The incidence of symptomatic infection with influenza virus in the Netherlands 2011/2012 through 2016/2017, estimated using Bayesian evidence synthesis.

Due to differences in the circulation of influenza viruses, distribution and antigenic drift of A subtypes and B lineages, and susceptibility to infection in the population, the incidence of symptomatic influenza infection can vary widely between seasons and age-groups. Our goal was to estimate the symptomatic infection incidence in the Netherlands for the six seasons 2011/2012 through 2016/2017, using Bayesian evidence synthesis methodology to combine season-specific sentinel surveillance data on influenza-like illness (ILI), virus detections in sampled ILI cases and data on healthcare-seeking behaviour. Estimated age-aggregated incidence was 6.5 per 1000 persons (95% uncertainty interval (UI): 4.7-9.0) for season 2011/2012, 36.7 (95% UI: 31.2-42.8) for 2012/2013, 9.1 (95% UI: 6.3-12.9) for 2013/2014, 41.1 (95% UI: 35.0-47.7) for 2014/2015, 39.4 (95% UI: 33.4-46.1) for 2015/2016 and 27.8 (95% UI: 22.7-33.7) for season 2016/2017. Incidence varied substantially between age-groups (highest for the age-group <5 years: 23 to 47/1000, but relatively low for 65+ years: 2 to 34/1000 over the six seasons). Integration of all relevant data sources within an evidence synthesis framework has allowed the estimation - with appropriately quantified uncertainty - of the incidence of symptomatic influenza virus infection. These estimates provide valuable insight into the variation in influenza epidemics across seasons, by virus subtype and lineage, and between age-groups.

Gripenet: an internet-based system to monitor influenza-like illness uniformly across Europe.

Gripenet has been monitoring the activity of influenza-like-illness (ILI) with the aid of volunteers via the internet in the Netherlands and Belgium since 2003 and in Portugal since 2005. In contrast with the traditional system of sentinel networks of mainly primary care physicians coordinated by the European Influenza Surveillance Scheme (EISS), Gripenet obtains its data directly from the population. Any resident of the three countries can participate in Gripenet by completing an application form on the appropriate websites (http://www.griepmeting.nl for the Netherlands and Belgium, http://www.gripenet.pt for Portugal), which contains various medical, geographic and behavioural questions. Participants report weekly on the website any symptoms they have experienced since their last visit. ILI incidence is determined on the basis of a uniform case definition. In the 2006/2007 season, 19,623 persons participated in Gripenet in the Netherlands, 7,025 in Belgium and 3,118 in Portugal. The rise, peak and decline of ILI activity occurred at similar times according to Gripenet and EISS. However, ILI attack rates in the Netherlands (6.6%), Belgium (6.1%) and Portugal (5.6%) were remarkably more similar in Gripenet than in EISS (0.8%, 3.9%, and 0.6% respectively). Monitoring ILI activity with the direct participation of volunteers provides similar incidence curves compared to the traditional system coordinated by EISS. Whereas EISS provides an established system whose data is validated by virology tests, Gripenet is a fast and flexible monitoring system whose uniformity allows for direct comparison of ILI rates between countries. A current objective of Gripenet is to engage more European countries.

Web-based participatory surveillance of infectious diseases: the Influenzanet participatory surveillance experience.

To overcome the limitations of the state-of-the-art influenza surveillance systems in Europe, we established in 2008 a European-wide consortium aimed at introducing an innovative information and communication technology approach for a web-based surveillance system across different European countries, called Influenzanet. The system, based on earlier efforts in The Netherlands and Portugal, works with the participation of the population in each country to collect real-time information on the distribution of influenza-like illness cases through web surveys administered to volunteers reporting their symptoms (or lack of symptoms) every week during the influenza season. Such a large European-wide web-based monitoring infrastructure is intended to rapidly identify public health emergencies, contribute to understanding global trends, inform data-driven forecast models to assess the impact on the population, optimize the allocation of resources, and help in devising mitigation and containment measures. In this article, we describe the scientific and technological issues faced during the development and deployment of a flexible and readily deployable web tool capable of coping with the requirements of different countries for data collection, during either a public health emergency or an ordinary influenza season. Even though the system is based on previous successful experience, the implementation in each new country represented a separate scientific challenge. Only after more than 5 years of development are the existing platforms based on a plug-and-play tool that can be promptly deployed in any country wishing to be part of the Influenzanet network, now composed of The Netherlands, Belgium, Portugal, Italy, the UK, France, Sweden, Spain, Ireland, and Denmark.

Internet-based monitoring of influenza-like illness in the general population: experience of five influenza seasons in The Netherlands.

Like in most other countries, influenza surveillance in The Netherlands is based upon influenza-like illness (ILI) consultations reported by sentinel general practitioners (GP). In addition, an internet-based monitoring of ILI in the general population started in 2003/2004 (Great Influenza Survey (GIS)). We compared GIS results over 5 influenza seasons with results from the GP system. Weekly ILI incidence from GIS correlated well with ILI incidence from the GP system the same week and even better 1 week later. This suggests that GIS is useful for early detection of trends in influenza activity. However, two important vulnerable groups, children and the elderly, are clearly underrepresented in the GIS. Furthermore, virological confirmation is lacking in the GIS. So, GIS can be a useful addition to the GP system, especially when representativeness can be improved and when participation remains at the current high level.