In recent years the availability of novel data streams has given rise to a variety of non-traditional approaches for monitoring seasonal influenza epidemics. Such new digital data sources can be exploited to capture additional surveillance signals that can be used to complement GPs surveillance data. In this context, some so-called participatory surveillance systems have emerged in several countries around the world with the aim of monitoring influenza circulation through Internet reporting of self-selected participant. One of these systems, the Influenzanet project, has been established in Europe since 2011 and it is now present in nine European countries.
The system relies on the voluntary participation of the general population through a dedicated national website in each country involved in the project. Data are obtained on a weekly basis through an online survey where participants are invited to report whether they experienced or not any of the following symptoms since their last survey. Even though participatory systems generally suffer from self-selection bias, causing the sample to be non-representative of the general population, previous works have shown that Web-based surveillance data can provide relevant information to estimate age-specific influenza attack rates, influenza vaccine effectiveness, risk factors for ILI, and to assess health care seeking behavior.
Moreover, it has been largely demonstrated that weekly ILI incidence rates that can be extracted from Web-based surveillance data correlate well with ILI incidence as reported by GPs surveillance.
This session is meant to showcase the highlights of the scientific activity carried out by the Influenza consortium of research teams during the past decade, from the beginning of the activity to the most recent developments.
|Paolotti Daniela||Chairman||ISI Foundation||Italy|
|Mexia||Instituto Nacional de Saúde Dr. Ricardo Jorge - INSA||Portugal|
|Hirsch Marco||German Center for Artificial Intelligence||Germany|