Enhancing syndromic surveillance with on-line respondent driven detection
Enhancing syndromic surveillance with on-line respondent driven detection
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.
e90-e97
Stein, M.L.
a23978d3-62d7-4876-a64a-683c7229823e
van Steenbergen, J.E.
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Buskens, V.
e1c1e174-aa90-4113-b9bc-ad4f600493ba
van der Heijden, P.
85157917-3b33-4683-81be-713f987fd612
Koppeschaar, C.E.
c7306f4c-0135-4dcf-90b8-6c6cf8ca9ae6
Bengtsson, L.
ddd51250-2064-4a6d-9672-392bfae5bd83
Thorson, A.E.
c96eec7c-88fa-430c-950e-2068704dfe10
Kretzschmar, M.E.E.
510a3574-ad89-4dfb-af62-cb5bc5df6151
August 2015
Stein, M.L.
a23978d3-62d7-4876-a64a-683c7229823e
van Steenbergen, J.E.
d92bc809-d87c-4eb6-adb0-0f81ef4013ea
Buskens, V.
e1c1e174-aa90-4113-b9bc-ad4f600493ba
van der Heijden, P.
85157917-3b33-4683-81be-713f987fd612
Koppeschaar, C.E.
c7306f4c-0135-4dcf-90b8-6c6cf8ca9ae6
Bengtsson, L.
ddd51250-2064-4a6d-9672-392bfae5bd83
Thorson, A.E.
c96eec7c-88fa-430c-950e-2068704dfe10
Kretzschmar, M.E.E.
510a3574-ad89-4dfb-af62-cb5bc5df6151
Stein, M.L., van Steenbergen, J.E., Buskens, V., van der Heijden, P., Koppeschaar, C.E., Bengtsson, L., Thorson, A.E. and Kretzschmar, M.E.E.
(2015)
Enhancing syndromic surveillance with on-line respondent driven detection.
American Journal of Public Health, 105 (8), .
(doi:10.2105/AJPH.2015.302717).
(PMID:26066940)
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.
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Published date: August 2015
Organisations:
Social Statistics & Demography
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Local EPrints ID: 381213
URI: http://eprints.soton.ac.uk/id/eprint/381213
PURE UUID: bbc6124f-6824-49e3-9763-214d0a4b678a
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Date deposited: 25 Sep 2015 13:29
Last modified: 15 Mar 2024 03:46
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Contributors
Author:
M.L. Stein
Author:
J.E. van Steenbergen
Author:
V. Buskens
Author:
C.E. Koppeschaar
Author:
L. Bengtsson
Author:
A.E. Thorson
Author:
M.E.E. Kretzschmar
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