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SARS epidemical forecast research in mathematical model
The SIJR model, simplified from the SEIJR model, is adopted to analyze the important parameters of the model of SARS epidemic such as the transmission rate, basic reproductive number. And some important parameters are obtained such as the transmission rate by applying this model to analyzing the sit...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Science in China Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089478/ https://www.ncbi.nlm.nih.gov/pubmed/32214715 http://dx.doi.org/10.1360/04we0073 |
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author | Guanghong, Ding Chang, Liu Jianqiu, Gong Ling, Wang Ke, Cheng Di, Zhang |
author_facet | Guanghong, Ding Chang, Liu Jianqiu, Gong Ling, Wang Ke, Cheng Di, Zhang |
author_sort | Guanghong, Ding |
collection | PubMed |
description | The SIJR model, simplified from the SEIJR model, is adopted to analyze the important parameters of the model of SARS epidemic such as the transmission rate, basic reproductive number. And some important parameters are obtained such as the transmission rate by applying this model to analyzing the situation in Hong Kong, Singapore and Canada at the outbreak of SARS. Then forecast of the transmission of SARS is drawn out here by the adjustment of parameters (such as quarantined rate) in the model. It is obvious that inflexion lies on the crunode of the graph, which indicates the big difference in transmission characteristics between the epidemic under control and not under control. This model can also be used in the comparison of the control effectiveness among different regions. The results from this model match well with the actual data in Hong Kong, Singapore and Canada and as a by-product, the index of the effectiveness of control in the later period can be acquired. It offers some quantitative indexes, which may help the further research in epidemic diseases. |
format | Online Article Text |
id | pubmed-7089478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Science in China Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-70894782020-03-23 SARS epidemical forecast research in mathematical model Guanghong, Ding Chang, Liu Jianqiu, Gong Ling, Wang Ke, Cheng Di, Zhang Chin Sci Bull Articles The SIJR model, simplified from the SEIJR model, is adopted to analyze the important parameters of the model of SARS epidemic such as the transmission rate, basic reproductive number. And some important parameters are obtained such as the transmission rate by applying this model to analyzing the situation in Hong Kong, Singapore and Canada at the outbreak of SARS. Then forecast of the transmission of SARS is drawn out here by the adjustment of parameters (such as quarantined rate) in the model. It is obvious that inflexion lies on the crunode of the graph, which indicates the big difference in transmission characteristics between the epidemic under control and not under control. This model can also be used in the comparison of the control effectiveness among different regions. The results from this model match well with the actual data in Hong Kong, Singapore and Canada and as a by-product, the index of the effectiveness of control in the later period can be acquired. It offers some quantitative indexes, which may help the further research in epidemic diseases. Science in China Press 2013-03-22 2004 /pmc/articles/PMC7089478/ /pubmed/32214715 http://dx.doi.org/10.1360/04we0073 Text en © Science in China Press 2004 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Articles Guanghong, Ding Chang, Liu Jianqiu, Gong Ling, Wang Ke, Cheng Di, Zhang SARS epidemical forecast research in mathematical model |
title | SARS epidemical forecast research in mathematical model |
title_full | SARS epidemical forecast research in mathematical model |
title_fullStr | SARS epidemical forecast research in mathematical model |
title_full_unstemmed | SARS epidemical forecast research in mathematical model |
title_short | SARS epidemical forecast research in mathematical model |
title_sort | sars epidemical forecast research in mathematical model |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089478/ https://www.ncbi.nlm.nih.gov/pubmed/32214715 http://dx.doi.org/10.1360/04we0073 |
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