Profile and Outcomes of Hospitalized COVID-19 Patients during the Prevalence of the Omicron Variant According to the Brazilian Regions: A Retrospective Cohort Study from 2022.

We investigated the clinical-epidemiological profile and outcomes of COVID-19 patients hospitalized in 2022, during the Omicron variant/subvariant prevalence, in different Brazilian regions to identify the most vulnerable subgroups requiring special attention. Data from COVID-19 patients were extracted from the national Information System for Epidemiological Surveillance of Influenza (SIVEP-Gripe database), and analyses stratified by region and age group were conducted. The constructed dataset encompassed clinical-epidemiological information, intensive care unit admission, invasive and non-invasive ventilation requirements, vaccination status, and evolution (cure or death).

Risks of Adverse Outcomes for Hospitalized COVID-19 Patients during the Four Waves in Brazil According to SARS-CoV-2 Variants, Age Group, and Vaccine Status.

Brazil was hit with four consecutive waves of COVID-19 until 2022 due to the ancestral SARS-CoV-2 (B.1 lineage), followed by the emergence of variants/subvariants. Relative risks of adverse outcomes for COVID-19 patients hospitalized during the four waves were evaluated.

Clinical symptom profile of hospitalized COVID-19 Brazilian patients according to SARS-CoV-2 variants.

Objectives: The aim of this study was to investigate the prevalence of the main symptoms in Brazilian coronavirus disease 2019 (COVID-19) patients hospitalized during 4 distinct waves, based on their infection with different severe acute respiratory disease coronavirus 2 (SARS-CoV-2) variants.

Methods: This study included hospitalized patients who tested positive for SARS-CoV-2 during 15 weeks around the peak of each of 4 waves: W1, ancestral strain/B.1 lineage (May 31 to September 12, 2020); W2, Gamma/P.

Profile of Brazilian inpatients with COVID-19 vaccine breakthrough infection and risk factors for unfavorable outcome.

Objective: To characterize the epidemiological and clinical profile of individuals more likely to become infected with SARS-CoV-2 after the fully vaccination schedule in order to profile priority groups to receive a booster dose in situations of vaccine doses shortage as well as for maintenance of personal protective care.

Methods: This cross-sectional study used data from hospitalized COVID-19 patients aged ≥18 years, who had been fully vaccinated and had a SARS-CoV-2 infection positive diagnosis collected from the SIVEP-Gripe database (Influenza Epidemiological Surveillance Information System) from January 18, 2021 to September 15, 2021. Demographic data, clinical symptoms and preexisting medical conditions (comorbidities) were analyzed.

An overview of Brazilian working age adults vulnerability to COVID-19.

Brazil is a country of continental dimensions, where many smaller countries would fit. In addition to demographic, socioeconomic, and cultural differences, hospital infrastructure and healthcare varies across all 27 federative units. Therefore, the evolution of COVID-19 pandemic did not manifest itself in a homogeneous and predictable trend across the nation.

A temporal study of Brazilian pregnant and postpartum women vulnerability for COVID-19: Characteristics, risk factors and outcomes.

Background: During the COVID-19 second wave in Brazil, there has been a significant increase in the number of daily cases and deaths, including pregnant and postpartum women. We assess risk factors and outcomes for this priority group compared to the COVID-19 non-pregnant cohort in two epidemic waves.

Methods: In this retrospective cohort study we evaluated data of hospitalized pregnant, postpartum, and nonpregnant women aged 15-44 years, between epidemiological weeks 2020-8 and 2021-15, who tested positive for SARS-CoV-2, retrieved from the Influenza Epidemiological Surveillance Information System maintained by Ministry of Health of Brazil.

MoHRiPA-An Architecture for Hybrid Resources Management of Private Cloud Environments.

The high demand for data processing in web applications has grown in recent years due to the increased computing infrastructure supply as a service in a cloud computing ecosystem. This ecosystem offers benefits such as broad network access, elasticity, and resource sharing, among others. However, properly exploiting these benefits requires optimized provisioning of computational resources in the target infrastructure.

Predicting the Disease Outcome in COVID-19 Positive Patients Through Machine Learning: A Retrospective Cohort Study With Brazilian Data.

The first officially registered case of COVID-19 in Brazil was on February 26, 2020. Since then, the situation has worsened with more than 672, 000 confirmed cases and at least 36, 000 reported deaths by June 2020. Accurate diagnosis of patients with COVID-19 is extremely important to offer adequate treatment, and avoid overloading the healthcare system.

On the analysis of mortality risk factors for hospitalized COVID-19 patients: A data-driven study using the major Brazilian database.

Background: Brazil became the epicenter of the COVID-19 epidemic in a brief period of a few months after the first officially registered case. The knowledge of the epidemiological/clinical profile and the risk factors of Brazilian COVID-19 patients can assist in the decision making of physicians in the implementation of early and most appropriate measures for poor prognosis patients. However, these reports are missing.

Towards a Fog-Enabled Intelligent Transportation System to Reduce Traffic Jam.

Frustrations, monetary losses, lost time, high fuel consumption and CO 2 emissions are some of the problems caused by traffic jams in urban centers. In an attempt to solve this problem, this article proposes a traffic service to control congestion, named FOXS-Fast Offset Xpath Service. FOXS aims to reduce the problems generated by a traffic jam in a distributed way through roads classification and the suggestion of new routes to vehicles.

An Integrated Dead Reckoning with Cooperative Positioning Solution to Assist GPS NLOS Using Vehicular Communications.

In Intelligent Transportation Systems (ITS), the Vehicular Ad Hoc Networks (VANETs) paradigm based on the WAVE IEEE 802.11p standard is the main alternative for inter-vehicle communications. Recently, many protocols, applications, and services have been developed with a wide range of objectives, ranging from comfort to security.

Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments.

Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT.