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Faculty of Economics

A University of Cambridge academic at the Faculty of Economics has developed a new class of time series models that reflect epidemic trajectories and are able to produce good forecasts before new cases or deaths reach their peak.

 

Professor Andrew Harvey

A new study co-authored by Andrew Harvey, Emeritus Professor of Econometrics at the Faculty of Economics, and published in the National Institute Economic Review, focuses on the growth rate of the daily number of cases, and the new mutant variants of COVID.

“Our new time series models are able to track the progress of the COVID-19 epidemic in the UK in early 2021. The models are not only simple and transparent, but are able to adapt quickly to changes in key series,” says Professor Harvey. “This ability to respond in a timely fashion is illustrated by the comparison of our estimates of the current R number with those produced by SAGE.”

The study’s new class of time series models therefore provides a “simple and transparent” route to predict an epidemic’s trajectory – and can be adapted to include additional factors including seasonal or day-of-the-week effects. The approach derives from econometric techniques for handling different vintages, but there are some novel technical features. The methods are new to epidemiology.

The UK recorded 29,000 new cases last week, and the R number appears to be rising, according to NIESR, who use a class of time series models developed by Prof Harvey. However, with this wave, the number of cases were always going to increase as the UK moved out of a strict four-month lockdown, and fatalities are much rarer, with responses much quicker.

Forecasting Covid in the UK image

“This ability to respond in a timely fashion is illustrated by the comparison of our estimates of the current R number with those produced by SAGE,” says Professor Harvey. “The complexity of the behavioural response to lockdown and the roll out of the vaccine adds yet more complexity. However, our models track these changes and project forward to make short term forecasts of the situation over the next few weeks.”

The paper – entitled “Time series models based on growth curves with applications to forecasting coronavirus” – is co-authored by Andrew Harvey, Emeritus Professor of Econometrics at the Faculty of Economics of the University of Cambridge, Craig Thamotheram from NIESR, and by Dr Paul Kattuman, Reader in Economics at Cambridge Judge Business School.

Further details: https://www.cambridge.org/core/journals/national-institute-economic-review/article/abs/tracking-the-mutant-forecasting-and-nowcasting-covid19-in-the-uk-in-2021/61A3E91B103E38D6ADA4BF5CC1E9CFC9

NIESR R number tracker: https://www.niesr.ac.uk/latest-covid-19-tracker-0

 

Tags:

COVID-19

Forecasting

Time Series

Models

UK

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