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Modeling the impact of changes in day-care contact patterns on the dynamics of varicella transmission in France between 1991 and 2015

Authors :
Vittoria Colizza
Piero Poletti
Valentina Marziano
Pierre-Yves Boëlle
Guillaume Béraud
Stefano Merler
Centre hospitalier universitaire de Poitiers (CHU Poitiers)
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS)
Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)
Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP)
Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)
Source :
PLoS Computational Biology, PLoS Computational Biology, Public Library of Science, 2018, 14 (8), pp.e1006334. ⟨10.1371/journal.pcbi.1006334⟩, PLoS Computational Biology, 2018, 14 (8), pp.e1006334. ⟨10.1371/journal.pcbi.1006334⟩, PLoS Computational Biology, Vol 14, Iss 8, p e1006334 (2018)
Publication Year :
2018
Publisher :
Public Library of Science, 2018.

Abstract

Annual incidence rates of varicella infection in the general population in France have been rather stable since 1991 when clinical surveillance started. Rates however show a statistically significant increase over time in children aged 0–3 years, and a decline in older individuals. A significant increase in day-care enrolment and structures’ capacity in France was also observed in the last decade. In this work we investigate the potential interplay between an increase of contacts of young children possibly caused by earlier socialization in the community and varicella transmission dynamics. To this aim, we develop an age-structured mathematical model, informed with historical demographic data and contact matrix estimates in the country, accounting for longitudinal linear increase of early childhood contacts. While the reported overall varicella incidence is well reproduced independently of mixing variations, age-specific empirical trends are better captured by accounting for an increase in contacts among pre-school children in the last decades. We found that the varicella data are consistent with a 30% increase in the number of contacts at day-care facilities, which would imply a 50% growth in the contribution of 0-3y old children to overall yearly infections in 1991–2015. Our findings suggest that an earlier exposure to pathogens due to changes in day-care contact patterns, represents a plausible explanation for the epidemiological patterns observed in France. Obtained results suggest that considering temporal changes in social factors in addition to demographic ones is critical to correctly interpret varicella transmission dynamics.<br />Author summary During the last decades, an increasing circulation of varicella in the early childhood has been observed in France. A plausible explanation of this trend may rely on the progressive increase of day-care attendance in the past years, which could have anticipated the exposure of young children to the infection. We propose a retrospective modelling study to assess whether the varicella dynamics in France since 1991 can be explained in terms of increasing day-care contacts of children under 3 years of age. To this aim, we develop a model including demographic changes and variations in age-specific contact rates over time. Our findings suggest that a 30% increase of day-care contacts in early childhood can explain the observed epidemiological trends. Obtained results highlight that temporal changes in contact patterns can significantly affect the transmission of childhood infectious diseases and should therefore be considered when investigating medium and long-term epidemiological patterns. A better understanding of the interplay between changing social behavior and disease transmission can help the interpretation of surveillance data and the design of effective and targeted intervention strategies.

Details

Language :
English
ISSN :
15537358 and 1553734X
Volume :
14
Issue :
8
Database :
OpenAIRE
Journal :
PLoS Computational Biology
Accession number :
edsair.doi.dedup.....10939cb4bc210c328cf2de9d2312a7be