Objective: Estimating the potential number of COVID-19 deaths in Brazil for the coming months.
Methods: The study included all confirmed cases of COVID-19 deaths, from the first confirmed death on March 17th to May 15th, 2020. These data were collected from an official Brazilian website of the Ministry of Health. The Boltzmann function was applied to a data simulation for each set of data regarding all states of the country.
Results: The model data were well-fitted, with R2 values close to 0.999. Up to May 15th, 14,817 COVID-19 deaths have been confirmed in the country. Amazonas has the highest rate of accumulated cases per 1,000,000 inhabitants (321.14), followed by Ceará (161.63). Rio de Janeiro, Roraima, Amazonas, Pará, and Pernambuco are estimated to experience a substantial increase in the rate of cumulative cases until July 15th. Mato Grosso do Sul, Paraná, Minas Gerais, Rio Grande do Sul, and Santa Catarina will show lower rates per 1,000,000 inhabitants.
Conclusion: We estimate a substantial increase in the rate of cumulative cases in Brazil over the next months. The Boltzmann function proved to be a simple tool for epidemiological forecasting that can assist in the planning of measures to contain COVID-19.
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http://dx.doi.org/10.1590/1980-549720200081 | DOI Listing |
Intern Emerg Med
January 2025
Emergency Department, National Institute of Medical Sciences and Nutrition Salvador Zubiran, Avenida Vasco de Quiróga No. 15, Colonia Belisario Domínguez Sección XVI, Alcaldía Tlalpan, CP 14080, Mexico City, Mexico.
The COVID-19 pandemic provided an ideal scenario for studying the care of the elderly population, we implemented a tool named the Geriatric Measure (GM) tool to determine the severity and need for hospitalization. The objective of the study is to evaluate if the results of a brief Geriatric Measure tool are associated with mortality and other outcomes among older adults with COVID-19 treated in the emergency department. Retrospective observational cohort study.
View Article and Find Full Text PDFLancet Public Health
January 2025
US Centers for Disease Control and Prevention, Atlanta, GA, USA.
Background: Rapid, accessible, and accurate testing was paramount to an effective US COVID-19 response. Federal partners supported SARS-CoV-2 testing scale-up through an interagency-coordinated approach that focused on expanding supply chains, research and development, validation, and improving patient access. We aimed to provide an overview of the federal efforts to scale up the testing response and study the impact of scale-up.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Industrial Engineering, Izmir University of Economics, Izmir, 35330, Türkiye. Electronic address:
Background: The severity of recent Coronavirus (COVID-19) pandemics has revealed the importance of development of inoculation strategies in case of limited vaccine availability. Authorities have implemented inoculation strategies based on perceived risk factors such as age and existence of other chronic health conditions for survivability from the disease. However, various other factors can be considered for identifying the preferred inoculation strategies depending on the vaccine availability and disease spread levels.
View Article and Find Full Text PDFJ Infect Public Health
December 2024
Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China. Electronic address:
The rapid global spread of Coronavirus Disease 2019 (COVID-19) has resulted in millions of infections and deaths, particularly impacting older adults. This study systematically analyzes risk factors reported in different geographical regions such as Asia and Europe that are associated with adverse outcomes in older adults with COVID-19. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched five databases up to December 2023 and conducted meta-analyses of odds ratios for 27 risk factors reported in at least two studies using R software (version 4.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Systems Engineering & Operations Research, George Mason University, Fairfax, VA, 22030, USA.
Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.
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