Determinants of COVID-19 vaccine hesitancy among students and parents in Sentinel Schools Network of Catalonia, Spain.

Vaccine hesitancy is defined as a delay in acceptance of vaccines despite its availability, caused by many determinants. Our study presents the key reasons, determinants and characteristics associated with COVID-19 vaccine acceptability among students over 16 years and parents of students under 16 years and describe the COVID-19 vaccination among students in the settings of sentinel schools of Catalonia, Spain. This is a cross-sectional study that includes 3,383 students and the parents between October 2021 and January 2022. We describe the student's vaccination status and proceed a univariate and multivariate analysis using a Deletion Substitution Addition (DSA) machine learning algorithm. Vaccination against COVID-19 reached 70.8% in students under 16 years and 95.8% in students over 16 years at the end of the study project. The acceptability among unvaccinated students was 40.9% and 20.8% in October and January, respectively, and among parents was proportionally higher among students aged 5-11 (70.2%) in October and aged 3-4 (47.8%) in January. The key reason to not vaccinate themselves, or their children, were concern about side effects, insufficient research about the effect of the vaccine in children, rapid development of vaccines, necessity for more information and previous infection by SARS-CoV-2. Several variables were associated with refusal end hesitancy. For students, the main ones were risk perception and use of alternative therapies. For parents, the age of students, sociodemographic variables, socioeconomic impact related to the pandemic, and use of alternative therapies were more evident. Monitoring vaccine acceptance and refusal among children and their parents has been important to understand the interaction between different multilevel determinants and we hope it will be useful to improve public health strategies for future interventions in this population.

The COVID-19 Sentinel Schools Network of Catalonia (CSSNC) project: Associated factors to prevalence and incidence of SARS-CoV-2 infection in educational settings during the 2020-2021 academic year.

The Sentinel Schools project was designed to monitor and evaluate the epidemiology of COVID-19 in Catalonia, gathering evidence for health and education policies to inform the development of health protocols and public health interventions to control of SARS-CoV-2 infection in schools. The aim of this study was to estimate the prevalence and incidence of SARS-CoV-2 infections and to identify their determinants among students and staff during February to June in the academic year 2020-2021. We performed two complementary studies, a cross-sectional and a longitudinal component, using a questionnaire to collect nominal data and testing for SARS-CoV-2 detection. We describe the results and perform a univariate and multivariate analysis. The initial crude seroprevalence was 14.8% (95% CI: 13.1-16.5) and 22% (95% CI: 18.3-25.8) for students and staff respectively, and the active infection prevalence was 0.7% (95% CI: 0.3-1) and 1.1% (95% CI: 0.1-2). The overall incidence for persons at risk was 2.73 per 100 person-month and 2.89 and 2.34 per 100 person-month for students and staff, respectively. Socioeconomic, self-reported knowledge, risk perceptions and contact pattern variables were positively associated with the outcome while sanitary measure compliance was negatively associated, the same significance trend was observed in multivariate analysis. In the longitudinal component, epidemiological close contact with SARS-CoV-2 infection was a risk factor for SARS-CoV-2 infection while the highest socioeconomic status level was protective as was compliance with sanitary measures. The small number of active cases detected in these schools suggests a low transmission among children in school and the efficacy of public health measures implemented, at least in the epidemiological scenario of the study period. The major contribution of this study was to provide results and evidence that help analyze the transmission dynamic of SARS-CoV-2 and evaluate the associations between sanitary protocols implemented, and measures to avoid SARS-CoV-2 spread in schools.

The first year of the COVID-19 pandemic in an indigenous population in Brazil: an epidemiological study.

This cross-sectional observational study that describes the epidemiological data of the first year of the COVID-19 pandemic in the Mato Grosso do Sul State, aimed to demonstrate the differences between indigenous and non-indigenous populations, characterize confirmed cases of COVID-19 according to risk factors related to ethnicity, comorbidities and their evolution and to verify the challenges in facing the disease in Brazil. SIVEP-Gripe and E-SUS-VE, a nationwide surveillance database in Brazil, from March 2020 to March 2021 in Mato Grosso do Sul state, were used to compare survivors and non-survivors from indigenous and non-indigenous populations and the epidemiological incidence curves of these populations. A total of 176,478, including 5,299 indigenous people, were confirmed. Among the indigenous population, 52.5% (confidence interval [CI] 51.2-53.9) were women, 38% (CI 36.7-39.4) were 20-39 years old, 56.7% were diagnosed by rapid antibody tests, 12.3% (CI 95%:11.5-13.2) had at least one comorbidity, and 5.3% (CI 95%:4.7-5.9) were hospitalized. In the non-indigenous patients, 56.8% were confirmed using RT-PCR, 4.4% (CI 95%:4.3-4.5) had at least one comorbidity, and 8.0% (CI 95%:7.9-8.2) were hospitalized. The majority of non-survivors were ≥60 years old (65.1% indigenous vs. 74.1% non-indigenous). The mortality in indigenous people was more than three times higher (11% vs. 2.9%). Indigenous people had a lower proportion of RT-PCR diagnoses; deaths were more frequent in younger patients and were less likely to be admitted to hospital. Mass vaccination may have controlled the incidence and mortality associated with COVID-19 in this population during the period of increased viral circulation.

HIV and SARS-CoV-2 Co-infection: Epidemiological, Clinical Features, and Future Implications for Clinical Care and Public Health for People Living with HIV (PLWH) and HIV Most-at-Risk Groups.

PURPOSE OF REVIEW: The purpose of this review is using the currently available clinical and epidemiological data, to identify key aspects to improve both the clinical management and public health response with regard SARS-CoV-2/HIV co-infection among HIV vulnerable populations and people living with HIV (PLWH). RECENT FINDINGS: While at the beginning of the COVID-19 pandemic, the lack of robust information on SARS-CoV-2/HIV coinfection prevented to have a clear picture of the synergies between them, currently available data strongly supports the importance of common structural factors on both the acquisition and clinical impact of these infections and the relevance of age, co-morbidities, and HIV viral load as associated worse prognosis factors among PLWH. Although more information is needed to better understand the biological, clinical, and epidemiological relationship between both infections, in the meanwhile, syndemic approaches to prevent SARS-CoV-2 among HIV higher risk groups and PLWH, targeting these population for SARS-CoV-2 vaccines and protocolizing early identification of HIV + patients with worse COVID-19 prognosis factors, are crucial strategies to decrease the overall impact of SARS-CoV-2 /HIV coinfection.

Imputation method to reduce undetected severe acute respiratory infection cases during the coronavirus disease outbreak in Brazil

INTRODUCTION: The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths. METHODS: The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics. RESULTS: Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases. CONCLUSIONS: The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical &epidemiological characteristics.

Imputation method to reduce undetected severe acute respiratory infection cases during the coronavirus disease outbreak in Brazil.

INTRODUCTION: The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths. METHODS: The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics. RESULTS: Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases. CONCLUSIONS: The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical & epidemiological characteristics.

A model to predict SARS-CoV-2 infection based on the first three-month surveillance data in Brazil.

OBJECTIVE: COVID-19 diagnosis is a critical problem, mainly due to the lack or delay in the test results. We aimed to obtain a model to predict SARS-CoV-2 infection in suspected patients reported to the Brazilian surveillance system. METHODS: We analysed suspected patients reported to the National Surveillance System that corresponded to the following case definition: patients with respiratory symptoms and fever, who travelled to regions with local or community transmission or who had close contact with a suspected or confirmed case. Based on variables routinely collected, we obtained a multiple model using logistic regression. The area under the receiver operating characteristic curve (AUC) and accuracy indicators were used for validation. RESULTS: We described 1468 COVID-19 cases (confirmed by RT-PCR) and 4271 patients with other illnesses. With a data subset including 80% of patients from Sao Paulo (SP) and Rio Janeiro (RJ), we obtained a function which reached an AUC of 95.54% (95% CI: 94.41-96.67%) for the diagnosis of COVID-19 and accuracy of 90.1% (sensitivity 87.62% and specificity 92.02%). In a validation dataset including the other 20% of patients from SP and RJ, this model exhibited an AUC of 95.01% (92.51-97.5%) and accuracy of 89.47% (sensitivity 87.32% and specificity 91.36%). CONCLUSION: We obtained a model suitable for the clinical diagnosis of COVID-19 based on routinely collected surveillance data. Applications of this tool include early identification for specific treatment and isolation, rational use of laboratory tests, and input for modelling epidemiological trends.

OBJECTIF: Le diagnostic du COVID-19 est un problème critique, principalement dû au manque ou au retard dans les résultats du test. Nous visions à obtenir un modèle pour prédire l'infection par le SRAS-CoV-2 chez les patients suspects signalés au système de surveillance brésilien. MÉTHODES: Nous avons analysé les patients suspects signalés au Système National de Surveillance qui correspondaient à la définition de cas suivante: patients présentant des symptômes respiratoires et de la fièvre, qui se sont rendus dans des régions à transmission locale ou communautaire ou qui ont eu des contacts étroits avec un cas suspect ou confirmé. Sur la base de variables collectées en routine, nous avons obtenu un modèle multiple en utilisant la régression logistique. L'aire sous la courbe caractéristique de fonctionnement du récepteur (AUC) et les indicateurs de précision ont été utilisés pour la validation. RÉSULTATS: Nous avons décrit 1.468 cas de COVID-19 (confirmés par RT-PCR) et 4.271 patients atteints d'autres maladies. Avec un sous-ensemble de données comprenant 80% de patients de Sao Paulo (SP) et de Rio de Janeiro (RJ), nous avons obtenu une fonction qui atteignait une AUC de 95,54% (IC95%: 94,41% - 96,67%) pour le diagnostic de COVID- 19 et une précision de 90,1% (sensibilité 87,62% et spécificité 92,02%). Dans un ensemble de données de validation incluant les 20% restants de patients de SP et de RJ, ce modèle présentait une AUC de 95,01% (92,51% - 97,5%) et une précision de 89,47% (sensibilité 87,32% et spécificité 91,36%). CONCLUSION: Nous avons obtenu un modèle adapté au diagnostic clinique du COVID-19 sur la base des données de surveillance collectées en routine. Les applications de cet outil comprennent l'identification précoce pour un traitement et un isolement spécifiques, l'utilisation rationnelle des tests de laboratoire et des données pour modéliser les tendances épidémiologiques.

Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil.

The first case of COVID-19 was detected in Brazil on 25 February 2020. We report and contextualize epidemiological, demographic and clinical findings for COVID-19 cases during the first 3 months of the epidemic. By 31 May 2020, 514,200 COVID-19 cases, including 29,314 deaths, had been reported in 75.3% (4,196 of 5,570) of municipalities across all five administrative regions of Brazil. The R0 value for Brazil was estimated at 3.1 (95% Bayesian credible interval = 2.4-5.5), with a higher median but overlapping credible intervals compared with some other seriously affected countries. A positive association between higher per-capita income and COVID-19 diagnosis was identified. Furthermore, the severe acute respiratory infection cases with unknown aetiology were associated with lower per-capita income. Co-circulation of six respiratory viruses was detected but at very low levels. These findings provide a comprehensive description of the ongoing COVID-19 epidemic in Brazil and may help to guide subsequent measures to control virus transmission.