Social media as Twitter are used today by people to disseminate health information but also to share or exchange on their health. Based on this observation, recent studies showed that Twitter data can be used to monitor trends of infectious diseases such as influenza. These studies were mainly carried out in United States where Twitter is very popular1-4. In our knowledge, no research has been implemented in France to know whether Twitter data can be a complementary data source to monitor seasonal influenza epidemic.

Sequence-informed surveillance is now recognized as an important extension to the monitoring of rapidly evolving pathogens [2]. This includes phylogeography, a field that studies the geographical lineages of species including viruses [3] by using sequence data (and relevant metadata such as sampling location). This work relies on bioinformatics knowledge. For example, the user first needs to find a relevant sequence database, navigate through it, and use proper search parameters to obtain the desired data.

Influenza viral infection is contentious, has a short incubation period, yet preventable if multiple barriers are employed. At some extend school holidays and travel restrictions serve as a socially accepted control measure. A study of a spatiotemporal spread of influenza among school-aged children in Belgium illustrated that changes in mixing patterns are responsible for altering disease seasonality3.

Syndromic surveillance achieves timeliness by collecting prediagnostic data, such as emergency department chief complaints, from the start of healthcare interactions. The tradeoff is less precision than from diagnosis data, which takes longer to generate. As the use and sophistication of electronic health information systems increases, additional data that provide an intermediate balance of timeliness and precision are becoming available. Information about the procedures and treatments ordered for a patient can indicate what diagnoses are being considered.