Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection. – MIDAS

Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection.

Abstract

. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

MIDAS Network Members

John Edmunds

Professor of Infectious Disease Modelling
London School of Hygiene & Tropical Medicine

Mark Jit

Professor of Vaccine Epidemiology
London School of Hygiene & Tropical Medicine

Quentin Leclerc

PhD Student
London School of Hygiene & Tropical Medicine

Citation:

Jombart T, Ghozzi S, Schumacher D, Taylor TJ, Leclerc QJ, Jit M, Flasche S, Greaves F, Ward T, Eggo RM, Nightingale E, Meakin S, Brady OJ, , Medley GF, Höhle M, Edmunds WJ. (2021). Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 376(1829)