ArticleBMC infectious diseases2015
Tracking social contact networks with online respondent-driven detection: who recruits whom?
Article in BMC infectious diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.Epidemiology (Cambridge, Mass.) · 2019Pooled it
- Social contact patterns in South Korea: an analysis of a survey conducted in 2023-2024.BMC infectious diseases · 2025Article
- Social contacts and mixing patterns in rural Gambia.BMC infectious diseases · 2025Article
- Article
- The effectiveness of visual triaging and testing of suspected COVID-19 cases in primary care setting in Saudi Arabia.Journal of family medicine and primary care · 2021Article
- Online respondent-driven detection for enhanced contact tracing of close-contact infectious diseases: benefits and barriers for public health practice.BMC infectious diseases · 2021Article
- Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011.BMC infectious diseases · 2021Article
- Analysis of SARS-CoV-2 Transmission in Different Settings, Brunei.Emerging infectious diseases · 2020Article
- Quantifying heterogeneous contact patterns in Japan: a social contact survey.Theoretical biology & medical modelling · 2019Article
- Article
- Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe.JMIR public health and surveillance · 2017Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTransmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven detection can provide relevant epidemiological data on numbers of contact persons and dynamics of contacts between pairs of individuals. We aimed to analyse contact networks with respect to sociodemographic and geographical characteristics, vaccine-induced immunity and self-reported symptoms.
methodsIn 2014, volunteers from two large participatory surveillance panels in the Netherlands and Belgium were invited for a survey. Participants were asked to record numbers of contacts at different locations and self-reported influenza-like-illness symptoms, and to invite 4 individuals they had met face to face in the preceding 2 weeks. We calculated correlations between linked individuals to investigate mixing patterns.
resultsIn total 1560 individuals completed the survey who reported in total 30591 contact persons; 488 recruiter-recruit pairs were analysed. Recruitment was assortative by age, education, household size, influenza vaccination status and sentiments, indicating that participants tended to recruit contact persons similar to themselves. We also found assortative recruitment by symptoms, reaffirming our objective of sampling contact persons whom a participant may infect or by whom a participant may get infected in case of an outbreak. Recruitment was random by sex and numbers of contact persons. Relationships between pairs were influenced by the spatial distribution of peer recruitment.
conclusionsAlthough complex mechanisms influence online peer recruitment, the observed statistical relationships reflected the observed contact network patterns in the general population relevant for the transmission of respiratory pathogens. This provides useful and innovative input for predictive epidemic models relying on network information.
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