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Projecting social contact matrices in 152 countries using contact surveys and demographic data
Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patter...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5609774/ https://www.ncbi.nlm.nih.gov/pubmed/28898249 http://dx.doi.org/10.1371/journal.pcbi.1005697 |
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author | Prem, Kiesha Cook, Alex R. Jit, Mark |
author_facet | Prem, Kiesha Cook, Alex R. Jit, Mark |
author_sort | Prem, Kiesha |
collection | PubMed |
description | Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models’ realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available. |
format | Online Article Text |
id | pubmed-5609774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56097742017-10-09 Projecting social contact matrices in 152 countries using contact surveys and demographic data Prem, Kiesha Cook, Alex R. Jit, Mark PLoS Comput Biol Research Article Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models’ realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available. Public Library of Science 2017-09-12 /pmc/articles/PMC5609774/ /pubmed/28898249 http://dx.doi.org/10.1371/journal.pcbi.1005697 Text en © 2017 Prem 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Prem, Kiesha Cook, Alex R. Jit, Mark Projecting social contact matrices in 152 countries using contact surveys and demographic data |
title | Projecting social contact matrices in 152 countries using contact surveys and demographic data |
title_full | Projecting social contact matrices in 152 countries using contact surveys and demographic data |
title_fullStr | Projecting social contact matrices in 152 countries using contact surveys and demographic data |
title_full_unstemmed | Projecting social contact matrices in 152 countries using contact surveys and demographic data |
title_short | Projecting social contact matrices in 152 countries using contact surveys and demographic data |
title_sort | projecting social contact matrices in 152 countries using contact surveys and demographic data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5609774/ https://www.ncbi.nlm.nih.gov/pubmed/28898249 http://dx.doi.org/10.1371/journal.pcbi.1005697 |
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