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Discovering network behind infectious disease outbreak
Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stoc...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125928/ https://www.ncbi.nlm.nih.gov/pubmed/32288081 http://dx.doi.org/10.1016/j.physa.2010.07.014 |
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author | Maeno, Yoshiharu |
author_facet | Maeno, Yoshiharu |
author_sort | Maeno, Yoshiharu |
collection | PubMed |
description | Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stochastic spreads over the network from a dataset on an infectious disease outbreak in the early growth phase. Populations in a combination of epidemiological compartment models and a meta-population network model are described by stochastic differential equations. Probability density functions are derived from the equations and used for the maximal likelihood estimation of the topology and parameters. The method is tested with computationally synthesized datasets and the WHO dataset on the SARS outbreak. |
format | Online Article Text |
id | pubmed-7125928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71259282020-04-08 Discovering network behind infectious disease outbreak Maeno, Yoshiharu Physica A Article Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stochastic spreads over the network from a dataset on an infectious disease outbreak in the early growth phase. Populations in a combination of epidemiological compartment models and a meta-population network model are described by stochastic differential equations. Probability density functions are derived from the equations and used for the maximal likelihood estimation of the topology and parameters. The method is tested with computationally synthesized datasets and the WHO dataset on the SARS outbreak. Elsevier B.V. 2010-11-01 2010-07-16 /pmc/articles/PMC7125928/ /pubmed/32288081 http://dx.doi.org/10.1016/j.physa.2010.07.014 Text en Copyright © 2010 Elsevier B.V. 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 Maeno, Yoshiharu Discovering network behind infectious disease outbreak |
title | Discovering network behind infectious disease outbreak |
title_full | Discovering network behind infectious disease outbreak |
title_fullStr | Discovering network behind infectious disease outbreak |
title_full_unstemmed | Discovering network behind infectious disease outbreak |
title_short | Discovering network behind infectious disease outbreak |
title_sort | discovering network behind infectious disease outbreak |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125928/ https://www.ncbi.nlm.nih.gov/pubmed/32288081 http://dx.doi.org/10.1016/j.physa.2010.07.014 |
work_keys_str_mv | AT maenoyoshiharu discoveringnetworkbehindinfectiousdiseaseoutbreak |