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Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination

The goal of this paper is to analyze the stochastic dynamics of childhood infectious disease time series. We present an univariate time series analysis of pertussis, mumps, measles and rubella based on Box-Jenkins or AutoRegressive Integrated Moving Average (ARIMA) modeling. The method, which enable...

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Detalles Bibliográficos
Autores principales: Trottier, Helen, Philippe, Pierre, Roy, Roch
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1584232/
https://www.ncbi.nlm.nih.gov/pubmed/16895599
http://dx.doi.org/10.1186/1742-7622-3-9
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author Trottier, Helen
Philippe, Pierre
Roy, Roch
author_facet Trottier, Helen
Philippe, Pierre
Roy, Roch
author_sort Trottier, Helen
collection PubMed
description The goal of this paper is to analyze the stochastic dynamics of childhood infectious disease time series. We present an univariate time series analysis of pertussis, mumps, measles and rubella based on Box-Jenkins or AutoRegressive Integrated Moving Average (ARIMA) modeling. The method, which enables the dependency structure embedded in time series data to be modeled, has potential research applications in studies of infectious disease dynamics. Canadian chronological series of pertussis, mumps, measles and rubella, before and after mass vaccination, are analyzed to characterize the statistical structure of these diseases. Despite the fact that these infectious diseases are biologically different, it is found that they are all represented by simple models with the same basic statistical structure. Aside from seasonal effects, the number of new cases is given by the incidence in the previous period and by periodically recurrent random factors. It is also shown that mass vaccination does not change this stochastic dependency. We conclude that the Box-Jenkins methodology does identify the collective pattern of the dynamics, but not the specifics of the diseases at the biological individual level.
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spelling pubmed-15842322006-10-02 Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination Trottier, Helen Philippe, Pierre Roy, Roch Emerg Themes Epidemiol Methodology The goal of this paper is to analyze the stochastic dynamics of childhood infectious disease time series. We present an univariate time series analysis of pertussis, mumps, measles and rubella based on Box-Jenkins or AutoRegressive Integrated Moving Average (ARIMA) modeling. The method, which enables the dependency structure embedded in time series data to be modeled, has potential research applications in studies of infectious disease dynamics. Canadian chronological series of pertussis, mumps, measles and rubella, before and after mass vaccination, are analyzed to characterize the statistical structure of these diseases. Despite the fact that these infectious diseases are biologically different, it is found that they are all represented by simple models with the same basic statistical structure. Aside from seasonal effects, the number of new cases is given by the incidence in the previous period and by periodically recurrent random factors. It is also shown that mass vaccination does not change this stochastic dependency. We conclude that the Box-Jenkins methodology does identify the collective pattern of the dynamics, but not the specifics of the diseases at the biological individual level. BioMed Central 2006-08-08 /pmc/articles/PMC1584232/ /pubmed/16895599 http://dx.doi.org/10.1186/1742-7622-3-9 Text en Copyright © 2006 Trottier et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Trottier, Helen
Philippe, Pierre
Roy, Roch
Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
title Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
title_full Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
title_fullStr Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
title_full_unstemmed Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
title_short Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
title_sort stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1584232/
https://www.ncbi.nlm.nih.gov/pubmed/16895599
http://dx.doi.org/10.1186/1742-7622-3-9
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