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Multi-regional COVID-19 epidemic forecast in Sweden
The novel coronavirus disease 2019 (COVID-19) is a contagious disease with high transmissibility to spread worldwide, reported to present a certain burden on worldwide public health. This study aimed to determine epidemic occurrence probability at any reasonable time horizon in any region of interes...
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/PMC10017956/ https://www.ncbi.nlm.nih.gov/pubmed/36937694 http://dx.doi.org/10.1177/20552076231162984 |
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author | Xing, Yihan Gaidai, Oleg |
author_facet | Xing, Yihan Gaidai, Oleg |
author_sort | Xing, Yihan |
collection | PubMed |
description | The novel coronavirus disease 2019 (COVID-19) is a contagious disease with high transmissibility to spread worldwide, reported to present a certain burden on worldwide public health. This study aimed to determine epidemic occurrence probability at any reasonable time horizon in any region of interest by applying modern novel statistical methods directly to raw clinical data. This paper describes a novel bio-system reliability approach, particularly suitable for multi-regional health and stationary environmental systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of the highly pathogenic virus outbreak probability. For this study, COVID-19 daily recorded patient numbers in most affected Sweden regions were chosen. This work aims to benchmark state-of-the-art methods, making it possible to extract necessary information from dynamically observed patient numbers while considering relevant territorial mapping. The method proposed in this paper opens up the possibility of accurately predicting epidemic outbreak probability for multi-regional biological systems. Based on their clinical survey data, the suggested methodology can be used in various public health applications. A novel spatiotemporal health system reliability method has been developed and applied to COVID-19 epidemic data. Accurate multi-regional epidemic occurrence prediction is made. Epidemic threshold confidence bands given. |
format | Online Article Text |
id | pubmed-10017956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-100179562023-03-17 Multi-regional COVID-19 epidemic forecast in Sweden Xing, Yihan Gaidai, Oleg Digit Health Original Research The novel coronavirus disease 2019 (COVID-19) is a contagious disease with high transmissibility to spread worldwide, reported to present a certain burden on worldwide public health. This study aimed to determine epidemic occurrence probability at any reasonable time horizon in any region of interest by applying modern novel statistical methods directly to raw clinical data. This paper describes a novel bio-system reliability approach, particularly suitable for multi-regional health and stationary environmental systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of the highly pathogenic virus outbreak probability. For this study, COVID-19 daily recorded patient numbers in most affected Sweden regions were chosen. This work aims to benchmark state-of-the-art methods, making it possible to extract necessary information from dynamically observed patient numbers while considering relevant territorial mapping. The method proposed in this paper opens up the possibility of accurately predicting epidemic outbreak probability for multi-regional biological systems. Based on their clinical survey data, the suggested methodology can be used in various public health applications. A novel spatiotemporal health system reliability method has been developed and applied to COVID-19 epidemic data. Accurate multi-regional epidemic occurrence prediction is made. Epidemic threshold confidence bands given. SAGE Publications 2023-03-14 /pmc/articles/PMC10017956/ /pubmed/36937694 http://dx.doi.org/10.1177/20552076231162984 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 Xing, Yihan Gaidai, Oleg Multi-regional COVID-19 epidemic forecast in Sweden |
title | Multi-regional COVID-19 epidemic forecast
in Sweden |
title_full | Multi-regional COVID-19 epidemic forecast
in Sweden |
title_fullStr | Multi-regional COVID-19 epidemic forecast
in Sweden |
title_full_unstemmed | Multi-regional COVID-19 epidemic forecast
in Sweden |
title_short | Multi-regional COVID-19 epidemic forecast
in Sweden |
title_sort | multi-regional covid-19 epidemic forecast
in sweden |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017956/ https://www.ncbi.nlm.nih.gov/pubmed/36937694 http://dx.doi.org/10.1177/20552076231162984 |
work_keys_str_mv | AT xingyihan multiregionalcovid19epidemicforecastinsweden AT gaidaioleg multiregionalcovid19epidemicforecastinsweden |