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      COVID-19 Epidemic Forecast in Brazil

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          Abstract

          This study advocates a novel spatio-temporal method for accurate prediction of COVID-19 epidemic occurrence probability at any time in any Brazil state of interest, and raw clinical observational data have been used. This article describes a novel bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient time period, resulting in robust long-term forecast of the virus outbreak probability. COVID-19 daily numbers of recorded patients in all affected Brazil states were taken into account. This work aimed to benchmark novel state-of-the-art methods, making it possible to analyse dynamically observed patient numbers while taking into account relevant regional mapping. Advocated approach may help to monitor and predict possible future epidemic outbreaks within a large variety of multi-regional biological systems. Suggested methodology may be used in various modern public health applications, efficiently using their clinical survey data.

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            A pneumonia outbreak associated with a new coronavirus of probable bat origin

            Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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              Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

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                Author and article information

                Journal
                Bioinform Biol Insights
                Bioinform Biol Insights
                BBI
                spbbi
                Bioinformatics and Biology Insights
                SAGE Publications (Sage UK: London, England )
                1177-9322
                11 April 2023
                2023
                11 April 2023
                : 17
                : 11779322231161939
                Affiliations
                [1 ]College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China
                [2 ]Department of Mechanical and Structural Engineering and Materials Science, University of Stavanger, Stavanger, Norway
                Author notes
                [*]Yihan Xing, University of Stavanger, 4036 Stavanger, P.O. Box 8600, Norway. Email: yihan.xing@ 123456uis.no
                Article
                10.1177_11779322231161939
                10.1177/11779322231161939
                10090958
                37065993
                85b698f9-47a8-4358-b9af-71b61758d320
                © The Author(s) 2023

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 29 November 2022
                : 16 February 2023
                Categories
                Original Research Article
                Custom metadata
                January-December 2023
                ts1

                Bioinformatics & Computational biology
                covid-19,epidemic outbreak,probability forecast,public health,mathematical biology

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