Enhancing Syndromic Surveillance With Online Respondent-Driven Detection

Am J Public Health. 2015 Aug;105(8):e90-7. doi: 10.2105/AJPH.2015.302717. Epub 2015 Jun 11.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Child
  • Child, Preschool
  • Communicable Diseases / epidemiology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Netherlands / epidemiology
  • Online Systems
  • Patient Selection
  • Population Surveillance / methods*
  • Respiratory Tract Infections / epidemiology
  • Self Report*
  • Surveys and Questionnaires
  • Young Adult