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Modelling the effects of media during an influenza epidemic
BACKGROUND: Mass media is used to inform individuals regarding diseases within a population. The effects of mass media during disease outbreaks have been studied in the mathematical modelling literature, by including ‘media functions’ that affect transmission rates in mathematical epidemiological mo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001363/ https://www.ncbi.nlm.nih.gov/pubmed/24742139 http://dx.doi.org/10.1186/1471-2458-14-376 |
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author | Collinson, Shannon Heffernan, Jane M |
author_facet | Collinson, Shannon Heffernan, Jane M |
author_sort | Collinson, Shannon |
collection | PubMed |
description | BACKGROUND: Mass media is used to inform individuals regarding diseases within a population. The effects of mass media during disease outbreaks have been studied in the mathematical modelling literature, by including ‘media functions’ that affect transmission rates in mathematical epidemiological models. The choice of function to employ, however, varies, and thus, epidemic outcomes that are important to inform public health may be affected. METHODS: We present a survey of the disease modelling literature with the effects of mass media. We present a comparison of the functions employed and compare epidemic results parameterized for an influenza outbreak. An agent-based Monte Carlo simulation is created to access variability around key epidemic measurements, and a sensitivity analysis is completed in order to gain insight into which model parameters have the largest influence on epidemic outcomes. RESULTS: Epidemic outcome depends on the media function chosen. Parameters that most influence key epidemic outcomes are different for each media function. CONCLUSION: Different functions used to represent the effects of media during an epidemic will affect the outcomes of a disease model, including the variability in key epidemic measurements. Thus, media functions may not best represent the effects of media during an epidemic. A new method for modelling the effects of media needs to be considered. |
format | Online Article Text |
id | pubmed-4001363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40013632014-05-09 Modelling the effects of media during an influenza epidemic Collinson, Shannon Heffernan, Jane M BMC Public Health Research Article BACKGROUND: Mass media is used to inform individuals regarding diseases within a population. The effects of mass media during disease outbreaks have been studied in the mathematical modelling literature, by including ‘media functions’ that affect transmission rates in mathematical epidemiological models. The choice of function to employ, however, varies, and thus, epidemic outcomes that are important to inform public health may be affected. METHODS: We present a survey of the disease modelling literature with the effects of mass media. We present a comparison of the functions employed and compare epidemic results parameterized for an influenza outbreak. An agent-based Monte Carlo simulation is created to access variability around key epidemic measurements, and a sensitivity analysis is completed in order to gain insight into which model parameters have the largest influence on epidemic outcomes. RESULTS: Epidemic outcome depends on the media function chosen. Parameters that most influence key epidemic outcomes are different for each media function. CONCLUSION: Different functions used to represent the effects of media during an epidemic will affect the outcomes of a disease model, including the variability in key epidemic measurements. Thus, media functions may not best represent the effects of media during an epidemic. A new method for modelling the effects of media needs to be considered. BioMed Central 2014-04-17 /pmc/articles/PMC4001363/ /pubmed/24742139 http://dx.doi.org/10.1186/1471-2458-14-376 Text en Copyright © 2014 Collinson and Heffernan; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Collinson, Shannon Heffernan, Jane M Modelling the effects of media during an influenza epidemic |
title | Modelling the effects of media during an influenza epidemic |
title_full | Modelling the effects of media during an influenza epidemic |
title_fullStr | Modelling the effects of media during an influenza epidemic |
title_full_unstemmed | Modelling the effects of media during an influenza epidemic |
title_short | Modelling the effects of media during an influenza epidemic |
title_sort | modelling the effects of media during an influenza epidemic |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001363/ https://www.ncbi.nlm.nih.gov/pubmed/24742139 http://dx.doi.org/10.1186/1471-2458-14-376 |
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