Targeting vaccination against novel infections: risk, age and spatial structure for pandemic influenza in Great Britain
Identifieur interne : 002614 ( Main/Exploration ); précédent : 002613; suivant : 002615Targeting vaccination against novel infections: risk, age and spatial structure for pandemic influenza in Great Britain
Auteurs : Matt J. Keeling [Royaume-Uni] ; Peter J. White [Royaume-Uni]Source :
- Journal of the Royal Society Interface [ 1742-5689 ] ; 2011.
Abstract
The emergence of a novel strain of H1N1 influenza virus in Mexico in 2009, and its subsequent worldwide spread, has focused attention to the question of optimal deployment of mass vaccination campaigns. Here, we use three relatively simple models to address three issues of primary concern in the targeting of any vaccine. The advantages of such simple models are that the underlying assumptions and effects of individual parameters are relatively clear, and the impact of uncertainty in the parametrization can be readily assessed in the early stages of an outbreak. In particular, we examine whether targeting risk-groups, age-groups or spatial regions could be optimal in terms of reducing the predicted number of cases or severe effects; and how these targeted strategies vary as the epidemic progresses. We examine the conditions under which it is optimal to initially target vaccination towards those individuals within the population who are most at risk of severe effects of infection. Using age-structured mixing matrices, we show that targeting vaccination towards the more epidemiologically important age groups (5–14 year olds and then 15–24 year olds) leads to the greatest reduction in the epidemic growth and hence reduces the total number of cases. Finally, we consider how spatially targeting the vaccine towards regions of country worst affected could provide an advantage. We discuss how all three of these priorities change as both the speed at which vaccination can be deployed and the start of the vaccination programme is varied.
Url:
DOI: 10.1098/rsif.2010.0474
Affiliations:
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White</name><affiliation wicri:level="1"><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Modelling and Economics Unit, Health Protection Agency Centre for Infections, 61 Colindale Avenue, London NW9 5EQ</wicri:regionArea><wicri:noRegion>London NW9 5EQ</wicri:noRegion></affiliation><affiliation wicri:level="1"><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, Norfolk Place, London W2 1PG</wicri:regionArea><wicri:noRegion>London W2 1PG</wicri:noRegion></affiliation></author></analytic><monogr></monogr><series><title level="j" type="main">Journal of the Royal Society Interface</title><title level="j" type="abbrev">J. R. Soc. Interface</title><idno type="ISSN">1742-5689</idno><idno type="eISSN">1742-5662</idno><imprint><publisher>The Royal Society</publisher><date type="published">2011</date><date type="e-published">2010</date><biblScope unit="vol">8</biblScope><biblScope unit="issue">58</biblScope><biblScope unit="page" from="661">661</biblScope><biblScope unit="page" to="670">670</biblScope></imprint><idno type="ISSN">1742-5689</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1742-5689</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract">The emergence of a novel strain of H1N1 influenza virus in Mexico in 2009, and its subsequent worldwide spread, has focused attention to the question of optimal deployment of mass vaccination campaigns. Here, we use three relatively simple models to address three issues of primary concern in the targeting of any vaccine. The advantages of such simple models are that the underlying assumptions and effects of individual parameters are relatively clear, and the impact of uncertainty in the parametrization can be readily assessed in the early stages of an outbreak. In particular, we examine whether targeting risk-groups, age-groups or spatial regions could be optimal in terms of reducing the predicted number of cases or severe effects; and how these targeted strategies vary as the epidemic progresses. We examine the conditions under which it is optimal to initially target vaccination towards those individuals within the population who are most at risk of severe effects of infection. Using age-structured mixing matrices, we show that targeting vaccination towards the more epidemiologically important age groups (5–14 year olds and then 15–24 year olds) leads to the greatest reduction in the epidemic growth and hence reduces the total number of cases. Finally, we consider how spatially targeting the vaccine towards regions of country worst affected could provide an advantage. We discuss how all three of these priorities change as both the speed at which vaccination can be deployed and the start of the vaccination programme is varied.</div></front></TEI><affiliations><list><country><li>Royaume-Uni</li></country></list><tree><country name="Royaume-Uni"><noRegion><name sortKey="Keeling, Matt J" sort="Keeling, Matt J" uniqKey="Keeling M" first="Matt J." last="Keeling">Matt J. Keeling</name></noRegion><name sortKey="Keeling, Matt J" sort="Keeling, Matt J" uniqKey="Keeling M" first="Matt J." last="Keeling">Matt J. Keeling</name><name sortKey="White, Peter J" sort="White, Peter J" uniqKey="White P" first="Peter J." last="White">Peter J. White</name><name sortKey="White, Peter J" sort="White, Peter J" uniqKey="White P" first="Peter J." last="White">Peter J. White</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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