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SQEIR: An epidemic virus spread analysis and prediction model
In 2019, a new strain of coronavirus pneumonia spread quickly worldwide. Viral propagation may be simulated using the Susceptible Infectious Removed (SIR) model. However, the SIR model fails to consider that separation of patients in the COVID-19 incubation stage entails difficulty and that these pa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9364756/ https://www.ncbi.nlm.nih.gov/pubmed/35965689 http://dx.doi.org/10.1016/j.compeleceng.2022.108230 |
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author | Wu, Yichun Sun, Yaqi Lin, Mugang |
author_facet | Wu, Yichun Sun, Yaqi Lin, Mugang |
author_sort | Wu, Yichun |
collection | PubMed |
description | In 2019, a new strain of coronavirus pneumonia spread quickly worldwide. Viral propagation may be simulated using the Susceptible Infectious Removed (SIR) model. However, the SIR model fails to consider that separation of patients in the COVID-19 incubation stage entails difficulty and that these patients have high transmission potential. The model also ignores the positive effect of quarantine measures on the spread of the epidemic. To address the two flaws in the SIR model, this study proposes a new infectious disease model referred to as the Susceptible Quarantined Exposed Infective Removed (SQEIR) model. The proposed model uses the weighted least squares for the optimal estimation of important parameters in the infectious disease model. Based on these parameters, new differential equations were developed to describe the spread of the epidemic. The experimental results show that this model exhibits an accuracy 6.7% higher than that of traditional infectious disease models. |
format | Online Article Text |
id | pubmed-9364756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93647562022-08-10 SQEIR: An epidemic virus spread analysis and prediction model Wu, Yichun Sun, Yaqi Lin, Mugang Comput Electr Eng Article In 2019, a new strain of coronavirus pneumonia spread quickly worldwide. Viral propagation may be simulated using the Susceptible Infectious Removed (SIR) model. However, the SIR model fails to consider that separation of patients in the COVID-19 incubation stage entails difficulty and that these patients have high transmission potential. The model also ignores the positive effect of quarantine measures on the spread of the epidemic. To address the two flaws in the SIR model, this study proposes a new infectious disease model referred to as the Susceptible Quarantined Exposed Infective Removed (SQEIR) model. The proposed model uses the weighted least squares for the optimal estimation of important parameters in the infectious disease model. Based on these parameters, new differential equations were developed to describe the spread of the epidemic. The experimental results show that this model exhibits an accuracy 6.7% higher than that of traditional infectious disease models. Elsevier Ltd. 2022-09 2022-08-10 /pmc/articles/PMC9364756/ /pubmed/35965689 http://dx.doi.org/10.1016/j.compeleceng.2022.108230 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Wu, Yichun Sun, Yaqi Lin, Mugang SQEIR: An epidemic virus spread analysis and prediction model |
title | SQEIR: An epidemic virus spread analysis and prediction model |
title_full | SQEIR: An epidemic virus spread analysis and prediction model |
title_fullStr | SQEIR: An epidemic virus spread analysis and prediction model |
title_full_unstemmed | SQEIR: An epidemic virus spread analysis and prediction model |
title_short | SQEIR: An epidemic virus spread analysis and prediction model |
title_sort | sqeir: an epidemic virus spread analysis and prediction model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9364756/ https://www.ncbi.nlm.nih.gov/pubmed/35965689 http://dx.doi.org/10.1016/j.compeleceng.2022.108230 |
work_keys_str_mv | AT wuyichun sqeiranepidemicvirusspreadanalysisandpredictionmodel AT sunyaqi sqeiranepidemicvirusspreadanalysisandpredictionmodel AT linmugang sqeiranepidemicvirusspreadanalysisandpredictionmodel |