Online Respondent-Driven Sampling for Studying Contact Patterns Relevant for the Spread of Close-Contact Pathogens: A Pilot Study in Thailand

Abstract

BackgroundInformation 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 MethodsWe 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.ResultsWe 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.ConclusionsDespite 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.

A Web 2.0 and Epidemiology Mash-Up: Using Respondent-Driven Sampling in Combination with Social Network Site Recruitment to Reach Young Transwomen

“…WebRDS uses an online Internet portal to assign unique identifiers to participants and enable them to generate electronic coupons and linked email messages which can be sent to peer referrals (26). Few studies have utilized webRDS (33-37), and none have been applied to young transgender populations. However, there is evidence that webRDS may be advantageous for hidden youth populations for whom research participation may be stigmatizing (38).…”

Enhancing Syndromic Surveillance With Online Respondent-Driven Detection

“…ASeedRec participants who completed the survey had the opportunity to join a raffle for 1 of 10 gift cards of €25. More details on the survey system are provided in Appendix A (available as a supplement to this article at http://www.ajph.org) and in Stein et al 10…”

“…Under certain conditions, such a recruitment method permits stepwise and controlled sampling of contacts of contacts, and so forth, in social networks in the general population. 10 We asked PS volunteers to complete a questionnaire and to invite their contacts into the study. In this way, we collected data on chains of contacts to analyze whether other symptomatic individuals could be detected via the local social network of symptomatic respondents.…”

The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations

“…Numerous studies have used websites and social media to recruit participants (Adler et al, 2014;Altshuler, Gerns Storey, & Prager, 2015;Barratt et al, 2015;Bauermeister et al, 2012;Ben-Ezra et al, 2013;Camacho et al, 2013;Chaulk & Jones, 2011;Dal Moro, 2013;Harris et al, 2014;Hernandez-Romieu et al, 2014;Janiec, Zielicka-Hardy, Polkowska, Rogalska, & Sadkowska-Todys, 2012;Jones, Saksvig, Grieser, & Young, 2012;Klein, Thomas, & Sutter, 2007;Moreno, Grant, Kacvinsky, Egan, & Fleming, 2012;Schumacher et al, 2014;Stein et al, 2014;Sueki, 2015;Thomas, Heysell, Houpt, Moore, & Keller, 2014;Turbow, Kent, & Jiang, 2008; van Genderen, Slobbe, Koene, Mastenbroek, & Overbosch, 2013;Zhang, Bi, Hiller, & Lv, 2008;Zheluk, Quinn, & Meylakhs, 2014). Online recruitment is a convenient method of reaching samples for rare outcomes (Schumacher et al, 2014) or hidden or difficult to reach populations (Barratt et al, 2015;Hernandez-Romieu et al, 2014).…”

“…Similar to Twitter, Facebook may be used for active or passive data collection. It has frequently been used to recruit participants (Altshuler et al, 2015;Barratt et al, 2015;Bauermeister et al, 2012;Ben-Ezra et al, 2013;Hernandez-Romieu et al, 2014;Schumacher et al, 2014;Stein et al, 2014;Thomas et al, 2014;van Genderen et al, 2013), but the information created by users has also been used for research.…”