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PLoS One. 2014 Nov 25;9(11):e113711. doi: 10.1371/journal.pone.0113711. eCollection 2014.

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and The Netherlands using respondent-driven sampling.

Author information

1
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
2
Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; Centre for Infectious Diseases, Leiden University Medical Centre, Leiden, The Netherlands.
3
Faculty of Social and Behavioural Sciences, University Utrecht, Utrecht, The Netherlands.
4
Faculty of Social and Behavioural Sciences, University Utrecht, Utrecht, The Netherlands; Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, United Kingdom.
5
Department of Microbiology, Faculty of Public Health, Mahidol University, Bangkok, Thailand.
6
Department of Epidemiology, Faculty of Public Health, Mahidol University, Bangkok, Thailand.
7
Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
8
Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden; Flowminder Foundation, Stockholm, Sweden.
9
Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden; College of Information System and Management, National University of Defense Technology, Changsha, China; Flowminder Foundation, Stockholm, Sweden.

Abstract

Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in The Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in The Netherlands and Thailand.

PMID:
25423343
PMCID:
PMC4244136
DOI:
10.1371/journal.pone.0113711
[Indexed for MEDLINE]
Free PMC Article

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