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Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium
BACKGROUND: Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been ca...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656518/ https://www.ncbi.nlm.nih.gov/pubmed/19154612 http://dx.doi.org/10.1186/1471-2334-9-5 |
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author | Hens, Niel Goeyvaerts, Nele Aerts, Marc Shkedy, Ziv Van Damme, Pierre Beutels, Philippe |
author_facet | Hens, Niel Goeyvaerts, Nele Aerts, Marc Shkedy, Ziv Van Damme, Pierre Beutels, Philippe |
author_sort | Hens, Niel |
collection | PubMed |
description | BACKGROUND: Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts. METHODS: Participants kept a paper diary with information on their contacts over two different days. A contact was defined as a two-way conversation of at least three words in each others proximity. The contact information included the age of the contact, gender, location, duration, frequency, and whether or not touching was involved. For data analysis, we used association rules and classification trees. Weighted generalized estimating equations were used to analyze contact frequency while accounting for the correlation between contacts reported on the two different days. A contact surface, expressing the average number of contacts between persons of different ages was obtained by a bivariate smoothing approach and the relation to the so-called next-generation matrix was established. RESULTS: People mostly mixed with people of similar age, or with their offspring, their parents and their grandparents. By imputing professional contacts, the average number of daily contacts increased from 11.84 to 15.70. The number of reported contacts depended heavily on the household size, class size for children and number of professional contacts for adults. Adults living with children had on average 2 daily contacts more than adults living without children. In the holiday period, the daily contact frequency for children and adolescents decreased with about 19% while a similar observation is made for adults in the weekend. These findings can be used to estimate the impact of school closure. CONCLUSION: We conducted a diary based contact survey in Belgium to gain insights in social interactions relevant to the spread of infectious diseases. The resulting contact patterns are useful to improve estimating crucial parameters for infectious disease transmission models. |
format | Text |
id | pubmed-2656518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26565182009-03-17 Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium Hens, Niel Goeyvaerts, Nele Aerts, Marc Shkedy, Ziv Van Damme, Pierre Beutels, Philippe BMC Infect Dis Research Article BACKGROUND: Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts. METHODS: Participants kept a paper diary with information on their contacts over two different days. A contact was defined as a two-way conversation of at least three words in each others proximity. The contact information included the age of the contact, gender, location, duration, frequency, and whether or not touching was involved. For data analysis, we used association rules and classification trees. Weighted generalized estimating equations were used to analyze contact frequency while accounting for the correlation between contacts reported on the two different days. A contact surface, expressing the average number of contacts between persons of different ages was obtained by a bivariate smoothing approach and the relation to the so-called next-generation matrix was established. RESULTS: People mostly mixed with people of similar age, or with their offspring, their parents and their grandparents. By imputing professional contacts, the average number of daily contacts increased from 11.84 to 15.70. The number of reported contacts depended heavily on the household size, class size for children and number of professional contacts for adults. Adults living with children had on average 2 daily contacts more than adults living without children. In the holiday period, the daily contact frequency for children and adolescents decreased with about 19% while a similar observation is made for adults in the weekend. These findings can be used to estimate the impact of school closure. CONCLUSION: We conducted a diary based contact survey in Belgium to gain insights in social interactions relevant to the spread of infectious diseases. The resulting contact patterns are useful to improve estimating crucial parameters for infectious disease transmission models. BioMed Central 2009-01-20 /pmc/articles/PMC2656518/ /pubmed/19154612 http://dx.doi.org/10.1186/1471-2334-9-5 Text en Copyright ©2009 Hens 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 | Research Article Hens, Niel Goeyvaerts, Nele Aerts, Marc Shkedy, Ziv Van Damme, Pierre Beutels, Philippe Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium |
title | Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium |
title_full | Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium |
title_fullStr | Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium |
title_full_unstemmed | Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium |
title_short | Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium |
title_sort | mining social mixing patterns for infectious disease models based on a two-day population survey in belgium |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656518/ https://www.ncbi.nlm.nih.gov/pubmed/19154612 http://dx.doi.org/10.1186/1471-2334-9-5 |
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