Browsing by Author "Xin Lu"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    PublicationMetadata only
    Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and The Netherlands using respondent-driven sampling
    (2014-11-25) Mart L. Stein; Jim E. Van Steenbergen; Vincent Buskens; Peter G.M. Van Der Heijden; Charnchudhi Chanyasanha; Mathuros Tipayamongkholgul; Anna E. Thorson; Linus Bengtsson; Xin Lu; Mirjam E.E. Kretzschmar; University Medical Center Utrecht; National Institute of Public Health and the Environment; Leiden University Medical Center - LUMC; Utrecht University; University of Southampton; Mahidol University; Karolinska Institutet; National University of Defense Technology; Flowminder Foundation
    © 2014 Stein et al. 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.
  • No Thumbnail Available
    PublicationMetadata only
    Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: A pilot study in Thailand
    (2014-01-08) Mart L. Stein; Jim E. Van Steenbergen; Charnchudhi Chanyasanha; Mathuros Tipayamongkholgul; Vincent Buskens; Peter G.M. Van Der Heijden; Wasamon Sabaiwan; Linus Bengtsson; Xin Lu; Anna E. Thorson; Mirjam E.E. Kretzschmar; University Medical Center Utrecht; National Institute of Public Health and the Environment; Leiden University Medical Center - LUMC; Mahidol University; Utrecht University; University of Southampton; Chulalongkorn University; Karolinska Institutet; National University of Defense Technology
    Background: Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens. Materials and Methods: We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks. Results: We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts. Conclusions: Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks. © 2014 Stein et al.