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The impact of media coverage on the transmission dynamics of human influenza
BACKGROUND: There is an urgent need to understand how the provision of information influences individual risk perception and how this in turn shapes the evolution of epidemics. Individuals are influenced by information in complex and unpredictable ways. Emerging infectious diseases, such as the rece...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317585/ https://www.ncbi.nlm.nih.gov/pubmed/21356134 http://dx.doi.org/10.1186/1471-2458-11-S1-S5 |
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author | Tchuenche, Jean M Dube, Nothabo Bhunu, Claver P Smith?, Robert J Bauch, Chris T |
author_facet | Tchuenche, Jean M Dube, Nothabo Bhunu, Claver P Smith?, Robert J Bauch, Chris T |
author_sort | Tchuenche, Jean M |
collection | PubMed |
description | BACKGROUND: There is an urgent need to understand how the provision of information influences individual risk perception and how this in turn shapes the evolution of epidemics. Individuals are influenced by information in complex and unpredictable ways. Emerging infectious diseases, such as the recent swine flu epidemic, may be particular hotspots for a media-fueled rush to vaccination; conversely, seasonal diseases may receive little media attention, despite their high mortality rate, due to their perceived lack of newness. METHODS: We formulate a deterministic transmission and vaccination model to investigate the effects of media coverage on the transmission dynamics of influenza. The population is subdivided into different classes according to their disease status. The compartmental model includes the effect of media coverage on reporting the number of infections as well as the number of individuals successfully vaccinated. RESULTS: A threshold parameter (the basic reproductive ratio) is analytically derived and used to discuss the local stability of the disease-free steady state. The impact of costs that can be incurred, which include vaccination, education, implementation and campaigns on media coverage, are also investigated using optimal control theory. A simplified version of the model with pulse vaccination shows that the media can trigger a vaccinating panic if the vaccine is imperfect and simplified messages result in the vaccinated mixing with the infectives without regard to disease risk. CONCLUSIONS: The effects of media on an outbreak are complex. Simplified understandings of disease epidemiology, propogated through media soundbites, may make the disease significantly worse. |
format | Online Article Text |
id | pubmed-3317585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33175852012-04-04 The impact of media coverage on the transmission dynamics of human influenza Tchuenche, Jean M Dube, Nothabo Bhunu, Claver P Smith?, Robert J Bauch, Chris T BMC Public Health Research BACKGROUND: There is an urgent need to understand how the provision of information influences individual risk perception and how this in turn shapes the evolution of epidemics. Individuals are influenced by information in complex and unpredictable ways. Emerging infectious diseases, such as the recent swine flu epidemic, may be particular hotspots for a media-fueled rush to vaccination; conversely, seasonal diseases may receive little media attention, despite their high mortality rate, due to their perceived lack of newness. METHODS: We formulate a deterministic transmission and vaccination model to investigate the effects of media coverage on the transmission dynamics of influenza. The population is subdivided into different classes according to their disease status. The compartmental model includes the effect of media coverage on reporting the number of infections as well as the number of individuals successfully vaccinated. RESULTS: A threshold parameter (the basic reproductive ratio) is analytically derived and used to discuss the local stability of the disease-free steady state. The impact of costs that can be incurred, which include vaccination, education, implementation and campaigns on media coverage, are also investigated using optimal control theory. A simplified version of the model with pulse vaccination shows that the media can trigger a vaccinating panic if the vaccine is imperfect and simplified messages result in the vaccinated mixing with the infectives without regard to disease risk. CONCLUSIONS: The effects of media on an outbreak are complex. Simplified understandings of disease epidemiology, propogated through media soundbites, may make the disease significantly worse. BioMed Central 2011-02-25 /pmc/articles/PMC3317585/ /pubmed/21356134 http://dx.doi.org/10.1186/1471-2458-11-S1-S5 Text en Copyright ©2011 Tchuenche et al; 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 cited. |
spellingShingle | Research Tchuenche, Jean M Dube, Nothabo Bhunu, Claver P Smith?, Robert J Bauch, Chris T The impact of media coverage on the transmission dynamics of human influenza |
title | The impact of media coverage on the transmission dynamics of human influenza |
title_full | The impact of media coverage on the transmission dynamics of human influenza |
title_fullStr | The impact of media coverage on the transmission dynamics of human influenza |
title_full_unstemmed | The impact of media coverage on the transmission dynamics of human influenza |
title_short | The impact of media coverage on the transmission dynamics of human influenza |
title_sort | impact of media coverage on the transmission dynamics of human influenza |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317585/ https://www.ncbi.nlm.nih.gov/pubmed/21356134 http://dx.doi.org/10.1186/1471-2458-11-S1-S5 |
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