H2N2V1, Main, Exploration, bibRecord, 002186

Epidemiological models with age structure, proportionate mixing, and cross-immunity

Identifieur interne : 002186 ( Main/Exploration ); précédent : 002185; suivant : 002187

Epidemiological models with age structure, proportionate mixing, and cross-immunity

Auteurs : C. Castillo-Chavez [États-Unis] ; H. W. Hethcote [États-Unis] ; V. Andreasen [États-Unis] ; S. A. Levin [États-Unis] ; W. M. Liu [États-Unis]

Source :

Journal of Mathematical Biology [ 0303-6812 ] ; 1989-05-01.

RBID : ISTEX:36CE2C15AC16B055FFA18E3323302C49E9702035

English descriptors

Abstract

Abstract: Infection by one strain of influenza type A provides some protection (cross-immunity) against infection by a related strain. It is important to determine how this influences the observed co-circulation of comparatively minor variants of the H1N1 and H3N2 subtypes. To this end, we formulate discrete and continuous time models with two viral strains, cross-immunity, age structure, and infectious disease dynamics. Simulation and analysis of models with cross-immunity indicate that sustained oscillations cannot be maintained by age-specific infection activity level rates when the mortality rate is constant; but are possible if mortalities are age-specific, even if activity levels are independent of age. Sustained oscillations do not seem possible for a single-strain model, even in the presence of age-specific mortalities; and thus it is suggested that the interplay between cross-immunity and age-specific mortalities may underlie observed oscillations.

Url:

https://api.istex.fr/ark:/67375/1BB-NWB7SKG7-G/fulltext.pdf

DOI: 10.1007/BF00275810

Affiliations:

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Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Age structure</term>
<term>Cross-immunity</term>
<term>Infectious diseases</term>
<term>Influenza</term>
<term>Proportionate mixing</term>
</keywords>
<keywords scheme="Teeft" xml:lang="en"><term>Academic press</term>
<term>Activity level</term>
<term>Activity level rates</term>
<term>Activity levels</term>
<term>Andreasen</term>
<term>Berlin heidelberg</term>
<term>Characteristic equation</term>
<term>Characteristic equations</term>
<term>Coefficient</term>
<term>Complete immunity</term>
<term>Constant mortality rate</term>
<term>Constant recovery rate</term>
<term>Contact number</term>
<term>Contact rates</term>
<term>Continuous dependence</term>
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<term>Cornell university</term>
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<term>Different sets</term>
<term>Different values</term>
<term>Differential equations</term>
<term>Dimensional system</term>
<term>Disease dynamics</term>
<term>Dominant eigenvalues</term>
<term>Dynamics</term>
<term>Eigenvalue</term>
<term>Epidemiological</term>
<term>Epidemiological models</term>
<term>Equilibrium values</term>
<term>Further details</term>
<term>General case</term>
<term>Heterogeneous populations</term>
<term>Hethcote</term>
<term>Human population</term>
<term>Imaginary part</term>
<term>Imaginary parts</term>
<term>Incidence proportionality factors</term>
<term>Infectious diseases</term>
<term>Infectious period</term>
<term>Influenza</term>
<term>Influenza type</term>
<term>Influenza viruses</term>
<term>Initial boundary value problem</term>
<term>Initial conditions</term>
<term>Intermediate amplitude</term>
<term>Larger amplitude</term>
<term>Levin</term>
<term>Local stability analysis</term>
<term>Mathematical approaches</term>
<term>Mathematical ecology</term>
<term>Mathematical models</term>
<term>Minor variants</term>
<term>Mortality rate</term>
<term>Mortality rates</term>
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<term>Nontrivial equilibrium</term>
<term>Notes biomath</term>
<term>Orthant approach</term>
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<term>Simulation model</term>
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<term>Special case</term>
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<term>Strain model</term>
<term>Subtypes</term>
<term>Survivorship curve</term>
<term>Susceptibility</term>
<term>Threshold condition</term>
<term>Threshold quantity</term>
<term>Time approaches infinity</term>
<term>Time step</term>
<term>Transfer diagram</term>
<term>Transmission coefficient</term>
<term>Transmission coefficients</term>
<term>Transmission rates</term>
<term>Viral</term>
<term>Viral strains</term>
<term>York tokyo</term>
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<front><div type="abstract" xml:lang="en">Abstract: Infection by one strain of influenza type A provides some protection (cross-immunity) against infection by a related strain. It is important to determine how this influences the observed co-circulation of comparatively minor variants of the H1N1 and H3N2 subtypes. To this end, we formulate discrete and continuous time models with two viral strains, cross-immunity, age structure, and infectious disease dynamics. Simulation and analysis of models with cross-immunity indicate that sustained oscillations cannot be maintained by age-specific infection activity level rates when the mortality rate is constant; but are possible if mortalities are age-specific, even if activity levels are independent of age. Sustained oscillations do not seem possible for a single-strain model, even in the presence of age-specific mortalities; and thus it is suggested that the interplay between cross-immunity and age-specific mortalities may underlie observed oscillations.</div>
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Epidemiological models with age structure, proportionate mixing, and cross-immunity

Epidemiological models with age structure, proportionate mixing, and cross-immunity

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English descriptors

Abstract

Links toward previous steps (curation, corpus...)

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