during both time periods., Competing Interests: The authors have declared that no competing interests exist.

This study aimed at analysing the potential effects of the COVID-19 pandemic on the time series and spatial patterns of live births in the state of Pernambuco, Brazil, from 2010 to 2021. This is an ecological study that applied intervention analysis in time series, with the goal to identify how projected data behaved in relation to observed data in the months December 2020 to November 2021, i.e. months representing conceptions from March2020 to April 2021. For the state of Pernambuco, a discrepancy up to +5.7% was found between the observed and projected data, while the respective difference for the São Francisco mesoregion showed the opposite trend with maximum discrepancy of -9%. The results did not indicate a clear change in the number of live births but supported the expected continuation of the downward trend of the previous years. Considering the importance of the number of live births in the context of demography, economy and public health, monitoring must be maintained to analyse the possible future impact of the COVID-19 pandemic on live birth projections.

The SARS-CoV-2 nucleocapsid protein (N) is a multifunctional promiscuous nucleic acid-binding protein, which plays a major role in nucleocapsid assembly and discontinuous RNA transcription, facilitating the template switch of transcriptional regulatory sequences (TRS). Here, we dissect the structural features of the N protein N-terminal domain (N-NTD) and N-NTD plus the SR-rich motif (N-NTD-SR) upon binding to single and double-stranded TRS DNA, as well as their activities for dsTRS melting and TRS-induced liquid-liquid phase separation (LLPS). Our study gives insights on the specificity for N-NTD(-SR) interaction with TRS. We observed an approximation of the triple-thymidine (TTT) motif of the TRS to β-sheet II, giving rise to an orientation difference of ~25° between dsTRS and non-specific sequence (dsNS). It led to a local unfavorable energetic contribution that might trigger the melting activity. The thermodynamic parameters of binding of ssTRSs and dsTRS suggested that the duplex dissociation of the dsTRS in the binding cleft is entropically favorable. We showed a preference for TRS in the formation of liquid condensates when compared to NS. Moreover, our results on DNA binding may serve as a starting point for the design of inhibitors, including aptamers, against N, a possible therapeutic target essential for the virus infectivity., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Studies have shown that human mobility is an important factor in dengue epidemiology. Changes in mobility resulting from COVID-19 pandemic set up a real-life situation to test this hypothesis. Our objective was to evaluate the effect of reduced mobility due to this pandemic in the occurrence of dengue in the state of São Paulo, Brazil., Method: It is an ecological study of time series, developed between January and August 2020. We use the number of confirmed dengue cases and residential mobility, on a daily basis, from secondary information sources. Mobility was represented by the daily percentage variation of residential population isolation, obtained from the Google database. We modeled the relationship between dengue occurrence and social distancing by negative binomial regression, adjusted for seasonality. We represent the social distancing dichotomously (isolation versus no isolation) and consider lag for isolation from the dates of occurrence of dengue., Results: The risk of dengue decreased around 9.1% (95% CI: 14.2 to 3.7) in the presence of isolation, considering a delay of 20 days between the degree of isolation and the dengue first symptoms., Conclusions: We have shown that mobility can play an important role in the epidemiology of dengue and should be considered in surveillance and control activities., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Understanding differences in hospital case fatality rates (HCFRs) of coronavirus disease 2019 (COVID-19) may help evaluate its severity and the capacity of the healthcare system to reduce mortality., Methods: We examined the variability in HCFRs of COVID-19 in relation to spatial inequalities in socio-economic factors, hospital health sector and patient medical condition across the city of São Paulo, Brazil. We obtained the standardized hospital case fatality ratio adjusted indirectly by age and sex, which is the ratio between the HCFR of a specific spatial unit and the HCFR for the entire study area. We modelled it using a generalized linear mixed model with spatial random effects in a Bayesian context., Results: We found that HCFRs were higher for men and for individuals ≥60 y of age. Our models identified per capita income as a significant factor that is negatively associated with the HCFRs of COVID-19, even after adjusting for age, sex and presence of risk factors., Conclusions: Spatial analyses of the implementation of these methods and of disparities in COVID-19 outcomes may help in the development of policies for at-risk populations in geographically defined areas., (© The Author(s) 2021. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)

Currently most researchers consider humanity's extermination of biodiversity as the antecedent of ideal conditions for the emergence of new viruses and diseases. Animals lose their natural habitats due to extensive landscape changes, consequently crowding them together and increasing their interaction with humans. Additionally, it is also important to emphasise the increasing concern on climate change because climate can modify the distribution and intensity of other diseases such as vector-borne disease. Unfortunately, the global resources for biodiversity conservation were diluted by government support for activities harmful to the environment. A tragic example is from the Amazon rainforest, that experienced fast environmental depletion and high social inequalities. Extractive systems and extensive land use on a large scale have induced deforestation, great loss of biodiversity, carbon emission, and water contamination, leading to indigenous land dispossession, violence, and rural-urban migration. The deforested areas in the Amazon region increase considerably at an alarming speed each year. The COVID-19 pandemic is an evidence to show how viruses and pathogens move further and faster than before, which means we must also show a quick response. It requires financing and, mostly, changes in human behaviour. The message is simple: we need to rethink our current relationship with nature and with ourselves, which should lead to a social transformation towards the sustainable use of the available resources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The present study focused on the scenario of confirmed cases of SARS-CoV-2 infection in the state of Minas Gerais (MG), Brazil, from March 2020 to March 2021. We evaluated the evolution of COVID-19 prevalence and death in one municipality from each of the 14 health macro-regions of MG state. Socio-demographic characteristics and variables related to the municipalities were analyzed. The raw dataset used in this study was freely sourced from the website Brasil.io. From the raw dataset, two time series were extracted: the cumulative confirmed cases of COVID-19 and cumulative death counts, and they were compared to the state data using a nowcasting approach. In order to make time series comparisons possible, all data was normalized per 100,000 inhabitants. When analyzing in light of colored wave code interventions initiated in August 2020 in MG, for the majority of the municipalities, there was an absence of clear influence on prevalence and deaths. The national holidays in the first semester of 2020 had a small impact on the COVID-19 prevalence of the municipalities, but the holidays in the second semester of 2020 and beginning of 2021 caused important impacts on COVID-19 prevalence. The low number of ICU beds in some municipalities contributed to the higher number of deaths. The analysis showed here is expected to contribute to the improvement of decision making of the MG government, as it opened a huge possibility to have the total macro-regions and state data analyzed.

Objective: To externally validate community-acquired pneumonia (CAP) tools on patients hospitalized with coronavirus disease 2019 (COVID-19) pneumonia from two distinct countries, and compare their performance with recently developed COVID-19 mortality risk stratification tools., Methods: We evaluated 11 risk stratification scores in a binational retrospective cohort of patients hospitalized with COVID-19 pneumonia in São Paulo and Barcelona: Pneumonia Severity Index (PSI), CURB, CURB-65, qSOFA, Infectious Disease Society of America and American Thoracic Society Minor Criteria, REA-ICU, SCAP, SMART-COP, CALL, COVID GRAM and 4C. The primary and secondary outcomes were 30-day in-hospital mortality and 7-day intensive care unit (ICU) admission, respectively. We compared their predictive performance using the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, likelihood ratios, calibration plots and decision curve analysis., Results: Of 1363 patients, the mean (SD) age was 61 (16) years. The 30-day in-hospital mortality rate was 24.6% (228/925) in São Paulo and 21.0% (92/438) in Barcelona. For in-hospital mortality, we found higher AUCs for PSI (0.79, 95% CI 0.77-0.82), 4C (0.78, 95% CI 0.75-0.81), COVID GRAM (0.77, 95% CI 0.75-0.80) and CURB-65 (0.74, 95% CI 0.72-0.77). Results were similar for both countries. For the 1%-20% threshold range in decision curve analysis, PSI would avoid a higher number of unnecessary interventions, followed by the 4C score. All scores had poor performance (AUC <0.65) for 7-day ICU admission., Conclusions: Recent clinical COVID-19 assessment scores had comparable performance to standard pneumonia prognostic tools. Because it is expected that new scores outperform older ones during development, external validation studies are needed before recommending their use., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objectives: This study aimed to compare differences in mortality risk factors between admission and follow-up incorporated models., Methods: A retrospective cohort study of 524 patients with confirmed COVID-19 infection admitted to a tertiary medical center in São Paulo, Brazil from 13 March to 30 April 2020. Data were collected on admission, and the third, eighth and fourteenth days of hospitalization. The hazard ratio (HR) was calculated and 28-day in-hospital mortality risk factors were compared between admission and follow-up models using a time-dependent Cox regression model., Results: Of 524 patients, 50.4% needed mechanical ventilation. The 28-day mortality rate was 32.8%. Compared with follow-up, admission models under-estimated the mortality HR for peripheral oxygen saturation <92% (1.21 versus 2.09), heart rate >100 bpm (1.19 versus 2.04), respiratory rate >24/min (1.01 versus 1.82) and mechanical ventilation (1.92 versus 12.93). Low oxygen saturation, higher oxygen support and more biomarkers-including lactate dehydrogenase, C-reactive protein, neutrophil-lymphocyte ratio, and urea remained associated with mortality after adjustment for clinical factors at follow-up compared with only urea and oxygen support at admission., Conclusions: The inclusion of follow-up measurements changed mortality hazards of clinical signs and biomarkers. Low oxygen saturation, higher oxygen support, lactate dehydrogenase, C-reactive protein, neutrophil-lymphocyte ratio, and urea could help with prognosis of patients during follow-up., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The COVID-19 pandemic has become one of the main international concerns regarding its impact on mental health. The present study aims to investigate the prevalence of depression, anxiety, and stress symptoms, and behavioral aspects amidst the COVID-19 pandemic in a Brazilian population. An online survey was administered from May 22 to June 5, 2020 using a questionnaire comprising of sociodemographic information, the Depression, Anxiety, and Stress Scale (DASS-21), and the Coping Strategies Inventory. Participants comprised 3,000 people from Brazil's 26 states and the Federal District, with an average age of 39.8 years, women (83%), married (50.6%), graduates (70.1%) and employees (46.7%). Some contracted the virus (6.4%) and had dead friends or relatives (22.7%). There was more consumption of drugs, tobacco, medication, and food (40.8%). Almost half of participants expressed symptoms of depression (46.4%), anxiety (39.7%), and stress (42.2%). These were higher in women, people without children, students, patients with chronic diseases, and people who had contact with others diagnosed with COVID-19. The existence of a group more vulnerable to situations with a high stress burden requires greater attention regarding mental health during and after the pandemic. That said, it should be emphasized that these findings are preliminary and portray a moment still being faced by many people amid the pandemic and quarantine measures. Therefore, we understand that the magnitude of the impacts on mental health will only be more specific with continuous studies after total relaxation of the quarantine., Competing Interests: The authors declare no conflict of interest.

Background: The first cases of coronavirus disease (COVID-19) in Brazil were diagnosed in February 2020. Our Emergency Department (ED) was designated as a COVID-19 exclusive service. We report our first 500 confirmed COVID-19 pneumonia patients., Methods: From 14 March to 16 May 2020, we enrolled all patients admitted to our ED that had a diagnosis of COVID-19 pneumonia. Infection was confirmed via nasopharyngeal swabs or tracheal aspirate PCR. The outcomes included hospital discharge, invasive mechanical ventilation, and in-hospital death, among others., Results: From 2219 patients received in the ED, we included 506 with confirmed COVID-19 pneumonia. We found that 333 patients were discharged home (65.9%), 153 died (30.2%), and 20 (3.9%) remained in the hospital. A total of 300 patients (59.3%) required ICU admission, and 227 (44.9%) needed invasive ventilation. The multivariate analysis found age, number of comorbidities, extension of ground glass opacities on chest CT and troponin with a direct relationship with all-cause mortality, whereas dysgeusia, use of angiotensin converting enzyme inhibitor or angiotensin-ii receptor blocker and number of lymphocytes with an inverse relationship with all-cause mortality., Conclusions: This was a sample of severe patients with COVID-19, with 59.2% admitted to the ICU and 41.5% requiring mechanical ventilator support. We were able to ascertain the outcome in majority (96%) of patients. While the overall mortality was 30.2%, mortality for intubated patients was 55.9%. Multivariate analysis agreed with data found in other studies although the use of angiotensin converting enzyme inhibitor or angiotensin-ii receptor blocker as a protective factor could be promising but would need further studies., Trial Registration: The study was registered in the Brazilian registry of clinical trials: RBR-5d4dj5., Competing Interests: The authors have declared that no competing interests exist.

Background: Currently, Brazil is experiencing one of the fastest increasing coronavirus disease (COVID-19) mortality rates worldwide, with a minimum of 158,000 confirmed deaths presently. The city of São Paulo is particularly vulnerable because it is the most populated city in Brazil. Thus, this study aimed to analyse COVID-19 mortality in a spatiotemporal context in São Paulo, with respect to socio-economic levels., Method: We modelled the deaths using spatiotemporal architectures and Poisson probability distributions using a latent Gaussian Bayesian model approach., Results: Both total deaths and confirmed deaths showed similar spatial patterns. Mortality was higher in men and increased with age. The most critical period regarding mortality occurred between the 20th and 23rd epidemiological weeks, followed by an apparent stabilisation of the epidemiological trend. The risk of death was greater in areas with the worst social conditions during the study period. However, this pattern was not uniform over time, since we identified a shift of high risk from the areas with the best socio-economic conditions to those with the worst conditions., Conclusions: Our study corroborated the relationship between COVID-19 mortality and socio-economic conditions, revealing the importance of geographic screening in the integration of better actions to face the pandemic., (Copyright © 2020 Elsevier Ltd. All rights reserved.)