H2N2V1, Main, Exploration, bibRecord, 001609

Semiparametric estimation of the duration of immunity from infectious disease time series: influenza as a case‐study

Identifieur interne : 001609 ( Main/Exploration ); précédent : 001608; suivant : 001610

Semiparametric estimation of the duration of immunity from infectious disease time series: influenza as a case‐study

Auteurs : Yingcun Xia [Singapour] ; Julia R. Gog [Royaume-Uni] ; Bryan T. Grenfell [États-Unis]

Source :

Journal of the Royal Statistical Society: Series C (Applied Statistics) [ 0035-9254 ] ; 2005-06.

RBID : ISTEX:5AAA04E43AF7B4AFD5869C8E209724A691ED9868

English descriptors

Teeft :
- Cile viboud, Constraint, Data sets, Decay function, Decay function estimates, Decay functions, Decay pattern, Different combinations, Dynamics, Estimation, Estimation method, Estimation methods, Estimation procedure, Estimation results, Finkenst, Grenfell, High level, Immune hosts, Immunity, Immunity function, Infection, Infectious disease time series, Infectious diseases, Infectious hosts, Kernel, Kernel function, Kernel weight, Last recovery, Linear model, Linear models, Link function, Mass action, Measles epidemics, National university, Netherlands, Netherlands institute, Next time unit, Oxford university press, Parameter, Parametric assumption, Popln biol, Population size, Primary health care, Relative immunity, Residual, Seasonal forces, Seasonal transmission parameters, Semiparametric, Semiparametric time series model, Semiparametric time series sirs model, Sirs mechanism, Subtype dynamics, Subtypes, Susceptible individuals, Test statistic, Time period, Time series, Time series data, Total number, Unknown function, Variance, Weekly cases, Weight function.

Abstract

Summary. An important epidemiological problem is to estimate the decay through time of immunity following infection. For this purpose, we propose a semiparametric time series epidemic model that is based on the mechanism of the susceptible–infected–recovered–susceptible system to analyse complex time series data. We develop an estimation method for the model. Simulations show that the approach proposed can capture the non‐linearity of epidemics as well as estimate the decay of immunity. We apply our approach to influenza in France and the Netherlands and show a rapid decline in immunity following infection, which agrees with recent spatiotemporal analyses.

Url:

https://api.istex.fr/ark:/67375/WNG-PFVGN95B-0/fulltext.pdf

DOI: 10.1111/j.1467-9876.2005.05383.x

Affiliations:

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Le document en format XML

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Semiparametric estimation of the duration of immunity from infectious disease time series: influenza as a case‐study

Semiparametric estimation of the duration of immunity from infectious disease time series: influenza as a case‐study

Source :

English descriptors

Abstract

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

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri