Mart L Stein1, Jim E van Steenbergen1, Vincent Buskens1, Peter G M van der Heijden1, Carl E Koppeschaar1, Linus Bengtsson1, Anna Thorson1, Mirjam E E Kretzschmar1. 1. Mart L. Stein and Mirjam E. E. Kretzschmar are with the Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Jim E. van Steenbergen is with the Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. Vincent Buskens is with the Department of Sociology, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Peter G. M. van der Heijden is with the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht. Carl E. Koppeschaar is with Science in Action BV, Amsterdam, the Netherlands. Linus Bengtsson and Anna Thorson are with the Department of Public Health Sciences-Global Health, Karolinska Institutet, Stockholm, Sweden.
Abstract
OBJECTIVES: We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants. METHODS: In 2014, volunteers from 2 large panels in the Netherlands were invited to complete a survey focusing on symptoms of upper respiratory tract infections and to invite 4 individuals they had met in the preceding 2 weeks to take part in the study. We compared sociodemographic characteristics among panel participants, individuals who volunteered for our survey, and individuals recruited via respondent-driven detection. RESULTS: Starting from 1015 panel members, the survey spread through all provinces of the Netherlands and all age groups in 83 days. A total of 433 individuals completed the survey via peer recruitment. Participants who reported symptoms were 6.1% (95% confidence interval = 5.4, 6.9) more likely to invite contact persons than were participants who did not report symptoms. Participants with symptoms invited more symptomatic recruits to take part than did participants without symptoms. CONCLUSIONS: Our findings suggest that online respondent-driven detection can enhance identification of symptomatic patients by making use of individuals' local social networks.
OBJECTIVES: We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants. METHODS: In 2014, volunteers from 2 large panels in the Netherlands were invited to complete a survey focusing on symptoms of upper respiratory tract infections and to invite 4 individuals they had met in the preceding 2 weeks to take part in the study. We compared sociodemographic characteristics among panel participants, individuals who volunteered for our survey, and individuals recruited via respondent-driven detection. RESULTS: Starting from 1015 panel members, the survey spread through all provinces of the Netherlands and all age groups in 83 days. A total of 433 individuals completed the survey via peer recruitment. Participants who reported symptoms were 6.1% (95% confidence interval = 5.4, 6.9) more likely to invite contact persons than were participants who did not report symptoms. Participants with symptoms invited more symptomatic recruits to take part than did participants without symptoms. CONCLUSIONS: Our findings suggest that online respondent-driven detection can enhance identification of symptomatic patients by making use of individuals' local social networks.
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