Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study

• Main Authors: Paul J. Birrell (Author), Xu-Sheng Zhang (Author), Alice Corbella (Author), Edwin van Leeuwen (Author), Nikolaos Panagiotopoulos (Author), Katja Hoschler (Author), Alex J. Elliot (Author), Maryia McGee (Author), Simon de Lusignan (Author), Anne M. Presanis (Author), Marc Baguelin (Author), Maria Zambon (Author), André Charlett (Author), Richard G. Pebody (Author), Daniela De Angelis (Author)
• Format: Book
• Published: BMC, 2020-04-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Background Since the 2009 A/H1N1 pandemic, Public Health England have developed a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare...