ArticleBMC public health2014
The representativeness of a European multi-center network for influenza-like-illness participatory surveillance.
Article in BMC public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed.
- SALGINTR: development and early evaluation of a low-cost cloud-based digital participatory surveillance system for influenza-like Illness among physicians in Türkiye - a proof of concept.BMC infectious diseases · 2026Article
- Assessing dengue knowledge, attitudes and preventive practices in France and Italy: A cross-sectional study using participatory surveillance cohorts.PLOS global public health · 2026Article
- Respiratory viral infections: when and where? A scoping review of spatiotemporal methods.Journal of global health · 2025Article
- Collective Intelligence-Based Participatory COVID-19 Surveillance in Accra, Ghana: Pilot Mixed Methods Study.JMIR infodemiology · 2024Article
- Engaging a national-scale cohort of smart thermometer users in participatory surveillance.NPJ digital medicine · 2023Article
- Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View.JMIR public health and surveillance · 2023Article
- Participatory Surveillance for COVID-19 Trend Detection in Brazil: Cross-sectional Study.JMIR public health and surveillance · 2023Article
- Calculating incidence of Influenza-like and COVID-like symptoms from Flutracking participatory survey data.MethodsX · 2022Article
- Acute respiratory infection symptoms and COVID-19 testing behaviour: results based on South Australian health surveys.BMC public health · 2021Article
- Cross-sectional telephone surveys as a tool to study epidemiological factors and monitor seasonal influenza activity in Malta.BMC public health · 2021Article
- Representativeness of the FluWatchers Participatory Disease Surveillance Program 2015-2016 to 2018-2019: How do participants compare with the Canadian population?Canada communicable disease report = Releve des maladies transmissibles au Canada · 2021Article
- Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response.Public health reports (Washington, D.C. : 1974) · 2021Article
- Article
- Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study.JMIR public health and surveillance · 2020Article
- Differences in Regional Patterns of Influenza Activity Across Surveillance Systems in the United States: Comparative Evaluation.JMIR public health and surveillance · 2019Article
- Factors associated with influenza-like-illness: a crowdsourced cohort study from 2012/13 to 2017/18.BMC public health · 2019Article
- Participatory Disease Surveillance Systems: Ethical Framework.Journal of medical Internet research · 2019Article
- Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptoms.PLoS computational biology · 2019Article
- Research Ethics in the European Influenzanet Consortium: Scoping Review.JMIR public health and surveillance · 2018Article
- Self-Swabbing for Virological Confirmation of Influenza-Like Illness Among an Internet-Based Cohort in the UK During the 2014-2015 Flu Season: Pilot Study.Journal of medical Internet research · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
Abstract
backgroundThe Internet is becoming more commonly used as a tool for disease surveillance. Similarly to other surveillance systems and to studies using online data collection, Internet-based surveillance will have biases in participation, affecting the generalizability of the results. Here we quantify the participation biases of Influenzanet, an ongoing European-wide network of Internet-based participatory surveillance systems for influenza-like-illness.
methodsIn 2011/2012 Influenzanet launched a standardized common framework for data collection applied to seven European countries. Influenzanet participants were compared to the general population of the participating countries to assess the representativeness of the sample in terms of a set of demographic, geographic, socio-economic and health indicators.
resultsMore than 30,000 European residents registered to the system in the 2011/2012 season, and a subset of 25,481 participants were selected for this study. All age classes (10 years brackets) were represented in the cohort, including under 10 and over 70 years old. The Influenzanet population was not representative of the general population in terms of age distribution, underrepresenting the youngest and oldest age classes. The gender imbalance differed between countries. A counterbalance between gender-specific information-seeking behavior (more prominent in women) and Internet usage (with higher rates in male populations) may be at the origin of this difference. Once adjusted by demographic indicators, a similar propensity to commute was observed for each country, and the same top three transportation modes were used for six countries out of seven. Smokers were underrepresented in the majority of countries, as were individuals with diabetes; the representativeness of asthma prevalence and vaccination coverage for 65+ individuals in two successive seasons (2010/2011 and 2011/2012) varied between countries.
conclusionsExisting demographic and national datasets allowed the quantification of the participation biases of a large cohort for influenza-like-illness surveillance in the general population. Significant differences were found between Influenzanet participants and the general population. The quantified biases need to be taken into account in the analysis of Influenzanet epidemiological studies and provide indications on populations groups that should be targeted in recruitment efforts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.