Simulation Studies of Influenza Epidemics: Assessment of Parameter Estimation and Sensitivity
Identifieur interne : 006643 ( Main/Exploration ); précédent : 006642; suivant : 006644Simulation Studies of Influenza Epidemics: Assessment of Parameter Estimation and Sensitivity
Auteurs : Ira M. Longini [États-Unis] ; Susan K. Seaholm [États-Unis] ; Eugene Ackerman [États-Unis] ; James S. Koopman [États-Unis] ; Arnold S. Monto [États-Unis]Source :
- International Journal of Epidemiology [ 0300-5771 ] ; 1984.
Abstract
Longini I M (Department of Statistics and Biometry, Emory University, Uppergate House, Atlanta, Georgia 30322, USA), Seaholm S K, Ackerman E, Koopman J S and Monto A S. Simulation studies of influenza epidemics: assessment of parameter estimation and sensitivity. International Journal of Epidemiology 1984, 13: 496-501. The influenza simulation model of Elveback et al7 is used to evaluate the accuracy of the maximum likelihood procedure of Longini et al3 for estimating the secondary attack rate in households. The sample population from the Tecumseh Respiratory Illness Study is mapped into the simulation model and simulations are carried out over a range of parameter values and conditions, some of which were derived from influenza seasons in Tecumseh and from the Seattle Flu Study for the years 1975–1980. The estimation procedure is found to be quite robust for parameter values preset within appropriate limits for influenza. However, a significant difference is found between the preset and estimated household contact parameter for epidemics of medium and high intensity when the preset value is zero. Incremental increases in the household contact parameter are shown to produce marked increases in the overall infection attack rate demonstrating that household spread is an important link in maintaining infection in other mixing groups such as schools, preschool groups and neighbourhood clusters of households.
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DOI: 10.1093/ije/13.4.496
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Monto</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><placeName><region type="state">Michigan</region></placeName><wicri:cityArea>Department of Epidemiology, School of Public Health, The University of Michigan Ann Arbor</wicri:cityArea></affiliation></author></analytic><monogr></monogr><series><title level="j" type="main">International Journal of Epidemiology</title><idno type="eISSN">1464-3685</idno><idno type="ISSN">0300-5771</idno><imprint><publisher>Oxford University Press</publisher><date type="published">1984</date><biblScope unit="vol">13</biblScope><biblScope unit="issue">4</biblScope><biblScope unit="page" from="496">496</biblScope><biblScope unit="page" to="501">501</biblScope></imprint><idno type="ISSN">0300-5771</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0300-5771</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract">Longini I M (Department of Statistics and Biometry, Emory University, Uppergate House, Atlanta, Georgia 30322, USA), Seaholm S K, Ackerman E, Koopman J S and Monto A S. Simulation studies of influenza epidemics: assessment of parameter estimation and sensitivity. International Journal of Epidemiology 1984, 13: 496-501. The influenza simulation model of Elveback et al7 is used to evaluate the accuracy of the maximum likelihood procedure of Longini et al3 for estimating the secondary attack rate in households. The sample population from the Tecumseh Respiratory Illness Study is mapped into the simulation model and simulations are carried out over a range of parameter values and conditions, some of which were derived from influenza seasons in Tecumseh and from the Seattle Flu Study for the years 1975–1980. The estimation procedure is found to be quite robust for parameter values preset within appropriate limits for influenza. However, a significant difference is found between the preset and estimated household contact parameter for epidemics of medium and high intensity when the preset value is zero. Incremental increases in the household contact parameter are shown to produce marked increases in the overall infection attack rate demonstrating that household spread is an important link in maintaining infection in other mixing groups such as schools, preschool groups and neighbourhood clusters of households.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Michigan</li><li>Minnesota</li></region></list><tree><country name="États-Unis"><region name="Michigan"><name sortKey="Longini, Ira M" sort="Longini, Ira M" uniqKey="Longini I" first="Ira M" last="Longini">Ira M. Longini</name></region><name sortKey="Ackerman, Eugene" sort="Ackerman, Eugene" uniqKey="Ackerman E" first="Eugene" last="Ackerman">Eugene Ackerman</name><name sortKey="Koopman, James S" sort="Koopman, James S" uniqKey="Koopman J" first="James S" last="Koopman">James S. Koopman</name><name sortKey="Monto, Arnold S" sort="Monto, Arnold S" uniqKey="Monto A" first="Arnold S" last="Monto">Arnold S. Monto</name><name sortKey="Seaholm, Susan K" sort="Seaholm, Susan K" uniqKey="Seaholm S" first="Susan K" last="Seaholm">Susan K. Seaholm</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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