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Age groups and spread of influenza: implications for vaccination strategy
BACKGROUND: The unpredictable nature of the potentially devastating impact of 2009 pH1N1 influenza pandemic highlights the need for pandemic preparedness planning, where modeling studies could be most useful for simulations of possible future scenarios. METHODS: A compartmental model with pre-sympto...
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Formato: | Texto |
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BioMed Central
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2876165/ https://www.ncbi.nlm.nih.gov/pubmed/20429954 http://dx.doi.org/10.1186/1471-2334-10-106 |
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author | Hsieh, Ying-Hen |
author_facet | Hsieh, Ying-Hen |
author_sort | Hsieh, Ying-Hen |
collection | PubMed |
description | BACKGROUND: The unpredictable nature of the potentially devastating impact of 2009 pH1N1 influenza pandemic highlights the need for pandemic preparedness planning, where modeling studies could be most useful for simulations of possible future scenarios. METHODS: A compartmental model with pre-symptomatic and asymptomatic influenza infections is proposed which incorporates age groups as well as intervention measures such as age-specific vaccination, in order to study spread of influenza in a community. RESULTS: We derive the basic reproduction number and other effective reproduction numbers under various intervention measures. For illustration, we make use of the Pneumonia and Influenza (P&I) mortality data and vaccination data of the very young (age 0-2) and the very old (age >64) during 2004-2005 Taiwan winter influenza season to fit our model and to compute the relevant reproduction numbers. The reproduction number for this winter flu season is estimated to be slightly above one (~1.0001). CONCLUSIONS: Comparatively large errors in fitting the P&I mortality data of the elderly (>64) were observed shortly after winter school closings in January, which may indicate the impact of younger, more active age groups transmitting influenza to other age groups outside of the school settings; in particular, to the elderly in the households. Pre-symptomatic infections seemed to have little effect on the model fit, while asymptomatic infection by asymptomatic infectives has a more pronounced impact on the model fit for the elderly mortality, perhaps indicating a larger role in disease transmission by asymptomatic infection. Simulations indicate that the impact of vaccination on the disease incidence might not be fully revealed in the change (or the lack thereof) in the effective reproduction number with interventions, but could still be substantial. The estimated per contact transmission probability for susceptible elderly is significantly higher than that of any other age group, perhaps highlighting the vulnerability of the elderly due to close contacts with their caretakers from other age groups. The relative impact of targeting the very young and the very old for vaccination was weakened by their relative inactivity, thus giving evidence of the lack of impact of vaccinating these two groups on the overall transmissibility of the disease in the community. This further underscores the need for morbidity-based strategy to prevent elderly mortality. |
format | Text |
id | pubmed-2876165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-28761652010-05-26 Age groups and spread of influenza: implications for vaccination strategy Hsieh, Ying-Hen BMC Infect Dis Research Article BACKGROUND: The unpredictable nature of the potentially devastating impact of 2009 pH1N1 influenza pandemic highlights the need for pandemic preparedness planning, where modeling studies could be most useful for simulations of possible future scenarios. METHODS: A compartmental model with pre-symptomatic and asymptomatic influenza infections is proposed which incorporates age groups as well as intervention measures such as age-specific vaccination, in order to study spread of influenza in a community. RESULTS: We derive the basic reproduction number and other effective reproduction numbers under various intervention measures. For illustration, we make use of the Pneumonia and Influenza (P&I) mortality data and vaccination data of the very young (age 0-2) and the very old (age >64) during 2004-2005 Taiwan winter influenza season to fit our model and to compute the relevant reproduction numbers. The reproduction number for this winter flu season is estimated to be slightly above one (~1.0001). CONCLUSIONS: Comparatively large errors in fitting the P&I mortality data of the elderly (>64) were observed shortly after winter school closings in January, which may indicate the impact of younger, more active age groups transmitting influenza to other age groups outside of the school settings; in particular, to the elderly in the households. Pre-symptomatic infections seemed to have little effect on the model fit, while asymptomatic infection by asymptomatic infectives has a more pronounced impact on the model fit for the elderly mortality, perhaps indicating a larger role in disease transmission by asymptomatic infection. Simulations indicate that the impact of vaccination on the disease incidence might not be fully revealed in the change (or the lack thereof) in the effective reproduction number with interventions, but could still be substantial. The estimated per contact transmission probability for susceptible elderly is significantly higher than that of any other age group, perhaps highlighting the vulnerability of the elderly due to close contacts with their caretakers from other age groups. The relative impact of targeting the very young and the very old for vaccination was weakened by their relative inactivity, thus giving evidence of the lack of impact of vaccinating these two groups on the overall transmissibility of the disease in the community. This further underscores the need for morbidity-based strategy to prevent elderly mortality. BioMed Central 2010-04-30 /pmc/articles/PMC2876165/ /pubmed/20429954 http://dx.doi.org/10.1186/1471-2334-10-106 Text en Copyright ©2010 Hsieh; 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 Article Hsieh, Ying-Hen Age groups and spread of influenza: implications for vaccination strategy |
title | Age groups and spread of influenza: implications for vaccination strategy |
title_full | Age groups and spread of influenza: implications for vaccination strategy |
title_fullStr | Age groups and spread of influenza: implications for vaccination strategy |
title_full_unstemmed | Age groups and spread of influenza: implications for vaccination strategy |
title_short | Age groups and spread of influenza: implications for vaccination strategy |
title_sort | age groups and spread of influenza: implications for vaccination strategy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2876165/ https://www.ncbi.nlm.nih.gov/pubmed/20429954 http://dx.doi.org/10.1186/1471-2334-10-106 |
work_keys_str_mv | AT hsiehyinghen agegroupsandspreadofinfluenzaimplicationsforvaccinationstrategy |