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COVID-19 Epidemic Forecast in Brazil
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 suitab...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090958/ https://www.ncbi.nlm.nih.gov/pubmed/37065993 http://dx.doi.org/10.1177/11779322231161939 |
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author | Gaidai, Oleg Xing, Yihan |
author_facet | Gaidai, Oleg Xing, Yihan |
author_sort | Gaidai, Oleg |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10090958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-100909582023-04-12 COVID-19 Epidemic Forecast in Brazil Gaidai, Oleg Xing, Yihan Bioinform Biol Insights Original Research Article 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. SAGE Publications 2023-04-11 /pmc/articles/PMC10090958/ /pubmed/37065993 http://dx.doi.org/10.1177/11779322231161939 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/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). |
spellingShingle | Original Research Article Gaidai, Oleg Xing, Yihan COVID-19 Epidemic Forecast in Brazil |
title | COVID-19 Epidemic Forecast in Brazil |
title_full | COVID-19 Epidemic Forecast in Brazil |
title_fullStr | COVID-19 Epidemic Forecast in Brazil |
title_full_unstemmed | COVID-19 Epidemic Forecast in Brazil |
title_short | COVID-19 Epidemic Forecast in Brazil |
title_sort | covid-19 epidemic forecast in brazil |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090958/ https://www.ncbi.nlm.nih.gov/pubmed/37065993 http://dx.doi.org/10.1177/11779322231161939 |
work_keys_str_mv | AT gaidaioleg covid19epidemicforecastinbrazil AT xingyihan covid19epidemicforecastinbrazil |