Participatory Disease Surveillance Systems: Ethical Framework.

Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants' physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants' privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance.

Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptoms.

Seasonal influenza surveillance is usually carried out by sentinel general practitioners (GPs) who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This traditional practice for surveillance generally presents several issues, such as a delay of one week or more in releasing reports, population biases in the health-seeking behaviour, and the lack of a common definition of ILI case. On the other hand, the availability of novel data streams has recently led to the emergence of non-traditional approaches for disease surveillance that can alleviate these issues. In Europe, a participatory web-based surveillance system called Influenzanet represents a powerful tool for monitoring seasonal influenza epidemics thanks to aid of self-selected volunteers from the general population who monitor and report their health status through Internet-based surveys, thus allowing a real-time estimate of the level of influenza circulating in the population. In this work, we propose an unsupervised probabilistic framework that combines time series analysis of self-reported symptoms collected by the Influenzanet platforms and performs an algorithmic detection of groups of symptoms, called syndromes. The aim of this study is to show that participatory web-based surveillance systems are capable of detecting the temporal trends of influenza-like illness even without relying on a specific case definition. The methodology was applied to data collected by Influenzanet platforms over the course of six influenza seasons, from 2011-2012 to 2016-2017, with an average of 34,000 participants per season. Results show that our framework is capable of selecting temporal trends of syndromes that closely follow the ILI incidence rates reported by the traditional surveillance systems in the various countries (Pearson correlations ranging from 0.69 for Italy to 0.88 for the Netherlands, with the sole exception of Ireland with a correlation of 0.38). The proposed framework was able to forecast quite accurately the ILI trend of the forthcoming influenza season (2016-2017) based only on the available information of the previous years (2011-2016). Furthermore, to broaden the scope of our approach, we applied it both in a forecasting fashion to predict the ILI trend of the 2016-2017 influenza season (Pearson correlations ranging from 0.60 for Ireland and UK, and 0.85 for the Netherlands) and also to detect gastrointestinal syndrome in France (Pearson correlation of 0.66). The final result is a near-real-time flexible surveillance framework not constrained by any specific case definition and capable of capturing the heterogeneity in symptoms circulation during influenza epidemics in the various European countries.

Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe.

BACKGROUND: The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries. OBJECTIVE: In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system. METHODS: Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone. RESULTS: In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time. CONCLUSIONS: Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases.

Comparison of different collection methods for reported adverse events following pandemic and seasonal influenza vaccination.

BACKGROUND: During the 2009/2010 season, information on adverse events after administration of seasonal and pandemic influenza vaccines was collected by different active surveys in the Netherlands. In the present paper, we compared data from a paper-based questionnaire with data from a web-based questionnaire with respect to outcomes and target population, in order to guide future influenza vaccine safety monitoring. METHODS: The paper-based survey collected data from patients who attended primary care practices in the province of Utrecht for influenza vaccination. The web-based survey recruited participants from the general population all provinces of the Netherlands. To analyze the association between study approach and the reported local and systemic adverse events, a generalized estimation equation model was applied. We adjusted for age, gender, comorbidity, previous vaccination and socio-economic status score. RESULTS: No significant differences were found between the two studies approaches in reporting local reactions (OR: 0.98, 95% CI 0.88-1.10) and systemic AEs (OR: 1.12, 95% CI 0.99-1.27). There were important differences in the age groups that responded. The elderly were more represented in the paper-based survey where participants were recruited via GPs (79%⩾60years) compared to 37% in the web-based survey where participants were recruited via internet. CONCLUSION: The paper-based survey with recruitment of participants through GPs is more representative for the target group of influenza vaccination compared to the web-based survey with recruitment of participants via internet. A web-based approach with recruitment of participants via internet seems more suitable for situations where information about adverse events on a national level is desirable. We recommend to recruit participants for a web-based survey during mass vaccinations sessions by GPs to comply with the recommendations of the European Centre for Disease Prevention Control.

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.

Ten-year performance of Influenzanet: ILI time series, risks, vaccine effects, and care-seeking behaviour.

Recent public health threats have propelled major innovations on infectious disease monitoring, culminating in the development of innovative syndromic surveillance methods. Influenzanet is an internet-based system that monitors influenza-like illness (ILI) in cohorts of self-reporting volunteers in European countries since 2003. We investigate and confirm coherence through the first ten years in comparison with ILI data from the European Influenza Surveillance Network and demonstrate country-specific behaviour of participants with ILI regarding medical care seeking. Using regression analysis, we determine that chronic diseases, being a child, living with children, being female, smoking and pets at home, are all independent predictors of ILI risk, whereas practicing sports and walking or bicycling for locomotion are associated with a small risk reduction. No effect for using public transportation or living alone was found. Furthermore, we determine the vaccine effectiveness for ILI for each season.

Tracking social contact networks with online respondent-driven detection: who recruits whom?

BACKGROUND: Transmission 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. METHODS: In 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. RESULTS: In 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. CONCLUSIONS: Although 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.

Enhancing Syndromic Surveillance With Online 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.

Association between recruitment methods and attrition in Internet-based studies.

Internet-based systems for epidemiological studies have advantages over traditional approaches as they can potentially recruit and monitor a wider range of individuals in a relatively inexpensive fashion. We studied the association between communication strategies used for recruitment (offline, online, face-to-face) and follow-up participation in nine Internet-based cohorts: the Influenzanet network of platforms for influenza surveillance which includes seven cohorts in seven different European countries, the Italian birth cohort Ninfea and the New Zealand birth cohort ELF. Follow-up participation varied from 43% to 89% depending on the cohort. Although there were heterogeneities among studies, participants who became aware of the study through an online communication campaign compared with those through traditional offline media seemed to have a lower follow-up participation in 8 out of 9 cohorts. There were no clear differences in participation between participants enrolled face-to-face and those enrolled through other offline strategies. An Internet-based campaign for Internet-based epidemiological studies seems to be less effective than an offline one in enrolling volunteers who keep participating in follow-up questionnaires. This suggests that even for Internet-based epidemiological studies an offline enrollment campaign would be helpful in order to achieve a higher participation proportion and limit the cohort attrition.

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.

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.

Comparison of five influenza surveillance systems during the 2009 pandemic and their association with media attention.

BACKGROUND: During the 2009 influenza pandemic period, routine surveillance of influenza-like-illness (ILI) was conducted in The Netherlands by a network of sentinel general practitioners (GPs). In addition during the pandemic period, four other ILI/influenza surveillance systems existed. For pandemic preparedness, we evaluated the performance of the sentinel system and the others to assess which of the four could be useful additions in the future. We also assessed whether performance of the five systems was influenced by media reports during the pandemic period. METHODS: The trends in ILI consultation rates reported by sentinel GPs from 20 April 2009 through 3 January 2010 were compared with trends in data from the other systems: ILI cases self-reported through the web-based Great Influenza Survey (GIS); influenza-related web searches through Google Flu Trends (GFT); patients admitted to hospital with laboratory-confirmed pandemic influenza, and detections of influenza virus by laboratories. In addition, correlations were determined between ILI consultation rates of the sentinel GPs and data from the four other systems. We also compared the trends of the five surveillance systems with trends in pandemic-related newspaper and television coverage and determined correlation coefficients with and without time lags. RESULTS: The four other systems showed similar trends and had strong correlations with the ILI consultation rates reported by sentinel GPs. The number of influenza virus detections was the only system to register a summer peak. Increases in the number of newspaper articles and television broadcasts did not precede increases in activity among the five surveillance systems. CONCLUSIONS: The sentinel general practice network should remain the basis of influenza surveillance, as it integrates epidemiological and virological information and was able to maintain stability and continuity under pandemic pressure. Hospital and virological data are important during a pandemic, tracking the severity, molecular and phenotypic characterization of the viruses and confirming whether ILI incidence is truly related to influenza virus infections. GIS showed that web-based, self-reported ILI can be a useful addition, especially if virological self-sampling is added and an epidemic threshold could be determined. GFT showed negligible added value.

Internet-based monitoring of influenza-like illness (ILI) in the general population of the Netherlands during the 2003-2004 influenza season.

BACKGROUND: An internet-based survey of influenza-like illness (ILI)--the Great Influenza Survey or GIS--was launched in the Netherlands in the 2003-2004 influenza season. The aim of the present study was to validate the representativeness of the GIS population and to compare the GIS data with the official ILI data obtained by Dutch GPs participating in the Dutch Sentinel Practice Network. METHOD: Direct mailings to schools and universities, and repeated interviews on television and radio, and in newspapers were used to kindle the enthusiasm of a broad section of the public for GIS. Strict symptomatic criteria for ILI were formulated with the assistance of expert institutes and only participants who responded at least five times to weekly e-mails asking them about possible ILI symptoms were included in the survey. Validation of GIS was done at different levels: 1) some key demographic (age distribution) and public health statistics (prevalence of asthma and diabetes, and influenza vaccination rates) for the Dutch population were compared with corresponding figures calculated from GIS; 2) the ILI rates in GIS were compared with the ILI consultation rates reported by GPs participating in the Dutch Sentinel Practice Network. RESULTS: 13,300 persons (53% of total responders), replied at least five times to weekly e-mails and were included in the survey. As expected, there was a marked under-representation of the age groups 0-10 years and 81->90 years in the GIS population, although the similarities were remarkable for most other age groups, albeit that the age groups between 21 and 70 years were slightly overrepresented. There were striking similarities between GIS and the Dutch population with regard to the prevalence of asthma (6.4% vs. 6.9%) and the influenza vaccination rates, and to a lesser degree for diabetes (2.4% vs. 3.5%). The vaccination rates in patients with asthma or diabetes, and persons older than 65 years were 68%, 85%, and 85% respectively in GIS, while the corresponding percentages in the Dutch population were 73%, 85% and 87%. There was also a marked similarity between the seasonal course of ILI measured by GIS and the GPs. Although the ILI rate in GIS was about 10 times higher, the curves followed an almost similar pattern, with peak incidences occurring in the same week. CONCLUSION: The current study demonstrates that recruitment of a high number of persons willing to participate in on-line health surveillance is feasible. The information gathered proved to be reliable, as it paralleled the information obtained via an undisputed route. We believe that the interactive nature of GIS and the appealing subject were keys to its success.