Duration of vaccine protection against breakthrough infections during five COVID-19 waves among healthcare workers primarily vaccinated with CoronaVac.

We aimed to characterise vaccine-induced protection against COVID-19 during five waves caused by Variants of Concern (VOCs). This is a nested case-control study of 3,972 HCW primarily vaccinated with CoronaVac (98%) that evaluated symptomatic SARS-CoV-2 breakthrough infections (BI) in almost two-years follow-up until the 3rd Omicron wave. Predictors of protection against SARS-CoV-2 BI were analysed using conditional logistic regression models. We included 1,491 SARS-CoV-2 breakthrough cases, mostly mild, and 2,962 controls. Most participants (90%) had received at least one booster before the onset of the Omicron waves, mainly BNT162b2. A multivariate logistic regression showed that vaccine-induced protection against BI wanes after six months regardless of the number of monovalent booster doses. Additionally, booster dose with BNT162b2 showed a trend for higher protection compared to CoronaVac during the Omicron waves. In conclusion, immunity of monovalent booster doses against SARS-CoV-2 is short-lasting. Individuals previously vaccinated with an inactivated vaccine should receive a BNT162B2 booster dose.

Cardiac involvement in Chagas disease and African trypanosomiasis.

Trypanosomiases are diseases caused by various species of protozoan parasite in the genus Trypanosoma, each presenting with distinct clinical manifestations and prognoses. Infections can affect multiple organs, with Trypanosoma cruzi predominantly affecting the heart and digestive system, leading to American trypanosomiasis or Chagas disease, and Trypanosoma brucei primarily causing a disease of the central nervous system known as human African trypanosomiasis or sleeping sickness. In this Review, we discuss the effects of these infections on the heart, with particular emphasis on Chagas disease, which continues to be a leading cause of cardiomyopathy in Latin America. The epidemiology of Chagas disease has changed substantially since 1990 owing to the emigration of over 30 million Latin American citizens, primarily to Europe and the USA. This movement of people has led to the global dissemination of individuals infected with T. cruzi. Therefore, cardiologists worldwide must familiarize themselves with Chagas disease and the severe, chronic manifestation - Chagas cardiomyopathy - because of the expanded prevalence of this disease beyond traditional endemic regions.

Genetic diversity in the partial sequence of the HIV-1 gag gene among people living with multidrug-resistant HIV-1 infection.

The group-specific antigen (gag) plays a crucial role in the assembly, release, and maturation of HIV. This study aimed to analyze the partial sequence of the HIV gag gene to classify HIV subtypes, identify recombination sites, and detect protease inhibitor (PI) resistance-associated mutations (RAMs). The cohort included 100 people living with HIV (PLH) who had experienced antiretroviral treatment failure with reverse transcriptase/protease inhibitors. Proviral HIV-DNA was successfully sequenced in 96 out of 100 samples for gag regions, specifically matrix (p17) and capsid (p24). Moreover, from these 96 sequences, 82 (85.42%) were classified as subtype B, six (6.25%) as subtype F1, one (1.04%) as subtype C, and seven (7.29%) exhibited a mosaic pattern between subtypes B and F1 (B/F1), with breakpoints at p24 protein. Insertions and deletions of amino acid at p17 were observed in 51 samples (53.13%). The prevalence of PI RAM in the partial gag gene was observed in 78 out of 96 PLH (81.25%). Among these cases, the most common mutations were R76K (53.13%), Y79F (31.25%), and H219Q (14.58%) at non-cleavage sites, as well as V128I (10.42%) and Y132F (11.46%) at cleavage sites. While B/F1 recombination was identified in the p24, the p17 coding region showed higher diversity, where insertions, deletions, and PI RAM, were observed at high prevalence. In PLH with virological failure, the analysis of the partial gag gene could contribute to more accurate predictions in genotypic resistance to PIs. This can aid guide more effective HIV treatment strategies.

Ocular manifestations of Monkeypox virus (MPXV) infection with viral persistence in ocular samples: A case series.

OBJECTIVE: We describe the clinical presentation and ocular viral dynamics in patients with Monkeypox virus-related ophthalmic disease (MPXROD). METHODS: In this case series, we investigated five consecutive patients with confirmed mpox, diagnosed through a positive Monkeypox virus (MPXV) Polymerase Chain Reaction (PCR) test and presenting with ocular symptoms. They were referred from the Reference Center for Sexually Transmitted Infections in São Paulo (CRT) to the Uveitis Sector at the Federal University of São Paulo, between August and December 2022. We performed PCR testing on ocular samples and culture supernatants for MPXV in all patients. Viral sequencing was conducted in one of the cases. RESULTS: Replicating MPXV was identified in at least one ocular sample of all patients, between day 31 and day 145 after the onset of skin lesions. All patients presented with keratitis, 3 with uveitis (60%) and two exhibited hypopyon (40%). The onset of ocular symptoms occurred at a mean of 21.2 days after the appearance of the first skin lesion and persisted, on average, for 61,.6 days, with a worsening trend observed until the initiation of tecovirimat treatment. Tecovirimat treatment was administered to all patients, with initiation occurring between 31 and 145 days after the onset of skin lesions. MPXV genome sequencing of an isolate from one patient classified it as belonging to lineage B1 in clade IIb. CONCLUSION: This study reveals a late onset and persistence of sight threatening ocular disease, along with potential viral infectivity even after systemic resolution in mpox cases. These findings highlight the risk of ongoing transmission from individuals with prolonged ocular manifestations, particularly through ocular discharge.

Human movement and environmental barriers shape the emergence of dengue.

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Nutraceutical blends predict enhanced health via microbiota reshaping improving cytokines and life quality: a Brazilian double-blind randomized trial.

Nutraceutical interventions supporting microbiota and eliciting clinical improvements in metabolic diseases have grown significantly. Chronic stress, gut dysbiosis, and metainflammation have emerged as key factors intertwined with sleep disorders, consequently exacerbating the decline in quality of life. This study aimed to assess the effects of two nutraceutical formulations containing prebiotics (fructooligosaccharides (FOS), galactooligosaccharides (GOS), yeast ß-glucans), minerals (Mg, Se, Zn), and the herbal medicine Silybum marianum L. Gaertn., Asteraceae (Milk thistle or Silymarin). These formulations, namely NSupple (without silymarin) and NSupple_Silybum (with silymarin) were tested over 180 days in overweight/obese volunteers from Brazil's southeastern region. We accessed fecal gut microbiota by partial 16S rRNA sequences; cytokines expression by CBA; anthropometrics, quality of life and sleep, as well as metabolic and hormonal parameters, at baseline (T0) and 180 days (T180) post-supplementation. Results demonstrated gut microbiota reshaping at phyla, genera, and species level post-supplementation. The Bacteroidetes phylum, Bacteroides, and Prevotella genera were positively modulated especially in the NSupple_Silybum group. Gut microbiota modulation was associated with improved sleep patterns, quality-of-life perception, cytokines expression, and anthropometric parameters post-supplementation. Our findings suggest that the nutraceutical blends positively enhance cardiometabolic and inflammatory markers. Particularly, NSupple_Silybum modulated microbiota composition, underscoring its potential significance in ameliorating metabolic dysregulation. Clinical trial registry number: NCT04810572. 23/03/2021.

Analysis of chlorhexidine, antibiotics and bacterial community composition in water environments from Brazil, Cameroon and Madagascar during the COVID-19 pandemic.

The widespread of chlorhexidine and antibiotics in the water bodies, which grew during the global COVID-19 pandemic, can increase the dispersion of antibiotic resistance. We assessed the occurrence of these pharmaceutical compounds as well as SARS-CoV-2 and analysed the bacterial community structure of hospital and urban wastewaters from Brazil, Cameroon, and Madagascar. Water and wastewater samples (n = 59) were collected between January-June 2022. Chlorhexidine, azithromycin, levofloxacin, ceftriaxone, gentamicin and meropenem were screened by Ultra-High-Performance Liquid Chromatography coupled with mass spectrometer. SARS-CoV-2 was detected based on the nucleocapsid gene (in Cameroon and Madagascar), and envelope and spike protein-encoding genes (in Brazil). The total community-DNA was extracted and used for bacterial community analysis based on the 16S rRNA gene. To unravel likely interaction between pharmaceutical compounds and/or SARS-CoV-2 with the water bacterial community, multivariate statistics were performed. Chlorhexidine was found in hospital wastewater effluent from Brazil with a maximum concentration value of 89.28 µg/L. Additionally, antibiotic residues such as azithromycin and levofloxacin were also present at concentrations between 0.32-7.37 µg/L and 0.11-118.91 µg/L, respectively. In Cameroon, azithromycin was the most found antibiotic present at concentrations from 1.14 to 1.21 µg/L. In Madagascar instead, ceftriaxone (0.68-11.53 µg/L) and levofloxacin (0.15-0.30 µg/L) were commonly found. The bacterial phyla statistically significant different (P < 0,05) among participating countries were Proteobacteria, Patescibacteria and Dependentiae which were mainly abundant in waters sampled in Africa and, other phyla such as Firmicutes, Campylobacterota and Fusobacteriota were more abundant in Brazil. The phylum Caldisericota was only found in raw hospital wastewater samples from Madagascar. The canonical correspondence analysis results suggest significant correlation of azithromycin, meropenem and levofloxacin with bacteria families such as Enterococcaceae, Flavobacteriaceae, Deinococcaceae, Thermacetogeniaceae and Desulfomonilaceae, Spirochaetaceae, Methanosaetaceae, Synergistaceae, respectively. Water samples were also positive for SARS-CoV-2 with the lowest number of hospitalized COVID-19 patients in Madagascar (n = 7) and Brazil (n = 30). Our work provides new data about the bacterial community profile and the presence of pharmaceutical compounds in the hospital effluents from Brazil, Cameroon, and Madagascar, whose limited information is available. These compounds can exacerbate the spreading of antibiotic resistance and therefore pose a risk to public health.

SARS-CoV-2 shedding, infectivity, and evolution in an immunocompromised adult patient.

This study aimed to provide further insight into the evolutionary dynamics of SARS-CoV-2 by analyzing the case of a 40-year-old man who had previously undergone autologous hematopoietic stem cell transplantation due to a diffuse large B-cell lymphoma. He developed a persistent SARS-CoV-2 infection lasting at least 218 days and did not manifest a humoral immune response to the virus during this follow-up period. Whole-genome sequencing and viral cultures confirmed a persistent infection with a replication-positive virus that had undergone genetic variation for at least 196 days after symptom onset.

Molecular Epidemiology of Mayaro Virus among Febrile Patients, Roraima State, Brazil, 2018-2021.

We detected Mayaro virus (MAYV) in 3.4% (28/822) of febrile patients tested during 2018-2021 from Roraima State, Brazil. We also isolated MAYV strains and confirmed that these cases were caused by genotype D. Improved surveillance is needed to better determine the burden of MAYV in the Amazon Region.

Temporal and spatial analysis of over 7,000 measles cases outbreak from 2018 to 2019 in the Brazilian Amazon.

OBJECTIVE: This study aimed to present a temporal and spatial analysis of the 2018 measles outbreak in Brazil, particularly in the metropolitan city of Manaus in the Amazon region, and further introduce a new tool for spatial analysis. METHODS: We analyzed the geographical data of the residences of over 7,000 individuals with measles in Manaus during 2018 and 2019. Spatial and temporal analyses were conducted to characterize various aspects of the outbreak, including the onset and prevalence of symptoms, demographics, and vaccination status. A visualization tool was also constructed to display the geographical and temporal distribution of the reported measles cases. RESULTS: Approximately 95% of the included participants had not received vaccination within the past decade. Heterogeneity was observed across all facets of the outbreak, including variations in the incubation period and symptom presentation. Age distribution exhibited two peaks, occurring at one year and 18 years of age, and the potential implications of this distribution on predictive analysis were discussed. Additionally, spatial analysis revealed that areas with the highest case densities tended to have the lowest standard of living. CONCLUSION: Understanding the spatial and temporal spread of measles outbreaks provides insights for decision-making regarding measures to mitigate future epidemics.

Modulation of the gut microbiome and Firmicutes phylum reduction by a nutraceutical blend in the obesity mouse model and overweight humans: A double-blind clinical trial.

Overweight and obesity are closely linked to gut dysbiosis/dysmetabolism and disrupted De-Ritis ratio [aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio], which may contribute to chronic noncommunicable diseases onset. Concurrently, extensive research explores nutraceuticals, and health-enhancing supplements, for disease prevention or treatment. Thus, sedentary overweight volunteers were double-blind randomized into two groups: Novel Nutraceutical_(S) (without silymarin) and Novel Nutraceutical (with silymarin). Experimental formulations were orally administered twice daily over 180 consecutive days. We evaluated fecal gut microbiota, based on partial 16S rRNA sequences, biochemistry and endocrine markers, steatosis biomarker (AST/ALT ratio), and anthropometric parameters. Post-supplementation, only the Novel Nutraceutical group reduced Clostridium clostridioforme (Firmicutes), Firmicutes/Bacteroidetes ratio (F/B ratio), and De-Ritis ratio, while elevating Bacteroides caccae and Bacteroides uniformis (Bacteroidetes) in Brazilian sedentary overweight volunteers after 180 days. In summary, the results presented here allow us to suggest the gut microbiota as the action mechanism of the Novel Nutraceutical promoting metabolic hepatic recovery in obesity/overweight non-drug interventions.

Machine learning for predicting Chagas disease infection in rural areas of Brazil.

INTRODUCTION: Chagas disease is a severe parasitic illness that is prevalent in Latin America and often goes unaddressed. Early detection and treatment are critical in preventing the progression of the illness and its associated life-threatening complications. In recent years, machine learning algorithms have emerged as powerful tools for disease prediction and diagnosis. METHODS: In this study, we developed machine learning algorithms to predict the risk of Chagas disease based on five general factors: age, gender, history of living in a mud or wooden house, history of being bitten by a triatomine bug, and family history of Chagas disease. We analyzed data from the Retrovirus Epidemiology Donor Study (REDS) to train five popular machine learning algorithms. The sample comprised 2,006 patients, divided into 75% for training and 25% for testing algorithm performance. We evaluated the model performance using precision, recall, and AUC-ROC metrics. RESULTS: The Adaboost algorithm yielded an AUC-ROC of 0.772, a precision of 0.199, and a recall of 0.612. We simulated the decision boundary using various thresholds and observed that in this dataset a threshold of 0.45 resulted in a 100% recall. This finding suggests that employing such a threshold could potentially save 22.5% of the cost associated with mass testing of Chagas disease. CONCLUSION: Our findings highlight the potential of applying machine learning to improve the sensitivity and effectiveness of Chagas disease diagnosis and prevention. Furthermore, we emphasize the importance of integrating socio-demographic and environmental factors into neglected disease prediction models to enhance their performance.

Temporal trends of severity and outcomes of critically ill patients with COVID-19 after the emergence of variants of concern: A comparison of two waves.

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.

Pathophysiology of chikungunya virus infection associated with fatal outcomes.

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes acute, subacute, and chronic human arthritogenic diseases and, in rare instances, can lead to neurological complications and death. Here, we combined epidemiological, virological, histopathological, cytokine, molecular dynamics, metabolomic, proteomic, and genomic analyses to investigate viral and host factors that contribute to chikungunya-associated (CHIK) death. Our results indicate that CHIK deaths are associated with multi-organ infection, central nervous system damage, and elevated serum levels of pro-inflammatory cytokines and chemokines compared with survivors. The histopathologic, metabolite, and proteomic signatures of CHIK deaths reveal hemodynamic disorders and dysregulated immune responses. The CHIKV East-Central-South-African lineage infecting our study population causes both fatal and survival cases. Additionally, CHIKV infection impairs the integrity of the blood-brain barrier, as evidenced by an increase in permeability and altered tight junction protein expression. Overall, our findings improve the understanding of CHIK pathophysiology and the causes of fatal infections.

Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic.

Introduction: The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency. Methods: At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output. Results: Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19. Discussion: Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.

An electrochemical genomagnetic assay for detection of SARS-CoV-2 and Influenza A viruses in saliva.

Viral respiratory infections represent a major threat to the population's health globally. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 disease and in some cases the symptoms can be confused with Influenza disease caused by the Influenza A viruses. A simple, fast, and selective assay capable of identifying the etiological agent and differentiating the diseases is essential to provide the correct clinical management to the patient. Herein, we described the development of a genomagnetic assay for the selective capture of viral RNA from SARS-CoV-2 and Influenza A viruses in saliva samples and employing a simple disposable electrochemical device for gene detection and quantification. The proposed method showed excellent performance detecting RNA of SARS-CoV-2 and Influenza A viruses, with a limit of detection (LoD) and limit of quantification (LoQ) of 5.0 fmol L-1 and 8.6 fmol L-1 for SARS-CoV-2, and 1.0 fmol L-1 and 108.9 fmol L-1 for Influenza, respectively. The genomagnetic assay was employed to evaluate the presence of the viruses in 36 saliva samples and the results presented similar responses to those obtained by the real-time reverse transcription-polymerase chain reaction (RT-PCR), demonstrating the reliability and capability of a method as an alternative for the diagnosis of COVID-19 and Influenza with point-of-care capabilities.

Phylogenetics, Epidemiology and Temporal Patterns of Dengue Virus in Araraquara, São Paulo State.

Dengue virus (DENV) is a prominent arbovirus with global spread, causing approximately 390 million infections each year. In Brazil, yearly epidemics follow a well-documented pattern of serotype replacement every three to four years on average. Araraquara, located in the state of São Paulo, has faced significant impacts from DENV epidemics since the emergence of DENV-1 in 2010. The municipality then transitioned from low to moderate endemicity in less than 10 years. Yet, there remains an insufficient understanding of virus circulation dynamics, particularly concerning DENV-1, in the region, as well as the genetic characteristics of the virus. To address this, we sequenced 37 complete or partial DENV-1 genomes sampled from 2015 to 2022 in Araraquara. Then, using also Brazilian and worldwide DENV-1 sequences we reconstructed the evolutionary history of DENV-1 in Araraquara and estimated the time to the most recent common ancestor (tMRCA) for serotype 1, for genotype V and its main lineages. Within the last ten years, there have been at least three introductions of genotype V in Araraquara, distributed in two main lineages (L Ia and L Ib, and L II). The tMRCA for the first sampled lineage (2015/2016 epidemics) was approximately 15 years ago (in 2008). Crucially, our analysis challenges existing assumptions regarding the emergence time of the DENV-1 genotypes, suggesting that genotype V might have diverged more recently than previously described. The presence of the two lineages of genotype V in the municipality might have contributed to the extended persistence of DENV-1 in the region.

Tracking arboviruses, their transmission vectors and potential hosts by nanopore sequencing of mosquitoes.

The risk to human health from mosquito-borne viruses such as dengue, chikungunya and yellow fever is increasing due to increased human expansion, deforestation and climate change. To anticipate and predict the spread and transmission of mosquito-borne viruses, a better understanding of the transmission cycle in mosquito populations is needed. We present a pathogen-agnostic combined sequencing protocol for identifying vectors, viral pathogens and their hosts or reservoirs using portable Oxford Nanopore sequencing. Using mosquitoes collected in São Paulo, Brazil, we extracted RNA for virus identification and DNA for blood meal and mosquito identification. Mosquitoes and blood meals were identified by comparing cytochrome c oxidase I (COI) sequences against a curated Barcode of Life Data System (BOLD). Viruses were identified using the SMART-9N protocol, which allows amplified DNA to be prepared with native barcoding for nanopore sequencing. Kraken 2 was employed to detect viral pathogens and Minimap2 and BOLD identified the contents of the blood meal. Due to the high similarity of some species, mosquito identification was conducted using blast after generation of consensus COI sequences using RACON polishing. This protocol can simultaneously uncover viral diversity, mosquito species and mosquito feeding habits. It also has the potential to increase understanding of mosquito genetic diversity and transmission dynamics of zoonotic mosquito-borne viruses.

Impacts of the first wave of the COVID-19 pandemic on leisure and transportation physical activity among healthcare workers.

Introduction: The COVID-19 pandemic may lead to reduced physical activity (PA) in health care workers (HCWs). Objective: To evaluate leisure and transport-related PA in HCW of a COVID-19-dedicated hospital during the first wave of the COVID-19 pandemic. Methods: This is a cross-sectional study with a sample of 1,527 HCWs. Socioeconomic aspects, occupational characteristics, and engagement in leisure and transport-related PA were investigated through an online survey administered in August of 2020. Results: More than 80 % HCWs performed < 150 min/week of leisure-related PA, and 85 % performed ≤ 30 min/day transport-related PA. Being male was associated with more PA (OR: 1.93; 95 % CI:1.40-2.66) and transport-related PA; working in nursing, physical therapy, and cleaning/housekeeping services was associated with low PA (OR: 0.70; 95 % CI:0.51-0.95). Physicians and administrative staff were less active in transport-related PA. Conclusions: HCWs working in a COVID-19 hospital had low levels of PA in the domains of leisure and transportation.

The Brazilian COVID-19 vaccination campaign: a modelling analysis of sociodemographic factors on uptake.

OBJECTIVE: Dose shortages delayed access to COVID-19 vaccination. We aim to characterise inequality in two-dose vaccination by sociodemographic group across Brazil. DESIGN: This is a cross-sectional study. SETTING: We used data retrieved from the Brazilian Ministry of Health databases published between 17 January 2021 and 6 September 2021. METHODS: We assessed geographical inequalities in full vaccination coverage and dose by age, sex, race and socioeconomic status. We developed a Campaign Optimality Index to characterise inequality in vaccination access due to premature vaccination towards younger populations before older and vulnerable populations were fully vaccinated. Generalised linear regression was used to investigate the risk of death and hospitalisation by age group, socioeconomic status and vaccination coverage. RESULTS: Vaccination coverage is higher in the wealthier South and Southeast. Men, people of colour and low-income groups were more likely to be only partially vaccinated due to missing or delaying a second dose. Vaccination started prematurely for age groups under 50 years which may have hindered uptake in older age groups. Vaccination coverage was associated with a lower risk of death, especially in older age groups (ORs 9.7 to 29.0, 95% CI 9. 4 to 29.9). Risk of hospitalisation was greater in areas with higher vaccination rates due to higher access to care and reporting. CONCLUSIONS: Vaccination inequality persists between states, age and demographic groups despite increasing uptake. The association between hospitalisation rates and vaccination is attributed to preferential delivery to areas of greater transmission and access to healthcare.