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

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

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...

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Bibliographic Details
Main Authors: Paul J. Birrell, Xu-Sheng Zhang, Alice Corbella, Edwin van Leeuwen, Nikolaos Panagiotopoulos, Katja Hoschler, Alex J. Elliot, Maryia McGee, Simon de Lusignan, Anne M. Presanis, Marc Baguelin, Maria Zambon, André Charlett, Richard G. Pebody, Daniela De Angelis
Format: Article
Language:English
Published: BMC 2020-04-01
Series:BMC Public Health
Subjects:
Transmission models
Seasonal influenza
Intensive care admissions
GP consultations
Nowcasting
Forecasting
Online Access:http://link.springer.com/article/10.1186/s12889-020-8455-9

Internet

http://link.springer.com/article/10.1186/s12889-020-8455-9

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