Enhancing Syndromic Surveillance With Online Respondent-Driven Detection

Overview

Journal Am J Public Health

Specialty Public Health

Date 2015 Jun 13

PMID 26066940

Citations 7

Authors

Mart L Stein

Jim E van Steenbergen

Vincent Buskens

Peter G M van der Heijden

Carl E Koppeschaar

Linus Bengtsson

Anna Thorson

Mirjam E E Kretzschmar

Affiliations

Soon will be listed here.

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.

Citing Articles

Improving web-based respondent-driven sampling performance among men who have sex with men in the Netherlands.

Diexer S, Teslya A, Buskens V, Matser A, Stein M, Kretzschmar M PLOS Digit Health. 2023; 2(2):e0000192.

PMID: 36812647 PMC: 9931300. DOI: 10.1371/journal.pdig.0000192.

Dutch public health professionals' perspectives and needs regarding citizen involvement in COVID-19 contact tracing through digital support tools: an exploratory qualitative study.

Helms Y, Stein M, Hamdiui N, van der Meer A, Baron R, Eilers R BMC Health Serv Res. 2022; 22(1):1378.

PMID: 36403008 PMC: 9675960. DOI: 10.1186/s12913-022-08764-y.

Online respondent-driven detection for enhanced contact tracing of close-contact infectious diseases: benefits and barriers for public health practice.

Helms Y, Hamdiui N, Eilers R, Hoebe C, Dukers-Muijrers N, van den Kerkhof H BMC Infect Dis. 2021; 21(1):358.

PMID: 33863279 PMC: 8051831. DOI: 10.1186/s12879-021-06052-4.

Applications and Recruitment Performance of Web-Based Respondent-Driven Sampling: Scoping Review.

Helms Y, Hamdiui N, Kretzschmar M, Rocha L, van Steenbergen J, Bengtsson L J Med Internet Res. 2021; 23(1):e17564.

PMID: 33448935 PMC: 7846441. DOI: 10.2196/17564.

A stochastic simulation model to study respondent-driven recruitment.

Stein M, Buskens V, van der Heijden P, van Steenbergen J, Wong A, Bootsma M PLoS One. 2018; 13(11):e0207507.

PMID: 30440047 PMC: 6237413. DOI: 10.1371/journal.pone.0207507.

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