Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI

Associations between epidemiological and laboratory parameters and disease severity in hospitalized patients with COVID-19 during first and second epidemic waves in middle south Mato Grosso

BACKGROUND

COVID-19 is a multisystemic disease characterized by respiratory distress. Disease severity is associated with several factors. Here we characterize virological findings and evaluate the association of laboratorial, epidemiological, virological findings and clinical outcomes of 251 patients during the first and second epidemic waves of COVID-19.

METHODS

This transversal study used biological samples and data from patients hospitalized with COVID-19 between May 2020 and August 2021 in the metropolitan region of Cuiabá, Mato Grosso Brazil. Biological samples were subjected to RT-qPCR and MinION sequencing. Univariate and multivariate logistic regression and Odds ratio were used to correlate clinical, laboratorial, epidemiological data.

FINDINGS

Patients were represented by males (61.7%) with mean age of 52.4 years, mild to moderate disease (49,0%), overweight/obese (69.3%), with comorbidities (66.1%) and evolving to death (55.38%). Severe cases showing symptoms for prolonged time, ≥ 25% of ground-glass opacities in the lungs and fatality rate increased significantly in second wave. Fatality was statistically associated to > 61 years of age,>25% ground-glass opacities in the lungs, immune, cardiac, or metabolic comorbidities. Higher viral load (p < 0.01/p = 0.02 in each wave), decreased erythrocyte (p < 0.01), hemoglobin (p < 0.05/p < 0.01), hematocrit (p < 0.01), RDW (p < 0.01), lymphocyte (p < 0.01), increased leucocyte (p < 0.01), neutrophil (p < 0.01) and CRP levels (p < 0.01) showed significant association with fatality in both waves, as did Neutrophil/Platelet (NPR; p < 0.01), Neutrophil/Lymphocyte (NLR; p < 0.01) and Monocyte/Lymphocyte ratio (MLR; p < 0.01). SARS-CoV-2 genomes from lineage B.1.1.33(n = 8) and Gamma/P.1(n = 15) shared 6/7 and 20/23 lineage-defining mutations, respectively.

MAIN CONCLUSIONS

Severity and mortality of COVID-19 associated with a panel of epidemiological and laboratorial findings, being second wave, caused by Gamma variant, more severe in this in-hospital population.

Assessing the Time Evolution of COVID-19 Effective Reproduction Number in Brazil

In this paper, we use a Bayesian method to estimate the effective reproduction number ( R ( t ) ), in the context of monitoring the time evolution of the COVID-19 pandemic in Brazil at different geographic levels. The focus of this study is to investigate the similarities between the trends in the evolution of such indicators at different subnational levels with the trends observed nationally. The underlying question addressed is whether national surveillance of such variables is enough to provide a picture of the epidemic evolution in the country or if it may hide important localized trends. This is particularly relevant in the scenario where health authorities use information obtained from such indicators in the design of non-pharmaceutical intervention policies to control the epidemic. A comparison between R ( t ) estimates and the moving average (MA) of daily reported infections is also presented, which is another commonly monitored variable. The analysis carried out in this paper is based on the data of confirmed infected cases provided by a public repository. The correlations between the time series of R ( t ) and MA in different geographic levels are assessed. Comparing national with subnational trends, higher degrees of correlation are found for the time series of R ( t ) estimates, compared to the MA time series. Nevertheless, differences between national and subnational trends are observed for both indicators, suggesting that local epidemiological surveillance would be more suitable as an input to the design of non-pharmaceutical intervention policies in Brazil, particularly for the least populated states.

Prevalence and factors associated with long COVID in adults from Southern Brazil: findings from the PAMPA cohort

Most COVID-19 survivors have reported experiencing persistent symptoms after the infection - these types of cases are known as long COVID. Since Brazil was an epicenter of the COVID-19 pandemic, a high burden of long COVID is expected. This study aimed to identify the prevalence and factors associated with long COVID in adults in Southern Brazil, analyzing data from the PAMPA cohort. Participants filled out a self-reported online questionnaire in June 2022. This study only included subjects who tested positive for COVID-19. Long COVID was defined by any symptoms that persisted for at least three months after the SARS-CoV-2 infection. Poisson's regression models with robust variance were used to identify factors associated with long COVID; and results were reported as prevalence ratios (PR) and respective 95% confidence intervals (95%CI). A total of 1,001 participants (77.4% women, mean age [SD] = 38.3 [11.9] years) were analyzed. The prevalence of long COVID among these patients was 77.4% (95%CI: 74.7; 79.9). The likelihood of long COVID was higher in unvaccinated participants (PR = 1.23, 95%CI: 1.06; 1.42), in those with chronic conditions (PR = 1.13, 95%CI: 1.04; 1.24), and in those who were hospitalized due to the COVID-19 infection (PR = 1.24, 95%CI: 1.16; 1.32). This prevalence was also higher in women (PR = 1.21, 95%CI: 1.09; 1.33) than in men. Physical activity was associated with a reduced likelihood of fatigue, neurological complications, coughing, and headaches as persistent symptoms after a COVID-19 infection. It was found that three out of four adults in Southern Brazil experienced long COVID. Public policies aiming to reduce the burden of long COVID must be prioritized, especially in groups that are at higher risk of developing this harmful condition.

COVID-19 in Brazil: a 3-year update

Three years into the coronavirus disease (COVID)-19 pandemic and the world is still struggling with the aftermath of this global health crisis. In Brazil, we are witnessing serious economic, health, social, and political problems. The rapid spread of the virus in our country was the result of a shortage of vaccines and the lack of an effective national campaign to identify and report cases. This health crisis also intensified social inequalities, hitting Indigenous peoples hard due to the lack of access to health services. In addition, rising unemployment and overcrowding of the health system made contagion possible, especially among the most vulnerable, increasing the number of serious cases of the disease. It is important to highlight that emotional problems worsened, the educational system was severely affected, and domestic violence increased during the confinement period, in addition to the fact that the pandemic exposed the great disparities of regional inequalities that exist across the country, mainly concerning health management.

The Causal Role of Lockdowns in COVID-19: Conclusions From Daily Epidemiological, Psychological, and Sociological Data

Much has been written about the COVID-19 pandemic's epidemiological, psychological, and sociological consequences. Yet, the question about the role of the lockdown policy from psychological and sociological points of view has not been sufficiently addressed. Using epidemiological, psychological, and sociological daily data, we examined the causal role of lockdown and variation in morbidity referring to emotional and behavioral aspects. Dynamics of support requests to the Sahar organization concerning loneliness, depression, anxiety, family difficulties, and sexual trauma were investigated alongside processes of emergency and domestic violence reports to the Ministry of Welfare and Social Affairs. By exploring the signals and predictive modeling for a situation with no lockdown implementation, the lockdown was found as a critical factor in distress rising among the general population, which could affect long after the improvement in pandemic case counts. Applications and implications are discussed in the context of decision-making in dealing with crises as well as the need to allocate resources for adaptive coping.

Does Widespread Use of Hydroxychloroquine Reduce the Transmissibility of SARS-CoV-2 / COVID-19? An Ecological Correlational Study

BACKGROUND

At the beginning of the coronavirus disease (COVID-19) pandemic, hydroxychloroquine (HCQ) was widely used as a possible antiviral agent. Current knowledge indicates that HCQ has little or no effect on individual clinical outcomes of COVID-19, but populational effects on disease transmissibility are still unknown.

OBJECTIVE

This study investigates the hypothesis that massive HCQ consumption by a population may contribute to reducing the transmissibility of SARS-CoV-2 and COVID-19 spread by reducing the viral load of infected individuals.

METHODS

Public database of seven states from Brazil in 2020 were assessed, before the start of COVID-19 vaccination. The daily values of the COVID-19 effective reproduction number (Rt) were obtained. Associations between Rt values and the proposed predictor variables (prevalence of COVID-19 as a marker of collective immunity; social isolation indices; consumption of HCQ) were tested using multiple linear regression analysis.

RESULTS

In all seven states, consumption of HCQ was a significant negative predictor of Rt (β ranged from -0.295 to -0.502, p = 0.001). Furthermore, the mean derivative of Rt during the declining period of the COVID-19 incidence (the mean rate of variation) was also significantly negatively related to the mean HCQ consumption in that period (R2 = 0.895; β = -0.783; p = 0.011), meaning that the higher the HCQ consumption, the faster the decline of COVID-19 Rt. It suggests a dose-response phenomenon and a causal relationship in this association.

CONCLUSION

The results of this study are compatible with the hypothesis that HCQ has small but significant in vivo antiviral effects that are able to reduce SARS-CoV-2 transmissibility at the populational level.

Communication, information, and knowledge in the pandemic by COVID-19 in Brazil

As coronavirus disease 2019 (COVID-19) is asserting itself as a health crisis, it is necessary to assess the knowledge and perceptions of people about the disease. The aim of this study is to assess the knowledge of the general population about COVID-19 and how the media influence this knowledge. This is a cross-sectional study with 5066 participants who answered an online questionnaire between April and May 2020. Data analysis was performed using descriptive statistics and logistic regression models. Over 75% have obtained a high degree of knowledge regarding signs, symptoms, and transmission, 95% stated to check the veracity of the information received, and also showed that the total knowledge about COVID-19 was associated with the level of instruction, with the perception of the quality of information disseminated by the media, and with the risk perception. Despite the high level of knowledge of participants, the results pointed to the need to reinforce information for individuals with less education and the importance of avoiding denialism that reduces the risk perception about COVID-19.

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

Background

The COVID-19 is a significant public health issue, and monitoring confirmed cases and deaths is an essential epidemiologic tool. We evaluated the features in Brazilian hospitalized patients due to severe acute respiratory infection (SARI) during the COVID-19 pandemic in Brazil. We grouped the patients into the following categories: Influenza virus infection (G1), other respiratory viruses' infection (G2), other known etiologic agents (G3), SARS-CoV-2 infection (patients with COVID-19, G4), and undefined etiological agent (G5).

Methods

We performed an epidemiological study using data from DataSUS (https://opendatasus.saude.gov.br/) from December 2019 to October 2021. The dataset included Brazilian hospitalized patients due to SARI. We considered the clinical evolution of the patients with SARI during the COVID-19 pandemic according to the SARI patient groups as the outcome. We performed the multivariate statistical analysis using logistic regression, and we adopted an Alpha error of 0.05.

Results

A total of 2,740,272 patients were hospitalized due to SARI in Brazil, being the São Paulo state responsible for most of the cases [802,367 (29.3%)]. Most of the patients were male (1,495,416; 54.6%), aged between 25 and 60 years (1,269,398; 46.3%), and were White (1,105,123; 49.8%). A total of 1,577,279 (68.3%) patients recovered from SARI, whereas 701,607 (30.4%) died due to SARI, and 30,551 (1.3%) did not have their deaths related to SARI. A major part of the patients was grouped in G4 (1,817,098; 66.3%) and G5 (896,207; 32.7%). The other groups account for &lt;1% of our sample [G1: 3,474 (0.1%), G2: 16,627 (0.6%), and G3: 6,866 (0.3%)]. The deaths related to SARI were more frequent in G4 (574,887; 34.7%); however, the deaths not related to SARI were more frequent among the patients categorized into the G3 (1,339; 21.3%) and G5 (25,829; 4.1%). In the multivariate analysis, the main predictors to classify the patients in the G5 when compared with G4 or G1-G4 were female sex, younger age, Black race, low educational level, rural place of residence, and the use of antiviral to treat the clinical signs. Furthermore, several features predict the risk of death by SARI, such as older age, race (Black, Indigenous, and multiracial background), low educational level, residence in a flu outbreak region, need for intensive care unit, and need for mechanical ventilatory support.

Conclusions

The possible COVID-19 underreporting (G5) might be associated with an enhanced mortality rate, more evident in distinct social groups. In addition, the patients' features are unequal between the patients' groups and can be used to determine the risk of possible COVID-19 underreporting in our population. Patients with a higher risk of death had a different epidemiological profile when compared with patients who recovered from SARI, like older age, Black, Indigenous, and multiracial background races, low educational level, residence in a flu outbreak region, need for intensive care unit and need for mechanical ventilatory support.

A parametrized nonlinear predictive control strategy for relaxing COVID-19 social distancing measures in Brazil

The SARS-CoV-2 virus was first registered in Brazil by the end of February 2020. Since then, the country counts over 150000 deaths due to COVID-19 and faces a profound social and economic crisis; there is also an ongoing health catastrophe, with the majority of hospital beds in many Brazilian cities currently occupied with COVID-19 patients. Thus, a Nonlinear Model Predictive Control (NMPC) scheme used to plan appropriate social distancing measures (and relaxations) in order to mitigate the effects of this pandemic is formulated in this paper. The strategy is designed upon an adapted data-driven Susceptible-Infected-Recovered-Deceased (SIRD) model, which includes time-varying auto-regressive immunological parameters. A novel identification procedure is proposed, composed of analytical regressions, Least-Squares optimization and auto-regressive model fits. The adapted SIRD model is validated with real data and able to adequately represent the contagion curves over large forecast horizons. The NMPC strategy is designed to generate piecewise constant quarantine guidelines, which can be reassessed (relaxed/strengthened) each week. Simulation results show that the proposed NMPC technique is able to mitigate the number of infections and progressively loosen social distancing measures. With respect to a "no-control" condition, the number of deaths could be reduced in up to 30% if the proposed NMPC coordinated health policy measures are enacted.

Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study

The Human Development Index measures a region's development and is a step for development debate beyond the traditional, economic perspective. It can also determine the success of a country's response to the COVID-19 pandemic, mainly affecting the case fatality rate among severe cases of SARS-CoV-2 infection. We aimed to associate the Human Development Index with the case fatality rate due to COVID-19 in each Brazilian state and the Federal District, taking into account comorbidities and the need for invasive mechanical ventilation. We also evaluated the influence of the GINI index, number of intensive care unit beds, and occupied households in subnormal clusters on the case fatality rate. We performed an ecological study including two populations: COVID-19 individuals that did not require the mechanical ventilation protocol; and COVID-19 individuals under invasive mechanical ventilation. We performed a Pearson correlation test and a univariate linear regression analysis on the relationship between Human Development Index, Human Development Index-Education Level, Human Development Index-Life Expectancy, and Human Development Index-Gross National Income per capita and COVID-19 deaths. The same analyses were performed using the other markers. We grouped the patients with COVID-19 according to comorbidities and the need for invasive mechanical ventilation. Alpha = 0.05. We included 848,501 COVID-19 individuals, out of which 153,710 needed invasive mechanical ventilation and 314,164 died, and 280,533 COVID-19 individuals without comorbidity, out of which 33,312 needed invasive mechanical ventilation and 73,723 died. We observed a low negative Pearson correlation between the Human Development Index and death and a moderate negative Pearson correlation between the Human Development Index and deaths of individuals on invasive mechanical ventilation, with or without comorbidity. The univariate linear analysis showed the case fatality rate depends on at least 20-40% of the Human Development Index. In Brazil, regions with a low Human Development Index demonstrated a higher case fatality rate due to COVID-19, mainly in individuals who needed invasive mechanical ventilation, than regions with a higher Human Development Index. Although other indexes studied, such as intensive care unit beds and GINI, were also associated with the COVID-19 case fatality rate, they were not as relevant as the Human Development Index. Brazil is a vast territory comprising cultural, social, and economic diversity, which mirrors the diversity of the Human Development Index. Brazil is a model nation for the study of the Human Development Index's influence on aspects of the COVID-19 pandemic, such as its impact on the case fatality rate.

Exploring the impact of under-reported cases on the COVID-19 spatiotemporal distributions using healthcare workers infection data

A timely understanding of the spatiotemporal pattern and development trend of COVID-19 is critical for timely prevention and control. However, the under-reporting of casesis widespread in fields associated with public health. It is also possible to draw biased inferences and formulate inappropriate prevention and control policies if the phenomenon of under-reporting is not taken into account. Therefore, in this paper, a novel framework was proposed to explore the impact of under-reporting on COVID-19 spatiotemporal distributions, and empirical analysis was carried out using infection data of healthcare workers in Wuhan and Hubei (excluding Wuhan). The results show that (1) the lognormal distribution was the most suitable to describe the evolution of epidemic with time; (2) the estimated peak infection time of the reported cases lagged the peak infection time of the healthcare worker cases, and the estimated infection time interval of the reported cases was smaller than that of the healthcare worker cases. (3) The impact of under-reporting cases on the early stages of the pandemic was greater than that on its later stages, and the impact on the early onset area was greater than that on the late onset area. (4) Although the number of reported cases was lower than the actual number of cases, a high spatial correlation existed between the cumulatively reported cases and healthcare worker cases. The proposed framework of this study is highly extensible, and relevant researchers can use data sources from other counties to carry out similar research.

Fine-scale heterogeneity in population density predicts wave dynamics in dengue epidemics

The spread of dengue and other arboviruses constitutes an expanding global health threat. The extensive heterogeneity in population distribution and potential complexity of movement in megacities of low and middle-income countries challenges predictive modeling, even as its importance to disease spread is clearer than ever. Using surveillance data at fine resolution from Rio de Janeiro, we document a scale-invariant pattern in the size of successive epidemics following DENV4 emergence. Using surveillance data at fine resolution following the emergence of the DENV4 dengue serotype in Rio de Janeiro, we document a pattern in the size of successive epidemics that is invariant to the scale of spatial aggregation. This pattern emerges from the combined effect of herd immunity and seasonal transmission, and is strongly driven by variation in population density at sub-kilometer scales. It is apparent only when the landscape is stratified by population density and not by spatial proximity as has been common practice. Models that exploit this emergent simplicity should afford improved predictions of the local size of successive epidemic waves.