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1.
The Lancet Regional Health - Americas ; : 100335, 2022.
Article in English | ScienceDirect | ID: covidwho-1983604

ABSTRACT

Summary 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.

4.
Nat Med ; 28(7): 1476-1485, 2022 07.
Article in English | MEDLINE | ID: covidwho-1830084

ABSTRACT

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.


Subject(s)
COVID-19 , Aged , Aged, 80 and over , Bayes Theorem , Brazil/epidemiology , COVID-19/epidemiology , Hospitals , Humans , SARS-CoV-2
5.
Ann Intensive Care ; 12(1): 37, 2022 Apr 26.
Article in English | MEDLINE | ID: covidwho-1808384

ABSTRACT

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.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-307251

ABSTRACT

Background: The spread of COVID-19 increased the stress of health systems globally, obligating adjustments to improve the management of severe cases. What are the impacts of preparedness measures on the outcomes of the COVID-19 critically ill patients? Our study aimed to analyze the clinical characteristics, resource use, and risk factors associated with 30-day in-hospital mortality of critically ill adult patients with COVID-19 requiring ICU admission in a network of Brazilian hospitals.Methods: A multicenter cohort of COVID-19-confirmed patients requiring ICU admission at 42 Brazilian hospitals between February 27th and June 27th, 2020. The primary outcome was 30-day in-hospital mortality. We evaluated the association of clinical characteristics, ICU resource use, and risk factors using a random-effects multivariable cox regression model, in which the hospital was the random intercept. Secondary outcomes were the length-of-stay, ICU, and in-hospital mortality, and the use of mechanical ventilation during hospitalization.Findings: From 4,942 patients, 713 (14·4%) died 30 days after the ICU admission. The median age was 56 (IQR: [43,72]) years, 38% of patients were over 60 years-old, and 41% were women. Being older than 70 years (70-79, Hazard Ratio [95%CI]: 1·95[1·3-2·93];≥ 80, 3·96[2·66-5·89]), frail (MFI≥3, 1·65 [1·26-2·15]) and requiring, early or late, invasive Mechanical Ventilation (<=48h, 5·42 [4·14-7·10];>48h, 3·26 [2·46-4·32]) were independently associated with 30-day mortality. In 1,400 ventilated patients, 30-day mortality was 44·4% (622/1,400), the median duration of mechanical ventilation was ten days (IQR [6,16]), and ICU length of stay was 17 days (IQR [10,26]). Those who died within 30 days were more often older than 80 years (≥80: 37% vs. 14%) and previously frail (35% vs. 19%) compared to the survivors.Interpretation: In this large cohort, critically ill COVID-19 patients showed reasonable survival rates, including those requiring mechanical ventilation. Factors associated with worse outcome were age, frailty, and early need for invasive ventilation. Adequate preparedness, early hospitalization, and no shortage of critical care resources were probably key to achieve such results.Funding: The National Council for Scientific and Technological Development (CNPq);the Coordination for the Improvement of Higher Education Personnel (CAPES);the Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ);the Pontifical Catholic University of Rio de Janeiro and the D’Or Institute for Research and Education.Declaration of Interests: Dr. Soares and Dr. Salluh are founders and equity shareholders of Epimed Solutions®, which commercializes the Epimed Monitor System®, a cloud-based software for ICU management and benchmarking. The other authors declare that they have no conflict of interest.Ethics Approval Statement: Local Ethics Committee and the Brazilian National Ethics Committee (CAAE: 17079119.7.0000.5249) approved the study without the need for informed consent.

7.
Lancet Reg Health Am ; 5: 100149, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1587086
9.
Intensive Care Med ; 47(12): 1440-1449, 2021 12.
Article in English | MEDLINE | ID: covidwho-1406151

ABSTRACT

PURPOSE: To assess whether intensive care unit (ICU) outcomes for patients not affected by coronavirus disease 2019 (COVID-19) worsened during the COVID-19 pandemic. METHODS: Retrospective cohort study including prospectively collected information of patients admitted to 165 ICUs in a hospital network in Brazil between 2011 and 2020. Association between admission in 2020 and worse hospital outcomes was performed using different techniques, including assessment of changes in illness severity of admitted patients, a variable life-adjusted display of mortality during 2020, a multivariate mixed regression model with admission year as both fixed effect and random slope adjusted for SAPS 3 score, an analysis of trends in performance using standardized mortality ratio (SMR) and standardized resource use (SRU), and perturbation analysis. RESULTS: A total of 644,644 admissions were considered. After excluding readmissions and patients with COVID-19, 514,219 patients were available for analysis. Non-COVID-19 patients admitted in 2020 had slightly lower age and SAPS 3 score but a higher mortality (6.4%) when compared with previous years (2019: 5.6%; 2018: 6.1%). Variable-adjusted life display (VLAD) in 2020 increased but started to decrease as the number of COVID-19 cases increased; this trend reversed as number of COVID cases reduced but recurred on the second wave. After logistic regression, being admitted in 2020 was associated with higher mortality when compared to previous years from 2016 and 2019. Individual ICUs standardized mortality ratio also increased during 2020 (higher SMR) while resource use remained constant, suggesting worsening performance. A perturbation analysis further confirmed changes in ICU outcomes for non-COVID-19 patients. CONCLUSION: Hospital outcomes of non-COVID-19 critically ill patients worsened during the pandemic in 2020, possibly resulting in an increased number of deaths in critically ill non-COVID patients.


Subject(s)
COVID-19 , Pandemics , Brazil/epidemiology , Cohort Studies , Critical Illness , Hospital Mortality , Humans , Intensive Care Units , Retrospective Studies , SARS-CoV-2
11.
Intensive Care Med ; 47(5): 538-548, 2021 05.
Article in English | MEDLINE | ID: covidwho-1182234

ABSTRACT

PURPOSE: Clinical characteristics and management of COVID-19 patients have evolved during the pandemic, potentially changing their outcomes. We analyzed the associations of changes in mortality rates with clinical profiles and respiratory support strategies in COVID-19 critically ill patients. METHODS: A multicenter cohort of RT-PCR-confirmed COVID-19 patients admitted at 126 Brazilian intensive care units between February 27th and October 28th, 2020. Assessing temporal changes in deaths, we identified distinct time periods. We evaluated the association of characteristics and respiratory support strategies with 60-day in-hospital mortality using random-effects multivariable Cox regression with inverse probability weighting. RESULTS: Among the 13,301 confirmed-COVID-19 patients, 60-day in-hospital mortality was 13%. Across four time periods identified, younger patients were progressively more common, non-invasive respiratory support was increasingly used, and the 60-day in-hospital mortality decreased in the last two periods. 4188 patients received advanced respiratory support (non-invasive or invasive), from which 42% underwent only invasive mechanical ventilation, 37% only non-invasive respiratory support and 21% failed non-invasive support and were intubated. After adjusting for organ dysfunction scores and premorbid conditions, we found that younger age, absence of frailty and the use of non-invasive respiratory support (NIRS) as first support strategy were independently associated with improved survival (hazard ratio for NIRS first [95% confidence interval], 0.59 [0.54-0.65], p < 0.001). CONCLUSION: Age and mortality rates have declined over the first 8 months of the pandemic. The use of NIRS as the first respiratory support measure was associated with survival, but causal inference is limited by the observational nature of our data.


Subject(s)
COVID-19 , Critical Illness , Adult , Brazil/epidemiology , Hospital Mortality , Humans , Intensive Care Units , Respiration, Artificial , SARS-CoV-2
12.
Lancet Respir Med ; 9(4): 407-418, 2021 04.
Article in English | MEDLINE | ID: covidwho-1180128

ABSTRACT

BACKGROUND: Most low-income and middle-income countries (LMICs) have little or no data integrated into a national surveillance system to identify characteristics or outcomes of COVID-19 hospital admissions and the impact of the COVID-19 pandemic on their national health systems. We aimed to analyse characteristics of patients admitted to hospital with COVID-19 in Brazil, and to examine the impact of COVID-19 on health-care resources and in-hospital mortality. METHODS: We did a retrospective analysis of all patients aged 20 years or older with quantitative RT-PCR (RT-qPCR)-confirmed COVID-19 who were admitted to hospital and registered in SIVEP-Gripe, a nationwide surveillance database in Brazil, between Feb 16 and Aug 15, 2020 (epidemiological weeks 8-33). We also examined the progression of the COVID-19 pandemic across three 4-week periods within this timeframe (epidemiological weeks 8-12, 19-22, and 27-30). The primary outcome was in-hospital mortality. We compared the regional burden of hospital admissions stratified by age, intensive care unit (ICU) admission, and respiratory support. We analysed data from the whole country and its five regions: North, Northeast, Central-West, Southeast, and South. FINDINGS: Between Feb 16 and Aug 15, 2020, 254 288 patients with RT-qPCR-confirmed COVID-19 were admitted to hospital and registered in SIVEP-Gripe. The mean age of patients was 60 (SD 17) years, 119 657 (47%) of 254 288 were aged younger than 60 years, 143 521 (56%) of 254 243 were male, and 14 979 (16%) of 90 829 had no comorbidities. Case numbers increased across the three 4-week periods studied: by epidemiological weeks 19-22, cases were concentrated in the North, Northeast, and Southeast; by weeks 27-30, cases had spread to the Central-West and South regions. 232 036 (91%) of 254 288 patients had a defined hospital outcome when the data were exported; in-hospital mortality was 38% (87 515 of 232 036 patients) overall, 59% (47 002 of 79 687) among patients admitted to the ICU, and 80% (36 046 of 45 205) among those who were mechanically ventilated. The overall burden of ICU admissions per ICU beds was more pronounced in the North, Southeast, and Northeast, than in the Central-West and South. In the Northeast, 1545 (16%) of 9960 patients received invasive mechanical ventilation outside the ICU compared with 431 (8%) of 5388 in the South. In-hospital mortality among patients younger than 60 years was 31% (4204 of 13 468) in the Northeast versus 15% (1694 of 11 196) in the South. INTERPRETATION: We observed a widespread distribution of COVID-19 across all regions in Brazil, resulting in a high overall disease burden. In-hospital mortality was high, even in patients younger than 60 years, and worsened by existing regional disparities within the health system. The COVID-19 pandemic highlights the need to improve access to high-quality care for critically ill patients admitted to hospital with COVID-19, particularly in LMICs. FUNDING: National Council for Scientific and Technological Development (CNPq), Coordinating Agency for Advanced Training of Graduate Personnel (CAPES), Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ), and Instituto de Salud Carlos III.


Subject(s)
COVID-19/epidemiology , Epidemiological Monitoring , Healthcare Disparities/statistics & numerical data , Hospital Mortality/trends , Pandemics/statistics & numerical data , Adult , Aged , Aged, 80 and over , Brazil/epidemiology , COVID-19/diagnosis , COVID-19/therapy , COVID-19/virology , Comorbidity , Female , Geography , Health Services Accessibility/organization & administration , Health Services Accessibility/statistics & numerical data , Health Services Needs and Demand/statistics & numerical data , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Patient Admission/statistics & numerical data , Respiration, Artificial/statistics & numerical data , Retrospective Studies , SARS-CoV-2/isolation & purification , Young Adult
13.
PLoS One ; 16(3): e0248920, 2021.
Article in English | MEDLINE | ID: covidwho-1150550

ABSTRACT

BACKGROUND: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of symptoms to build a predictive model as a screening tool to identify people and areas with a higher risk of SARS-CoV-2 infection to be prioritized for testing. MATERIALS AND METHODS: We performed a retrospective analysis of individuals registered in "Dados do Bem," a Brazilian app-based symptom tracker. We applied machine learning techniques and provided a SARS-CoV-2 infection risk map of Rio de Janeiro city. RESULTS: From April 28 to July 16, 2020, 337,435 individuals registered their symptoms through the app. Of these, 49,721 participants were tested for SARS-CoV-2 infection, being 5,888 (11.8%) positive. Among self-reported symptoms, loss of smell (OR[95%CI]: 4.6 [4.4-4.9]), fever (2.6 [2.5-2.8]), and shortness of breath (2.1 [1.6-2.7]) were independently associated with SARS-CoV-2 infection. Our final model obtained a competitive performance, with only 7% of false-negative users predicted as negatives (NPV = 0.93). The model was incorporated by the "Dados do Bem" app aiming to prioritize users for testing. We developed an external validation in the city of Rio de Janeiro. We found that the proportion of positive results increased significantly from 14.9% (before using our model) to 18.1% (after the model). CONCLUSIONS: Our results showed that the combination of symptoms might predict SARS-Cov-2 infection and, therefore, can be used as a tool by decision-makers to refine testing and disease control strategies.


Subject(s)
COVID-19/diagnosis , Machine Learning , Adult , Anosmia/etiology , Brazil , COVID-19/complications , COVID-19/virology , COVID-19 Testing , Dyspnea/etiology , False Negative Reactions , False Positive Reactions , Female , Fever/etiology , Humans , Male , Middle Aged , Mobile Applications , Registries , Retrospective Studies , Risk , SARS-CoV-2/isolation & purification , Self Report
14.
Front Med (Lausanne) ; 8: 630982, 2021.
Article in English | MEDLINE | ID: covidwho-1082440

ABSTRACT

Background: Convalescent plasma is a potential therapeutic option for critically ill patients with coronavirus disease 19 (COVID-19), yet its efficacy remains to be determined. The aim was to investigate the effects of convalescent plasma (CP) in critically ill patients with COVID-19. Methods: This was a single-center prospective observational study conducted in Rio de Janeiro, Brazil, from March 17th to May 30th, with final follow-up on June 30th. We included 113 laboratory-confirmed COVID-19 patients with respiratory failure. Primary outcomes were time to clinical improvement and survival within 28 days. Secondary outcomes included behavior of biomarkers and viral loads. Kaplan-Meier analyses and Cox proportional-hazards regression using propensity score with inverse-probability weighing were performed. Results: 41 patients received CP and 72 received standard of care (SOC). Median age was 61 years (IQR 48-68), disease duration was 10 days (IQR 6-13), and 86% were mechanically ventilated. At least 29 out of 41CP-recipients had baseline IgG titers ≥ 1:1,080. Clinical improvement within 28 days occurred in 19 (46%) CP-treated patients, as compared to 23 (32%) in the SOC group [adjusted hazard ratio (aHR) 0.91 (0.49-1.69)]. There was no significant change in 28-day mortality (CP 49% vs. SOC 56%; aHR 0.90 [0.52-1.57]). Biomarker assessment revealed reduced inflammatory activity and increased lymphocyte count after CP. Conclusions: In this study, CP was not associated with clinical improvement or increase in 28-day survival. However, our study may have been underpowered and included patients with high IgG titers and life-threatening disease. Clinical Trial Registration: The study protocol was retrospectively registered at the Brazilian Registry of Clinical Trials (ReBEC) with the identification RBR-4vm3yy (http://www.ensaiosclinicos.gov.br).

15.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-722

ABSTRACT

Background: Brazil detected community transmission of COVID-19 on March 13, 2020. In this study we identify which areas in the country are most vulnerable for C

16.
PLoS One ; 15(9): e0238214, 2020.
Article in English | MEDLINE | ID: covidwho-781641

ABSTRACT

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


Subject(s)
Betacoronavirus , Coronavirus Infections/transmission , Models, Theoretical , Morbidity/trends , Pneumonia, Viral/transmission , Brazil/epidemiology , COVID-19 , Cluster Analysis , Coronavirus Infections/epidemiology , Disease Outbreaks/statistics & numerical data , Forecasting/methods , Humans , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Socioeconomic Factors
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