Early and Real-Time Detection of Seasonal Influenza Onset

Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.Author Summary: Influenza, generally referred to as the flu, is a common infectious disease that affects millions of people. Every year, we expect this seasonal disease to occur during the Winter, but exactly when it will start and how severe it will be is not known. This places a strong burden on health services, as often the spread can be felt as very fast and emergency rooms become flooded with patients. With this work, we propose a new method that identifies the beginning of the yearly flu season. This is done by using several different data sources, including searches for flu-related symptoms on Google and phone call logs to a specialized medical phone service. These data sources, together with our method, can provide a daily or weekly report, making it much faster than current methods, which require lab testing or centralized medical reports. Our method was applied to different European countries and can anticipate current official alerts by several weeks.