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Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation
There have been many research works on epidemic spreading by mathematical or simulation methods. However, to make it practical as a decision support tool for policy maker, it should be combined with business operation of epidemic control. Thus, an alert and response framework covering outbreak detec...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120482/ http://dx.doi.org/10.1007/978-3-540-72588-6_166 |
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author | Tian, Chunhua Zhang, Xun Ding, Wei Cao, Rongzeng |
author_facet | Tian, Chunhua Zhang, Xun Ding, Wei Cao, Rongzeng |
author_sort | Tian, Chunhua |
collection | PubMed |
description | There have been many research works on epidemic spreading by mathematical or simulation methods. However, to make it practical as a decision support tool for policy maker, it should be combined with business operation of epidemic control. Thus, an alert and response framework covering outbreak detection, policy analysis and policy execution is proposed in this paper. Key technologies for such a framework at modeling, analysis and data collection aspects are discussed. Sensitivity analysis is proposed for model verification and confidence analysis. Critical point identification is another important topic for control policy making by network topology analysis. The importance and feasibility of these technologies are illustrated by the experiment on Beijing SARS (Severe Acute Respiratory Syndrome) data in 2003. |
format | Online Article Text |
id | pubmed-7120482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71204822020-04-06 Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation Tian, Chunhua Zhang, Xun Ding, Wei Cao, Rongzeng Computational Science – ICCS 2007 Article There have been many research works on epidemic spreading by mathematical or simulation methods. However, to make it practical as a decision support tool for policy maker, it should be combined with business operation of epidemic control. Thus, an alert and response framework covering outbreak detection, policy analysis and policy execution is proposed in this paper. Key technologies for such a framework at modeling, analysis and data collection aspects are discussed. Sensitivity analysis is proposed for model verification and confidence analysis. Critical point identification is another important topic for control policy making by network topology analysis. The importance and feasibility of these technologies are illustrated by the experiment on Beijing SARS (Severe Acute Respiratory Syndrome) data in 2003. 2007 /pmc/articles/PMC7120482/ http://dx.doi.org/10.1007/978-3-540-72588-6_166 Text en © Springer Berlin Heidelberg 2007 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 | Article Tian, Chunhua Zhang, Xun Ding, Wei Cao, Rongzeng Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation |
title | Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation |
title_full | Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation |
title_fullStr | Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation |
title_full_unstemmed | Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation |
title_short | Epidemic Alert & Response Framework and Technology Based on Spreading Dynamics Simulation |
title_sort | epidemic alert & response framework and technology based on spreading dynamics simulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120482/ http://dx.doi.org/10.1007/978-3-540-72588-6_166 |
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