Determinants of follow-up participation in the Internet-based European influenza surveillance platform Influenzanet.

BACKGROUND: "Influenzanet" is a network of Internet-based platforms aimed at collecting real-time data for influenza surveillance in several European countries. More than 30,000 European volunteers participate every year in the study, representing one of the largest existing Internet-based multicenter cohorts. Each week during the influenza season, participants are asked to report their symptoms (if any) along with a set of additional questions. OBJECTIVE: Focusing on the first influenza season of 2011-12, when the Influenzanet system was completely harmonized within a common framework in Sweden, the United Kingdom, the Netherlands, Belgium, France, Italy, and Portugal, we investigated the propensity of users to regularly come back to the platform to provide information about their health status. Our purpose was to investigate demographic and behavioral factors associated with participation in follow-up. METHODS: By means of a multilevel analysis, we evaluated the association between regular participation during the season and sociodemographic and behavioral characteristics as measured by a background questionnaire completed by participants on registration. RESULTS: We found that lower participation in follow-up was associated with lower educational status (odds ratio [OR] 0.80, 95% CI 0.75-0.85), smoking (OR 0.64, 95% CI 0.59-0.70), younger age (OR ranging from 0.30, 95% CI 0.26-0.33 to 0.70, 95% CI 0.64-0.77), not being vaccinated against seasonal influenza (OR 0.77, 95% CI 0.72-0.84), and living in a household with children (OR 0.69, 95% CI 0.65-0.74). Most of these results hold when single countries are analyzed separately. CONCLUSIONS: Given the opportunistic enrollment of self-selected volunteers in the Influenzanet study, we have investigated how sociodemographic and behavioral characteristics may be associated with follow-up participation in the Influenzanet cohort. The study described in this paper shows that, overall, the most important determinants of participation are related to education and lifestyle: smoking, lower education level, younger age, people living with children, and people who have not been vaccinated against seasonal influenza tend to have a lower participation in follow-up. Despite the cross-country variation, the main findings are similar in the different national cohorts, and indeed the results are found to be valid also when performing a single-country analysis. Differences between countries do not seem to play a crucial role in determining the factors associated with participation in follow-up

The representativeness of a European multi-center network for influenza-like-illness participatory surveillance.

BACKGROUND: The 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. METHODS: In 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. RESULTS: More 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. CONCLUSIONS: Existing 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

Participatory Syndromic Surveillance of Influenza in Europe

The growth of digital communication technologies for public health is offering an unconventional means to engage the general public in monitoring community health. Here we present Influenzanet, a participatory system for the syndromic surveillance of influenza-like illness (ILI) in Europe. Through standardized online surveys, the system collects detailed profile information and self-reported symptoms volunteered by participants resident in the Influenzanet countries. Established in 2009, it now includes 10 countries representing more than half of the 28 member states of the European Union population. The experience of 7 influenza seasons illustrates how Influenzanet has become an adjunct to existing ILI surveillance networks, offering coherence across countries, inclusion of nonmedically attended ILI, flexibility in case definition, and facilitating individual-level epidemiological analyses generally not possible in standard systems. Having the sensitivity to timely detect substantial changes in population health, Influenzanet has the potential to become a viable instrument for a wide variety of applications in public health preparedness and control.info:eu-repo/semantics/publishedVersio

Summary of the results reported in <b>Table 2</b>.

<p>The effect of face-to-face recruitment on follow-up participation compared to offline recruitment is shown. Given that the studies are highly heterogeneous by design and target different populations, the pooled estimate should be considered as an average of the study-specific effects rather than as a causal estimate.</p

Follow-up participation proportion, unadjusted odds ratios and odds ratios adjusted for the variables detailed in the Methods section and confidence intervals are shown for different recruitment methods of individuals enrolled in the Influenzanet study (stratified by country), Ninfea and ELF.

<p>*OR, odds ratio adjusted for: age, smoking, educational level, presence of chronic disorder/condition for all the three cohorts; plus gender, household composition and vaccination against seasonal influenza for the Influenzanet cohort; plus for trimester of pregnancy for the Ninfea cohort; CI, confidence interval. Bold indicates that 1 lies outside the 95% confidence interval. Sample size refers to participants with complete data.</p><p>Follow-up participation proportion, unadjusted odds ratios and odds ratios adjusted for the variables detailed in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114925#s2" target="_blank">Methods</a> section and confidence intervals are shown for different recruitment methods of individuals enrolled in the Influenzanet study (stratified by country), Ninfea and ELF.</p

Data summary by cohort and country.

<p>*Cohort size = Number of enrolled participants eligible for this study (see text for details regarding the inclusion criteria). Participants at follow up (%) = number of participants at follow-up divided by cohort size (x100).</p>1<p>Data referred to the percentage of Internet users in 2011 and were gathered from the International Telecommunication Union (ITU, <a href="http://www.itu.int" target="_blank">www.itu.int</a>), the United Nations specialized agency for information and communication technologies.</p><p>Data summary by cohort and country.</p