Persistent high mortality rates for Diabetes Mellitus and Hypertension after excluding deaths associated with COVID-19 in Brazil, 2020-2022.

INTRODUCTION: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a significant public health challenge globally, with Brazil being no exception. Excess mortality during this period reached alarming levels. Cardiovascular diseases (CVD), Systemic Hypertension (HTN), and Diabetes Mellitus (DM) were associated with increased mortality. However, the specific impact of DM and HTN on mortality during the pandemic remains poorly understood. METHODS: This study analyzed mortality data from Brazil's mortality system, covering the period from 2015 to 2022. Data included all causes of death as listed on death certificates, categorized by International Classification of Diseases 10th edition (ICD-10) codes. Population data were obtained from the Brazilian Census. Mortality ratios (MRs) were calculated by comparing death rates in 2020, 2021, and 2022 to the average rates from 2015 to 2019. Adjusted MRs were calculated using Poisson models. RESULTS: Between 2015 and 2022, Brazil recorded a total of 11,423,288 deaths. Death rates remained relatively stable until 2019 but experienced a sharp increase in 2020 and 2021. In 2022, although a decrease was observed, it did not return to pre-pandemic levels. This trend persisted even when analyzing records mentioning DM, HTN, or CVD. Excluding death certificates mentioning COVID-19 codes, the trends still showed increases from 2020 through 2022, though less pronounced. CONCLUSION: This study highlights the persistent high mortality rates for DM and HTN in Brazil during the years 2020-2022, even after excluding deaths associated with COVID-19. These findings emphasize the need for continued attention to managing and preventing DM and HTN as part of public health strategies, both during and beyond the COVID-19 pandemic. There are complex interactions between these conditions and the pandemic's impact on mortality rates.

Was the COVID-19 epidemic synchronous in space? An analysis in the health regions of the Rio de Janeiro state, 2020-2022.

OBJECTIVE: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. METHODS: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. RESULTS: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. CONCLUSION: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.

Integrated environmental assessment of iron ore tailings in floodplain soils and plants after the Fundão Dam disaster in Brazil.

Previous studies of the Doce River basin (Brazil) seem to be contradictory regarding the contamination of soils with potentially harmful elements (PHE). This research aimed to perform an integrated assessment of PHE in the soil-plant-tailing system from the area most affected by the iron waste after the Fundão Dam disaster in 2015. Different fractions of PHE (exchangeable, nonexchangeable, reducible, and pseudo-total) were determined on deposited iron waste (DIW), soil waste mixture (SWM), and control soil (CS) samples. Total contents of PHE in Poaceae were also determined, and Allium cepa bioassays were performed to determine DIW and CS cytotoxicity and/or genotoxicity to plants. The Fe and Mn contaminations were the only ones related to the deposition of DIW on floodplains, and other harmful element content (such as As, Hg, Ni, Cd, Cr, and Pb) was not found above baseline values for soils. In addition, a significant part of the Fe and Mn in DIW is readily available or subject to acidification and prolonged flood reduction processes. The high available content of Fe favored its excessive accumulation by Brachiaria. The DIW chemical conditions reduced biological functions of A. cepa under a controlled environment. However, more drastic effects, such as genetic damage, were not seen. The postdisaster action of covering DIW with CS resulted in undesirable enrichment of Pb on the floodplain soils. The integrated results allow the conclusion that the iron waste is not a time bomb for PHE contamination of soils between the Fundão and Risoleta Neves Hydroelectric Dam (~100 km away from Fundão). Integr Environ Assess Manag 2024;20:117-132. © 2023 SETAC.

The Association Between Prepandemic ICU Performance and Mortality Variation in COVID-19: A Multicenter Cohort Study of 35,619 Critically Ill Patients.

BACKGROUND: During the COVID-19 pandemic, ICUs remained under stress and observed elevated mortality rates and high variations of outcomes. A knowledge gap exists regarding whether an ICU performing best during nonpandemic times would still perform better when under high pressure compared with the least performing ICUs. RESEARCH QUESTION: Does prepandemic ICU performance explain the risk-adjusted mortality variability for critically ill patients with COVID-19? STUDY DESIGN AND METHODS: This study examined a cohort of adults with real-time polymerase chain reaction-confirmed COVID-19 admitted to 156 ICUs in 35 hospitals from February 16, 2020, through December 31, 2021, in Brazil. We evaluated crude and adjusted in-hospital mortality variability of patients with COVID-19 in the ICU during the pandemic. Association of baseline (prepandemic) ICU performance and in-hospital mortality was examined using a variable life-adjusted display (VLAD) during the pandemic and a multivariable mixed regression model adjusted by clinical characteristics, interaction of performance with the year of admission, and mechanical ventilation at admission. RESULTS: Thirty-five thousand six hundred nineteen patients with confirmed COVID-19 were evaluated. The median age was 52 years, median Simplified Acute Physiology Score 3 was 42, and 18% underwent invasive mechanical ventilation. In-hospital mortality was 13% and 54% for those receiving invasive mechanical ventilation. Adjusted in-hospital mortality ranged from 3.6% to 63.2%. VLAD in the most efficient ICUs was higher than the overall median in 18% of weeks, whereas VLAD was 62% and 84% in the underachieving and least efficient groups, respectively. The least efficient baseline ICU performance group was associated independently with increased mortality (OR, 2.30; 95% CI, 1.45-3.62) after adjusting for patient characteristics, disease severity, and pandemic surge. INTERPRETATION: ICUs caring for patients with COVID-19 presented substantial variation in risk-adjusted mortality. ICUs with better baseline (prepandemic) performance showed reduced mortality and less variability. Our findings suggest that achieving ICU efficiency by targeting improvement in organizational aspects of ICUs may impact outcomes, and therefore should be a part of the preparedness for future pandemics.

Development and validation of a machine learning model to predict the use of renal replacement therapy in 14,374 patients with COVID-19.

PURPOSE: To develop a model to predict the use of renal replacement therapy (RRT) in COVID-19 patients. MATERIALS AND METHODS: Retrospective analysis of multicenter cohort of intensive care unit (ICU) admissions of Brazil involving COVID-19 critically adult patients, requiring ventilatory support, admitted to 126 Brazilian ICUs, from February 2020 to December 2021 (development) and January to May 2022 (validation). No interventions were performed. RESULTS: Eight machine learning models' classifications were evaluated. Models were developed using an 80/20 testing/train split ratio and cross-validation. Thirteen candidate predictors were selected using the Recursive Feature Elimination (RFE) algorithm. Discrimination and calibration were assessed. Temporal validation was performed using data from 2022. Of 14,374 COVID-19 patients with initial respiratory support, 1924 (13%) required RRT. RRT patients were older (65 [53-75] vs. 55 [42-68]), had more comorbidities (Charlson's Comorbidity Index 1.0 [0.00-2.00] vs 0.0 [0.00-1.00]), had higher severity (SAPS-3 median: 61 [51-74] vs 48 [41-58]), and had higher in-hospital mortality (71% vs 22%) compared to non-RRT. Risk factors for RRT, such as Creatinine, Glasgow Coma Scale, Urea, Invasive Mechanical Ventilation, Age, Chronic Kidney Disease, Platelets count, Vasopressors, Noninvasive Ventilation, Hypertension, Diabetes, modified frailty index (mFI) and Gender, were identified. The best discrimination and calibration were found in the Random Forest (AUC [95%CI]: 0.78 [0.75-0.81] and Brier's Score: 0.09 [95%CI: 0.08-0.10]). The final model (Random Forest) showed comparable performance in the temporal validation (AUC [95%CI]: 0.79 [0.75-0.84] and Brier's Score, 0.08 [95%CI: 0.08-0.1]). CONCLUSIONS: An early ML model using easily available clinical and laboratory data accurately predicted the use of RRT in critically ill patients with COVID-19. Our study demonstrates that using ML techniques is feasible to provide early prediction of use of RRT in COVID-19 patients.

Was the COVID-19 epidemic synchronous in space? An analysis in the health regions of the Rio de Janeiro state, 2020-2022 / A epidemia de COVID-19 foi síncrona no espaço? Uma análise nas regiões de saúde do estado do Rio de Janeiro, 2020-2022

ABSTRACT Objective: To analyze the spatio-temporal dynamics of COVID-19 in the Rio de Janeiro state within the nine health regions, between March 2020 and December 2022. Methods: The Poisson model with random effects was used to smooth and estimate the incidence of COVID-19 hospitalizations reported in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) to verify the synchronicity of the epidemic in the state. Results: The COVID-19 epidemic in the state is characterized by the presence of seven peaks during the analyzed period corresponding to seven found. An asynchrony in hospitalizations was identified, varying according to the different virus variants in the nine health regions of the state. The incidence peaks of hospitalizations ranged from 1 to 12 cases per 100,000 inhabitants during the pandemic. Conclusion: This spatio-temporal analysis is applicable to other scenarios, enabling monitoring and decision-making for the control of epidemic diseases in different areas.

RESUMO Objetivo: Analisar a dinâmica espaço-temporal de COVID-19 no estado do Rio de Janeiro nas nove regiões de saúde, entre março de 2020 e dezembro de 2022. Métodos: Utilizou-se o modelo de Poisson com efeitos aleatórios para suavizar a curva de incidência de hospitalizações por COVID-19 notificadas no Sistema de Informação da Vigilância Epidemiológica da Gripe (Sivep-Gripe) para verificar a sincronicidade da epidemia no estado. Resultados: A epidemia de COVID-19 no estado é caracterizada pela presença de sete picos no período analisado correspondentes a sete variantes encontradas. Identificou-se uma assincronicidade nas hospitalizações, variando de acordo com as diferentes variantes do vírus nas nove regiões de saúde do estado. Os picos de incidência das hospitalizações variaram de 1 a 12 casos por 100 mil habitantes no decorrer da pandemia. Conclusão: Essa análise espaço-temporal é extensível em outros cenários, sendo possível o monitoramento e a tomada de decisões de controle de doenças epidêmicas em várias áreas.

Joint spatial modeling of the risks of co-circulating mosquito-borne diseases in Ceará, Brazil.

Mosquito-borne diseases such as dengue and chikungunya have been co-circulating in the Americas, causing great damage to the population. In 2021, for instance, almost 1.5 million cases were reported on the continent, being Brazil the responsible for most of them. Even though they are transmitted by the same mosquito, it remains unclear whether there exists a relationship between both diseases. In this paper, we model the geographic distributions of dengue and chikungunya over the years 2016 to 2021 in the Brazilian state of Ceará. We use a Bayesian hierarchical spatial model for the joint analysis of two arboviruses that includes spatial covariates as well as specific and shared spatial effects that take into account the potential autocorrelation between the two diseases. Our findings allow us to identify areas with high risk of one or both diseases. Only 7% of the areas present high relative risk for both diseases, which suggests a competition between viruses. This study advances the understanding of the geographic patterns and the identification of risk factors of dengue and chikungunya being able to help health decision-making.

Neurobehavioral effects of fungicides in zebrafish: a systematic review and meta-analysis.

Pesticides are widely used in global agriculture to achieve high productivity levels. Among them, fungicides are specifically designed to inhibit fungal growth in crops and seeds. However, their application often results in environmental contamination, as these chemicals can persistently be detected in surface waters. This poses a potential threat to non-target organisms, including humans, that inhabit the affected ecosystems. In toxicologic research, the zebrafish (Danio rerio) is the most commonly used fish species to assess the potential effects of fungicide exposure, and numerous and sometimes conflicting findings have been reported. To address this, we conducted a systematic review and meta-analysis focusing on the neurobehavioral effects of fungicides in zebrafish. Our search encompassed three databases (PubMed, Scopus, and Web of Science), and the screening process followed predefined inclusion/exclusion criteria. We extracted qualitative and quantitative data, as well as assessed reporting quality, from 60 included studies. Meta-analyses were performed for the outcomes of distance traveled in larvae and adults and spontaneous movements in embryos. The results revealed a significant overall effect of fungicide exposure on distance, with a lower distance traveled in the exposed versus control group. No significant effect was observed for spontaneous movements. The overall heterogeneity was high for distance and moderate for spontaneous movements. The poor reporting practices in the field hindered a critical evaluation of the studies. Nevertheless, a sensitivity analysis did not identify any studies skewing the meta-analyses. This review underscores the necessity for better-designed and reported experiments in this field.

Registration with Primary Health Care and COVID-19 mortality: cohort of diabetics from five administrative health regions in the city of Rio de Janeiro, Brazil, 2020-2021. / Cadastro na Atenção Primária e mortalidade por COVID-19: coorte de diabéticos de cinco regiões administrativas de saúde do município do Rio de Janeiro, 2020­2021.

OBJECTIVE: The present study carried out an analysis of survival according to the status of registration with Primary Health Care (PHC) and of factors associated with death from COVID-19, in cases residing in Programmatic Area 3.1 (PA3.1) with a diagnosis of diabetes (in the notification form or in the electronic medical record), of the Municipality of Rio de Janeiro (RJ), Brazil, in 2020-2021. METHODS: A probabilistic linkage of databases was performed based on information on cases notified as COVID-19 and data from the electronic medical records of people living with diabetes. A survival analysis was carried out, using the Cox regression model stratified by age group and adjusted for confounding variables. RESULTS: Individuals registered with the PHC of PA3.1 had almost twice the risk of death from COVID-19 (adjusted hazard ratio [HRadj]=1.91) when compared to those unregistered. This association was stronger in individuals aged 18 to 59 years registered with the PHC (HRadj=2.82) than in individuals aged 60 years or over (HRadj=1.56). CONCLUSION: Surveillance strategies for identifying and adequately monitoring higher-risk groups, among individuals living with diabetes, within the scope of Primary Health Care, can contribute to reducing mortality from COVID-19.

OBJETIVO: O presente estudo realizou uma análise de sobrevivência segundo situação de cadastro na Atenção Primária à Saúde (APS) e de fatores associados ao óbito por COVID-19, nos casos residentes da Área Programática 3.1 (AP3.1) com diagnóstico de diabetes (na ficha de notificação ou no prontuário eletrônico) do município do Rio de Janeiro, em 2020­2021. MÉTODOS: Foi realizado relacionamento probabilístico de bases de dados com base nas informações dos casos notificados por COVID-19 e dos dados de prontuário eletrônico de pessoas que vivem com diabetes. Conduziu-se uma análise de sobrevivência, utilizando-se o modelo de regressão de Cox estratificado por faixa etária e ajustando-se por variáveis confundidoras. RESULTADOS: Verificou-se que indivíduos cadastrados na APS da AP3.1 possuíam risco quase duas vezes maior de óbito por COVID-19 (hazard ratio ajustada ­ HRaj=1,91) quando comparados aos não cadastrados na APS da AP3.1. Essa associação foi mais forte naqueles com 18 a 59 anos, cadastrados na APS (HRaj=2,82), do que nos de 60 anos ou mais (HRaj=1,56). CONCLUSÃO: Estratégias de vigilância para a identificação e acompanhamento adequado de grupos de maior risco de mortalidade, dentre indivíduos que vivem com DM, no âmbito da APS podem contribuir para a redução da mortalidade em decorrência da COVID-19.

Systematic review and meta-analysis of 10 years of unpredictable chronic stress in zebrafish.

The zebrafish (Danio rerio) is a model animal that is being increasingly used in neuroscience research. A decade ago, the first study on unpredictable chronic stress (UCS) in zebrafish was published, inspired by protocols established for rodents in the early 1980s. Since then, several studies have been published by different groups, in some cases with conflicting results. Here we conducted a systematic review to identify studies evaluating the effects of UCS in zebrafish and meta-analytically synthetized the data of neurobehavioral outcomes and relevant biomarkers. Literature searches were performed in three databases (PubMed, Scopus and Web of Science) with a two-step screening process based on inclusion/exclusion criteria. The included studies underwent extraction of qualitative and quantitative data, as well as risk-of-bias assessment. Outcomes of included studies (n = 38) were grouped into anxiety/fear-related behavior, locomotor function, social behavior or cortisol level domains. UCS increased anxiety/fear-related behavior and cortisol levels while decreasing locomotor function, but a significant summary effect was not observed for social behavior. Despite including a substantial number of studies, the high heterogeneity and the methodological and reporting problems evidenced in the risk-of-bias analysis made it difficult to assess the internal validity of most studies and the overall validity of the model. Our review thus evidences the need to conduct well-designed experiments to better evaluate the effects of UCS on diverse behavioral patterns displayed by zebrafish.

SARS-CoV-2 Reinfection Cases in a Household-Based Prospective Cohort in Rio de Janeiro.

This was a household-based prospective cohort study conducted in Rio de Janeiro, in which people with laboratory-confirmed coronavirus disease 2019 (COVID-19) and their household contacts were followed from April 2020 through June 2022. Ninety-eight reinfections were identified, with 71 (72.5%) confirmed by genomic analyses and lineage definition in both infections. During the pre-Omicron period, 1 dose of any COVID-19 vaccine was associated with a reduced risk of reinfection, but during the Omicron period not even booster vaccines had this effect. Most reinfections were asymptomatic or milder in comparison with primary infections, a justification for continuing active surveillance to detect infections in vaccinated individuals. Our findings demonstrated that vaccination may not prevent infection or reinfection with severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). Therefore we highlight the need to continuously update the antigenic target of SARS CoV-2 vaccines and administer booster doses to the population regularly, a strategy well established in the development of vaccines for influenza immunization programs.

Genotypic and Phenotypic Characterization of Antimicrobial and Heavy Metal Tolerance in Salmonella enterica and Escherichia coli Isolates from Swine Feed Mills.

Antimicrobials and heavy metals are commonly used in the animal feed industry. The role of in-feed antimicrobials on the evolution and persistence of resistance in enteric bacteria is not well described. Whole-Genome Sequencing (WGS) is widely used for genetic characterizations of bacterial isolates, including antimicrobial resistance, heavy metal tolerance, virulence factors, and relatedness to other sequenced isolates. The goals of this study were to i) use WGS to characterize Salmonella enterica (n = 33) and Escherichia coli (n = 30) isolated from swine feed and feed mill environments; and ii) investigate their genotypic and phenotypic antimicrobial and heavy metal tolerance. Salmonella isolates belonged to 10 serovars, the most common being Cubana, Senftenberg, and Tennessee. E. coli isolates were grouped into 22 O groups. Phenotypic resistance to at least one antimicrobial was observed in 19 Salmonella (57.6%) and 17 E. coli (56.7%) isolates, whereas multidrug resistance (resistant to ≥3 antimicrobial classes) was observed in four Salmonella (12%) and two E. coli (7%) isolates. Antimicrobial resistance genes were identified in 17 Salmonella (51%) and 29 E. coli (97%), with 11 and 29 isolates possessing genes conferring resistance to multiple antimicrobial classes. Phenotypically, 53% Salmonella and 58% E. coli presented resistance to copper and arsenic. All isolates that possessed the copper resistance operon were resistant to the highest concentration tested (40 mM). Heavy metal tolerance genes to copper and silver were present in 26 Salmonella isolates. Our study showed a strong agreement between predicted and measured resistances when comparing genotypic and phenotypic data for antimicrobial resistance, with an overall concordance of 99% and 98.3% for Salmonella and E. coli, respectively.

The Role of Children in Household Transmission of SARS-CoV-2 Across Four Waves of the Pandemic.

BACKGROUND: It is important to understand the dynamics of SARS-CoV-2 transmission in close-contact settings such as households. We hypothesized that children would most often acquire SARS-CoV-2 from a symptomatic adult caregiver. METHODS: This prospective cohort study was conducted from April 2020 to July 2022 in a low-resource, urban settlement in Brazil. We recruited families who brought their children to a public clinic. We collected nasopharyngeal and oral swabs from household members and tracked symptoms and vaccination. RESULTS: In total, 1256 participants in 298 households were tested for SARS-CoV-2. A total of 4073 RT-PCR tests were run with 893 SARS-CoV-2 positive results (21.9%). SARS-CoV-2 cases were defined as isolated cases (N = 158) or well-defined transmission events (N = 175). The risk of household transmission was lower if the index case was a child (OR: 0.3 [95% CI: 0.16-0.55], P < .001) or was vaccinated (OR: 0.29 [95% CI: 0.1-0.85], P = .024), and higher if the index was symptomatic (OR: 2.53 [95% CI: 1.51-4.26], P < .001). The secondary attack rate for child index cases to child contacts was 0.29, whereas the secondary attack rate for adult index cases to child contacts was 0.47 (P = .08). CONCLUSIONS: In this community, children were significantly less infectious to their household contacts than adolescents or adults. Most children were infected by a symptomatic adult, usually their mother. There was a double benefit of vaccination as it protected the vaccine from severe illness and prevented onward transmission to household contacts. Our findings may also be valid for similar populations throughout Latin America.

The spatio-temporal distribution of acute encephalitis syndrome and its association with climate and landcover in Vietnam.

BACKGROUND: Acute encephalitis syndrome (AES) differs in its spatio-temporal distribution in Vietnam with the highest incidence seen during the summer months in the northern provinces. AES has multiple aetiologies, and the cause remains unknown in many cases. While vector-borne disease such as Japanese encephalitis and dengue virus and non-vector-borne diseases such as influenza and enterovirus show evidence of seasonality, associations with climate variables and the spatio-temporal distribution in Vietnam differs between these. The aim of this study was therefore to understand the spatio-temporal distribution of, and risk factors for AES in Vietnam to help hypothesise the aetiology. METHODS: The number of monthly cases per province for AES, meningitis and diseases including dengue fever; influenza-like-illness (ILI); hand, foot, and mouth disease (HFMD); and Streptococcus suis were obtained from the General Department for Preventive Medicine (GDPM) from 1998-2016. Covariates including climate, normalized difference vegetation index (NDVI), elevation, the number of pigs, socio-demographics, JEV vaccination coverage and the number of hospitals were also collected. Spatio-temporal multivariable mixed-effects negative binomial Bayesian models with an outcome of the number of cases of AES, a combination of the covariates and harmonic terms to determine the magnitude of seasonality were developed. RESULTS: The national monthly incidence of AES declined by 63.3% over the study period. However, incidence increased in some provinces, particularly in the Northwest region. In northern Vietnam, the incidence peaked in the summer months in contrast to the southern provinces where incidence remained relatively constant throughout the year. The incidence of meningitis, ILI and S. suis infection; temperature, relative humidity with no lag, NDVI at a lag of one month, and the number of pigs per 100,000 population were positively associated with the number of cases of AES in all models in which these covariates were included. CONCLUSIONS: The positive correlation of AES with temperature and humidity suggest that a number of cases may be due to vector-borne diseases, suggesting a need to focus on vaccination campaigns. However, further surveillance and research are recommended to investigate other possible aetiologies such as S. suis or Orientia tsutsugamushi.

Industrial wastewater treatment by plant-based bio-filtration.

Constructed wetlands (CWs) represent a natural wastewater treatment process, offering economic and environmental advantages. These systems can remove several components that may cause negative impacts on the environment. Media types and plant species are crucial influencing factors for the removal of contaminants in CWs. The goal of this study is to evaluate the capacity of a CW using Tamarix spp. with three filter media to treat FGD wastewater. Planted and unplanted CWs were set up with varying types of biofilm support media: 3 bioreactors were operated with 50% gravel and 50% zeolite (v/v), 3 with 100% gravel, and 3 with 50% gravel, 25% zeolite, and 25% silage. Planted CWs had the greatest potential to reduce the concentrations of B, K, and NH4+-N in 64.9%, 91.1%, and 92.5%, respectively, when used in addition to the filter composed by 50% gravel + 50% zeolite, which was the only media keeping the plants alive for 60 days. The results showed that the optimal selection of filter media depends on the purpose for which the treatment has been projected for, considering that the types of substrates influenced the nature of the contaminant removal in the CW.

Salinity impact on Constructed wetlands (CWs) is still scarce in the literature. The novelty is the choice of a salt cedar (Tamarix spp.) combined with three filter media types ((1) gravel; (2) gravel and zeolite; (3) gravel, zeolite, and silage) to treat flue gas desulfurization wastewater in CWs. Our findings demonstrate that filter media containing 50% gravel + 50% zeolite can decrease the toxicity of contaminants from FGD wastewater in plants.

Effectiveness of a multicomponent intervention to face the COVID-19 pandemic in Rio de Janeiro's favelas: difference-in-differences analysis.

INTRODUCTION: Few community-based interventions addressing the transmission control and clinical management of COVID-19 cases have been reported, especially in poor urban communities from low-income and middle-income countries. Here, we analyse the impact of a multicomponent intervention that combines community engagement, mobile surveillance, massive testing and telehealth on COVID-19 cases detection and mortality rates in a large vulnerable community (Complexo da Maré) in Rio de Janeiro, Brazil. METHODS: We performed a difference-in-differences (DID) analysis to estimate the impact of the multicomponent intervention in Maré, before (March-August 2020) and after the intervention (September 2020 to April 2021), compared with equivalent local vulnerable communities. We applied a negative binomial regression model to estimate the intervention effect in weekly cases and mortality rates in Maré. RESULTS: Before the intervention, Maré presented lower rates of reported COVID-19 cases compared with the control group (1373 vs 1579 cases/100 000 population), comparable mortality rates (309 vs 287 deaths/100 000 population) and higher case fatality rates (13.7% vs 12.2%). After the intervention, Maré displayed a 154% (95% CI 138.6% to 170.4%) relative increase in reported case rates. Relative changes in reported death rates were -60% (95% CI -69.0% to -47.9%) in Maré and -28% (95% CI -42.0% to -9.8%) in the control group. The case fatality rate was reduced by 77% (95% CI -93.1% to -21.1%) in Maré and 52% (95% CI -81.8% to -29.4%) in the control group. The DID showed a reduction of 46% (95% CI 17% to 65%) of weekly reported deaths and an increased 23% (95% CI 5% to 44%) of reported cases in Maré after intervention onset. CONCLUSION: An integrated intervention combining communication, surveillance and telehealth, with a strong community engagement component, could reduce COVID-19 mortality and increase case detection in a large vulnerable community in Rio de Janeiro. These findings show that investment in community-based interventions may reduce mortality and improve pandemic control in poor communities from low-income and middle-income countries.