Evaluation of targeted influenza vaccination strategies via population modeling.

<h4>Background</h4>Because they can generate comparable predictions, mathematical models are ideal tools for evaluating alternative drug or vaccine allocation strategies. To remain credible, however, results must be consistent. Authors of a recent assessment of possible influenza vaccina...

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Autores principales:	John Glasser, Denis Taneri, Zhilan Feng, Jen-Hsiang Chuang, Peet Tüll, William Thompson, Mary Mason McCauley, James Alexander
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d130bb90621241c1a01f06cbf060cf48
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spelling	oai:doaj.org-article:d130bb90621241c1a01f06cbf060cf482021-11-18T06:35:03ZEvaluation of targeted influenza vaccination strategies via population modeling.1932-620310.1371/journal.pone.0012777https://doaj.org/article/d130bb90621241c1a01f06cbf060cf482010-09-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20862297/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Because they can generate comparable predictions, mathematical models are ideal tools for evaluating alternative drug or vaccine allocation strategies. To remain credible, however, results must be consistent. Authors of a recent assessment of possible influenza vaccination strategies conclude that older children, adolescents, and young adults are the optimal targets, no matter the objective, and argue for vaccinating them. Authors of two earlier studies concluded, respectively, that optimal targets depend on objectives and cautioned against changing policy. Which should we believe?<h4>Methods and findings</h4>In matrices whose elements are contacts between persons by age, the main diagonal always predominates, reflecting contacts between contemporaries. Indirect effects (e.g., impacts of vaccinating one group on morbidity or mortality in others) result from off-diagonal elements. Mixing matrices based on periods in proximity with others have greater sub- and super-diagonals, reflecting contacts between parents and children, and other off-diagonal elements (reflecting, e.g., age-independent contacts among co-workers), than those based on face-to-face conversations. To assess the impact of targeted vaccination, we used a time-usage study's mixing matrix and allowed vaccine efficacy to vary with age. And we derived mortality rates either by dividing observed deaths attributed to pneumonia and influenza by average annual cases from a demographically-realistic SEIRS model or by multiplying those rates by ratios of (versus adding to them differences between) pandemic and pre-pandemic mortalities.<h4>Conclusions</h4>In our simulations, vaccinating older children, adolescents, and young adults averts the most cases, but vaccinating either younger children and older adults or young adults averts the most deaths, depending on the age distribution of mortality. These results are consistent with those of the earlier studies.John GlasserDenis TaneriZhilan FengJen-Hsiang ChuangPeet TüllWilliam ThompsonMary Mason McCauleyJames AlexanderPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 9 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q John Glasser Denis Taneri Zhilan Feng Jen-Hsiang Chuang Peet Tüll William Thompson Mary Mason McCauley James Alexander Evaluation of targeted influenza vaccination strategies via population modeling.
description	<h4>Background</h4>Because they can generate comparable predictions, mathematical models are ideal tools for evaluating alternative drug or vaccine allocation strategies. To remain credible, however, results must be consistent. Authors of a recent assessment of possible influenza vaccination strategies conclude that older children, adolescents, and young adults are the optimal targets, no matter the objective, and argue for vaccinating them. Authors of two earlier studies concluded, respectively, that optimal targets depend on objectives and cautioned against changing policy. Which should we believe?<h4>Methods and findings</h4>In matrices whose elements are contacts between persons by age, the main diagonal always predominates, reflecting contacts between contemporaries. Indirect effects (e.g., impacts of vaccinating one group on morbidity or mortality in others) result from off-diagonal elements. Mixing matrices based on periods in proximity with others have greater sub- and super-diagonals, reflecting contacts between parents and children, and other off-diagonal elements (reflecting, e.g., age-independent contacts among co-workers), than those based on face-to-face conversations. To assess the impact of targeted vaccination, we used a time-usage study's mixing matrix and allowed vaccine efficacy to vary with age. And we derived mortality rates either by dividing observed deaths attributed to pneumonia and influenza by average annual cases from a demographically-realistic SEIRS model or by multiplying those rates by ratios of (versus adding to them differences between) pandemic and pre-pandemic mortalities.<h4>Conclusions</h4>In our simulations, vaccinating older children, adolescents, and young adults averts the most cases, but vaccinating either younger children and older adults or young adults averts the most deaths, depending on the age distribution of mortality. These results are consistent with those of the earlier studies.
format	article
author	John Glasser Denis Taneri Zhilan Feng Jen-Hsiang Chuang Peet Tüll William Thompson Mary Mason McCauley James Alexander
author_facet	John Glasser Denis Taneri Zhilan Feng Jen-Hsiang Chuang Peet Tüll William Thompson Mary Mason McCauley James Alexander
author_sort	John Glasser
title	Evaluation of targeted influenza vaccination strategies via population modeling.
title_short	Evaluation of targeted influenza vaccination strategies via population modeling.
title_full	Evaluation of targeted influenza vaccination strategies via population modeling.
title_fullStr	Evaluation of targeted influenza vaccination strategies via population modeling.
title_full_unstemmed	Evaluation of targeted influenza vaccination strategies via population modeling.
title_sort	evaluation of targeted influenza vaccination strategies via population modeling.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/d130bb90621241c1a01f06cbf060cf48
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Evaluation of targeted influenza vaccination strategies via population modeling.

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