Impact of the first year of COVID-19 vaccination strategy in Brazil: an ecological study.

OBJECTIVES: No consensus exists about the best COVID-19 vaccination strategy to be adopted by low-income and middle-income countries. Brazil adopted an age-based calendar strategy to reduce mortality and the burden on the healthcare system. This study evaluates the impact of the vaccination campaign in Brazil on the progression of the reported COVID-19 deaths. METHODS: This ecological study analyses the dynamic of vaccination coverage and COVID-19 deaths in hospitalised adults (≥20 years) during the first year of the COVID-19 vaccination roll-out (January to December 2021) using nationwide data (DATASUS). We stratified the adult population into 20-49, 50-59, 60-69 and 70+ years. The dynamic effect of the vaccination campaign on mortality rates was estimated by applying a negative binomial regression. The prevented and possible preventable deaths (observed deaths higher than expected) and potential years of life lost (PYLL) for each age group were obtained in a counterfactual analysis. RESULTS: During the first year of COVID-19 vaccination, 266 153 517 doses were administered, achieving 91% first-dose coverage. A total of 380 594 deaths were reported, 154 091 (40%) in 70+ years and 136 804 (36%) from 50-59 or 20-49 years. The mortality rates of 70+ decreased by 52% (rate ratio [95% CI]: 0.48 [0.43-0.53]) in 6 months, whereas rates for 20-49 were still increasing due to low coverage (52%). The vaccination roll-out strategy prevented 59 618 deaths, 53 088 (89%) from those aged 70+ years. However, the strategy did not prevent 54 797 deaths, 85% from those under 60 years, being 26 344 (45%) only in 20-49, corresponding to 1 589 271 PYLL, being 1 080 104 PYLL (68%) from those aged 20-49 years. CONCLUSION: The adopted aged-based calendar vaccination strategy initially reduced mortality in the oldest but did not prevent the deaths of the youngest as effectively as compared with the older age group. Countries with a high burden, limited vaccine supply and young populations should consider other factors beyond the age to prioritise who should be vaccinated first.

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.

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.

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.

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.

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.

Effects of Tranexamic Acid in Patients with Subarachnoid Hemorrhage in Brazil: A Prospective Observational Study with Propensity Score Analysis.

BACKGROUND: Rebleeding from a ruptured aneurysm increases the risk of unfavorable outcomes after subarachnoid hemorrhage (SAH) and is prevented by early aneurysm occlusion. The role of antifibrinolytics before aneurysm obliteration remains controversial. We investigated the effects of tranexamic acid on long-term functional outcomes of patients with aneurysmal SAH (aSAH). METHODS: This was a single-center, prospective, observational study conducted in a high-volume tertiary hospital in a middle-income country from December 2016 to February 2020. We included all consecutive patients with aSAH who either received or did not receive tranexamic acid (TXA) treatment. Multivariate logistic regression analysis using propensity score was used to evaluate the association of TXA use with long-term functional outcomes, measured by the modified Rankin Scale (mRS) at 6 months. RESULTS: A total of 230 patients with aSAH were analyzed. The median (interquartile range) age was 55 (46-63) years, 72% were women, 75% presented with good clinical grade (World Federation of Neurological Surgeons grade 1-3), and 83% had a Fisher scale of 3 or 4. Around 80% of patients were admitted up to 72 h from ictus. The aneurysm occlusion method was surgical clipping in 80% of the patients. A total of 129 patients (56%) received TXA. In multivariable logistic regression using inverse probability treatment weighting, the long-term rate of unfavorable outcomes (modified Rankin scale 4-6) was the same in the TXA and non-TXA groups (61 [48%] in TXA group vs. 33 [33%] in non-TXA group; odds ratio [OR] 1.39, 95% confidence interval [CI] 0.67-2.92; p = 0.377). The TXA group had higher in-hospital mortality (33 vs. 11% in non-TXA group; OR 4.13, 95% CI 1.55-12.53, p = 0.007). There were no differences between the groups concerning intensive care unit length of stay (16 ± 11.22 days in TXA group vs. 14 ± 9.24 days in non-TXA group; p = 0.2) or hospital (23 ± 13.35 days in TXA group vs. 22 ± 13.36 days in non-TXA group; p = 0.9). There was no difference in the rates of rebleeding (7.8% in TXA group vs. 8.9% in non-TXA group; p = 0.31) or delayed cerebral ischemia (27% in TXA group vs. 19% in non-TXA group; p = 0.14). For the propensity-matched analysis, 128 individuals were selected (64 in TXA group and 64 in non-TXA group), and the rates of unfavorable outcomes at 6 months were also similar between groups (45% in TXA group and 36% in non-TXA group; OR 1.22, 95% CI 0.51-2.89; p = 0.655). CONCLUSIONS: Our findings in a cohort with delayed aneurysm treatment reinforce previous data that TXA use before aneurysm occlusion does not improve functional outcomes in aSAH.

Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times.

BACKGROUND: As controlling malaria transmission remains a public-health challenge in the Brazilian Amazon basin, the National Surveillance System for Malaria (SIVEP-MALARIA) has registered malaria notifications for over fifteen years helping in the decision-making on control and elimination. As a surveillance database, the system is prone to reporting delays, and knowledge about reporting patterns is essential in decisions. METHODS: This study contains an analysis of temporal and state trends of reporting times in a total of 1,580,617 individual malaria reports from January 2010 to December 2020, applying procedures for statistical distribution fitting. A nowcasting technique was applied to show an estimation of number of cases using a statistical model of reporting delays. RESULTS: Reporting delays increased over time for the states of Amazonas, Rondônia, Roraima, and Pará. Amapá has maintained a similar reporting delay pattern, while Acre decreased reporting delay between 2010 and 2020. Predictions were more accurate in states with lower reporting delays. The temporal evolution of reporting delays only showed a decrease in malaria reports in Acre from 2010 to 2020. CONCLUSION: Malaria notifications may take days or weeks to enter the national surveillance database. The reporting times are likely to impact incidence estimation over periods when data is incomplete, whilst the impact of delays becomes smaller for retrospective analysis. Short-term assessments for the estimation of malaria incidence from the malaria control programme must deal with reporting delays.

MDexciteR: Enhanced Sampling Molecular Dynamics by Excited Normal Modes or Principal Components Obtained from Experiments.

Molecular dynamics with excited normal modes (MDeNM) is an enhanced sampling method for exploring conformational changes in proteins with minimal biases. The excitation corresponds to injecting kinetic energy along normal modes describing intrinsic collective motions. Herein, we developed a new automated open-source implementation, MDexciteR (https://github.com/mcosta27/MDexciteR), enabling the integration of MDeNM with two commonly used simulation programs with GPU support. Second, we generalized the method to include the excitation of principal components calculated from experimental ensembles. Finally, we evaluated whether the use of coarse-grained normal modes calculated with elastic network representations preserved the performance and accuracy of the method. The advantages and limitations of these new approaches are discussed based on results obtained for three different protein test cases: two globular and a protein/membrane system.

Trends in Intensive Care Admissions and Outcomes of Stroke Patients Over 10 Years in Brazil: Impact of the COVID-19 Pandemic.

BACKGROUND: The coronavirus 2019 (COVID-19) pandemic affected stroke care worldwide. Data from low- and middle-income countries are limited. RESEARCH QUESTION: What was the impact of the pandemic in ICU admissions and outcomes of patients with stroke, in comparison with trends over the last 10 years? STUDY DESIGN AND METHODS: Retrospective cohort study including prospectively collected data from 165 ICUs in Brazil between 2011 and 2020. We analyzed clinical characteristics and mortality over a period of 10 years and evaluated the impact of the pandemic on stroke outcomes, using the following approach: analyses of admissions for ischemic and hemorrhagic strokes and trends in in-hospital mortality over 10 years; analysis of variable life-adjusted display (VLAD) during 2020; and a mixed-effects multivariable logistic regression model. RESULTS: A total of 17,115 stroke admissions were analyzed, from which 13,634 were ischemic and 3,481 were hemorrhagic. In-hospital mortality was lower after ischemic stroke as compared with hemorrhagic (9% vs 24%, respectively). Changes in VLAD across epidemiological weeks of 2020 showed that the rise in COVID-19 cases was accompanied by increased mortality, mainly after ischemic stroke. In logistic regression mixed models, mortality was higher in 2020 compared with 2019, 2018, and 2017 in patients with ischemic stroke, namely, in those without altered mental status. In hemorrhagic stroke, the increased mortality in 2020 was observed in patients 50 years of age or younger, as compared with 2019. INTERPRETATION: Hospital outcomes of stroke admissions worsened during the COVID-19 pandemic, interrupting a trend of improvements in survival rates over 10 years. This effect was more pronounced during the surge of COVID-19 ICU admissions affecting predominantly patients with ischemic stroke without coma, and young patients with hemorrhagic stroke.

Primary healthcare protects vulnerable populations from inequity in COVID-19 vaccination: An ecological analysis of nationwide data from Brazil.

Background: There is limited information on the inequity of access to vaccination in low-and-middle-income countries during the COVID-19 pandemic. Here, we described the progression of the Brazilian immunisation program for COVID-19, and the association of socioeconomic development with vaccination rates, considering the potential protective effect of primary health care coverage. Methods: We performed an ecological analysis of COVID-19 immunisation data from the Brazilian National Immunization Program from January 17 to August 31, 2021. We analysed the dynamics of vaccine coverage in the adult population of 5,570 Brazilian municipalities. We estimated the association of human development index (HDI) levels (low, medium, and high) with age-sex standardised first dose coverage using a multivariable negative binomial regression model. We evaluated the interaction between the HDI and primary health care coverage. Finally, we compared the adjusted monthly progression of vaccination rates, hospital admission and in-hospital death rates among HDI levels. Findings: From January 17 to August 31, 2021, 202,427,355 COVID-19 vaccine doses were administered in Brazil. By the end of the period, 64·2% of adults had first and 31·4% second doses, with more than 90% of those aged ≥60 years with primary scheme completed. Four distinct vaccine platforms were used in the country, ChAdOx1-S/nCoV-19, Sinovac-CoronaVac, BNT162b2, Ad26.COV2.S, composing 44·8%, 33·2%, 19·6%, and 2·4% of total doses, respectively. First dose coverage differed between municipalities with high, medium, and low HDI (Median [interquartile range] 72 [66, 79], 68 [61, 75] and 63 [55, 70] doses per 100 people, respectively). Municipalities with low (Rate Ratio [RR, 95% confidence interval]: 0·87 [0·85-0·88]) and medium (RR [95% CI]: 0·94 [0·93-0·95]) development were independently associated with lower vaccination rates compared to those with high HDI. Primary health care coverage modified the association of HDI and vaccination rate, improving vaccination rates in those municipalities of low HDI and high primary health care coverage. Low HDI municipalities presented a delayed decrease in adjusted in-hospital death rates by first dose coverage compared to high HDI locations. Interpretation: In Brazil, socioeconomic disparities negatively impacted the first dose vaccination rate. However, the primary health care mitigated these disparities, suggesting that the primary health care coverage guarantees more equitable access to vaccines in vulnerable locations. Funding: This work is part of the Grand Challenges ICODA pilot initiative, delivered by Health Data Research UK and funded by the Bill & Melinda Gates Foundation and the Minderoo Foundation. This study was supported by the National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES) - Finance Code 001, Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ) and the Pontifical Catholic University of Rio de Janeiro.

Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization and pandemic preparedness are critical to minimize population-wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries.

Comparing continuous versus categorical measures to assess and benchmark intensive care unit performance.

PURPOSE: To compare categorical and continuous combinations of the standardized mortality ratio (SMR) and the standardized resource use (SRU) to evaluate ICU performance. MATERIALS AND METHODS: We analysed data from adult patients admitted to 128 ICUs in Brazil and Uruguay (BR/UY) and 83 ICUs in The Netherlands between 2016 and 2018. SMR and SRU were calculated using SAPS-3 (BR/UY) or APACHE-IV (The Netherlands). Performance was defined as a combination of metrics. The categorical combination was the efficiency matrix, whereas the continuous combination was the average SMR and SRU (average standardized ratio, ASER). Association among metrics in each dataset was evaluated using Spearman's rho and R2. RESULTS: We included 277,459 BR/UY and 164,399 Dutch admissions. Median [interquartile range] ASER = 0.99[0.83-1.21] in BR/UY and 0.99[0.92-1.09] in Dutch datasets. The SMR and SRU were more correlated in BR/UY ICUs than in Dutch ICUs (Spearman's Rho: 0.54vs.0.24). The highest and lowest ASER values were concentrated in the least and most efficient groups. An expert focus group listed potential advantages and limitations of both combinations. CONCLUSIONS: The categorical combination of metrics is easy to interpret but limits statistical inference for benchmarking. The continuous combination offers appropriate statistical properties for evaluating performance when metrics are positively correlated.

The resilient intensive care unit.

BACKGROUND: The COVID-19 pandemic tested the capacity of intensive care units (ICU) to respond to a crisis and demonstrated their fragility. Unsurprisingly, higher than usual mortality rates, lengths of stay (LOS), and ICU-acquired complications occurred during the pandemic. However, worse outcomes were not universal nor constant across ICUs and significant variation in outcomes was reported, demonstrating that some ICUs could adequately manage the surge of COVID-19. METHODS: In the present editorial, we discuss the concept of a resilient Intensive Care Unit, including which metrics can be used to address the capacity to respond, sustain results and incorporate new practices that lead to improvement. RESULTS: We believe that a resiliency analysis adds a component of preparedness to the usual ICU performance evaluation and outcomes metrics to be used during the crisis and in regular times. CONCLUSIONS: The COVID-19 pandemic demonstrated the need for a resilient health system. Although this concept has been discussed for health systems, it was not tested in intensive care. Future studies should evaluate this concept to improve ICU organization for standard and pandemic times.

On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis.

BACKGROUND: Malaria incidence in Brazil reversed its decreasing trend when cases from recent years, as recent as 2015, exhibited an increase in the Brazilian Amazon basin, the area with the highest transmission of Plasmodium vivax and Plasmodium falciparum. In fact, an increase of more than 20% in the years 2016 and 2017 revealed possible vulnerabilities in the national malaria-control programme. METHODS: Factors potentially associated with this reversal, including migration, economic activities, and deforestation, were studied. Past incidences of malaria cases due to P. vivax and P. falciparum were analysed with a spatio-temporal Bayesian model using more than 5 million individual records of malaria cases from January of 2003 to December of 2018 in the Brazilian Amazon to establish the municipalities with unexpected increases in cases. RESULTS: Plasmodium vivax incidence surpassed the past trends in Amazonas (AM), Amapá (AP), Acre (AC), Pará (PA), Roraima (RR), and Rondônia (RO), implying a rebound of these states between 2015 and 2018. On the other hand, P. falciparum also surpassed the past trends in AM, AC, AP, and RR with less severity than P. vivax incidence. Outdoor activities, agricultural activities, accumulated deforestation, and travelling might explain the rebound in malaria cases in RR, AM, PA, and RO, mainly in P. vivax cases. These variables, however, did not explain the rebound of either P. vivax and P. falciparum cases in AC and AP states or P. falciparum cases in RR and RO states. CONCLUSION: The Amazon basin has experienced an unexpected increase in malaria cases, mainly in P. vivax cases, in some regions of the states of Amazonas, Acre, Pará, Amapá, Roraima, and Rondônia from 2015 to 2018 and agricultural activities, outdoor activities, travelling activities, and accumulated deforestation appear linked to this rebound of cases in particular regions with different impact. This shows the multifactorial effects and the heterogeneity of the Amazon basin, boosting the necessity of focusing the malaria control programme on particular social, economic, and environmental conditions.

Cohort-profile: Household transmission of SARS-CoV-2 in a low-resource community in Rio de Janeiro, Brazil.

PURPOSE: To better understand the household transmission of SARS-COV-2 in a low-resource community in Rio de Janeiro during the COVID-19 pandemic (2020-2022). PARTICIPANTS: This is an open prospective cohort study of children ≤12 years old and their household contacts. During home visits over 24 months, we collected data on sociodemographic characteristics, behavioural data, clinical manifestations of SARS-CoV-2, vaccination status, SARS-CoV-2 (reverse transcription-polymerase chain reaction) RT-PCR and anti-S antibody tests. Among adults, the majority of participants were women (62%). FINDINGS TO DATE: We enrolled 845 families from May 2020 to May 2022. The median number of residents per household was four. The median household density, defined as the number of persons per room, was 0.95. The risk of SARS-CoV-2 occurrence was higher in households with a high number of persons per room. Children were not the principal source of SARS-CoV-2 infections in their households during the first wave of the pandemic. FUTURE PLANS: Future studies will investigate cellular and humoral immune responses to locally circulating SARS-CoV-2 variants, which is relevant for the design of vaccines, antivirals and monoclonal antibodies. We will also engage in outreach to encourage vaccination as a means of limiting the transmission of novel SARS-CoV-2 variants and other emerging pathogens.