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Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children

BACKGROUND: Respiratory syncytial virus (RSV) is a major cause of paediatric morbidity. Mathematical models can be used to characterise annual RSV seasonal epidemics and are a valuable tool to assess the impact of future vaccines. OBJECTIVES: Construct a mathematical model of seasonal epidemics of R...

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Autores principales: Moore, Hannah C., Jacoby, Peter, Hogan, Alexandra B., Blyth, Christopher C., Mercer, Geoffry N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072624/
https://www.ncbi.nlm.nih.gov/pubmed/24968133
http://dx.doi.org/10.1371/journal.pone.0100422
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author Moore, Hannah C.
Jacoby, Peter
Hogan, Alexandra B.
Blyth, Christopher C.
Mercer, Geoffry N.
author_facet Moore, Hannah C.
Jacoby, Peter
Hogan, Alexandra B.
Blyth, Christopher C.
Mercer, Geoffry N.
author_sort Moore, Hannah C.
collection PubMed
description BACKGROUND: Respiratory syncytial virus (RSV) is a major cause of paediatric morbidity. Mathematical models can be used to characterise annual RSV seasonal epidemics and are a valuable tool to assess the impact of future vaccines. OBJECTIVES: Construct a mathematical model of seasonal epidemics of RSV and by fitting to a population-level RSV dataset, obtain a better understanding of RSV transmission dynamics. METHODS: We obtained an extensive dataset of weekly RSV testing data in children aged less than 2 years, 2000–2005, for a birth cohort of 245,249 children through linkage of laboratory and birth record datasets. We constructed a seasonally forced compartmental age-structured Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) mathematical model to fit to the seasonal curves of positive RSV detections using the Nelder-Mead method. RESULTS: From 15,830 specimens, 3,394 were positive for RSV. RSV detections exhibited a distinct biennial seasonal pattern with alternating sized peaks in winter months. Our SEIRS model accurately mimicked the observed data with alternating sized peaks using disease parameter values that remained constant across the 6 years of data. Variations in the duration of immunity and recovery periods were explored. The best fit to the data minimising the residual sum of errors was a model using estimates based on previous models in the literature for the infectious period and a slightly lower estimate for the immunity period. CONCLUSIONS: Our age-structured model based on routinely collected population laboratory data accurately captures the observed seasonal epidemic curves. The compartmental SEIRS model, based on several assumptions, now provides a validated base model. Ranges for the disease parameters in the model that could replicate the patterns in the data were identified. Areas for future model developments include fitting climatic variables to the seasonal parameter, allowing parameters to vary according to age and implementing a newborn vaccination program to predict the effect on RSV incidence.
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spelling pubmed-40726242014-07-02 Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children Moore, Hannah C. Jacoby, Peter Hogan, Alexandra B. Blyth, Christopher C. Mercer, Geoffry N. PLoS One Research Article BACKGROUND: Respiratory syncytial virus (RSV) is a major cause of paediatric morbidity. Mathematical models can be used to characterise annual RSV seasonal epidemics and are a valuable tool to assess the impact of future vaccines. OBJECTIVES: Construct a mathematical model of seasonal epidemics of RSV and by fitting to a population-level RSV dataset, obtain a better understanding of RSV transmission dynamics. METHODS: We obtained an extensive dataset of weekly RSV testing data in children aged less than 2 years, 2000–2005, for a birth cohort of 245,249 children through linkage of laboratory and birth record datasets. We constructed a seasonally forced compartmental age-structured Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) mathematical model to fit to the seasonal curves of positive RSV detections using the Nelder-Mead method. RESULTS: From 15,830 specimens, 3,394 were positive for RSV. RSV detections exhibited a distinct biennial seasonal pattern with alternating sized peaks in winter months. Our SEIRS model accurately mimicked the observed data with alternating sized peaks using disease parameter values that remained constant across the 6 years of data. Variations in the duration of immunity and recovery periods were explored. The best fit to the data minimising the residual sum of errors was a model using estimates based on previous models in the literature for the infectious period and a slightly lower estimate for the immunity period. CONCLUSIONS: Our age-structured model based on routinely collected population laboratory data accurately captures the observed seasonal epidemic curves. The compartmental SEIRS model, based on several assumptions, now provides a validated base model. Ranges for the disease parameters in the model that could replicate the patterns in the data were identified. Areas for future model developments include fitting climatic variables to the seasonal parameter, allowing parameters to vary according to age and implementing a newborn vaccination program to predict the effect on RSV incidence. Public Library of Science 2014-06-26 /pmc/articles/PMC4072624/ /pubmed/24968133 http://dx.doi.org/10.1371/journal.pone.0100422 Text en © 2014 Moore et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Moore, Hannah C.
Jacoby, Peter
Hogan, Alexandra B.
Blyth, Christopher C.
Mercer, Geoffry N.
Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children
title Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children
title_full Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children
title_fullStr Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children
title_full_unstemmed Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children
title_short Modelling the Seasonal Epidemics of Respiratory Syncytial Virus in Young Children
title_sort modelling the seasonal epidemics of respiratory syncytial virus in young children
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072624/
https://www.ncbi.nlm.nih.gov/pubmed/24968133
http://dx.doi.org/10.1371/journal.pone.0100422
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