NIESR Weekly Covid-19 Tracker: Reproduction Number (R) and Forecasts of New Cases: An upward revision

Publication date: 25 Feb 2021 | Publication type: NIESR Covid-19 Tracker | NIESR Author(s): Thamotheram, C Issue 2

Reproduction Number (R) and Forecasts of New Cases: An upward revision

Main points

  • The NIESR estimates use a new time series model to project new cases of Covid-19 and produce timely estimates of the R number.  The forecasts reported here were made using publicly available data on 23rd February 2021.
  • Figure 1 shows that the Reproduction number, R, which is the average number of secondary infections currently generated by an infected individual, is starting to move up to 0.9 – 1.0 from a range of 0.8 – 0.9 where it had been since mid-January.
  • Should new cases in the UK continue to fall at the current rate, we can expect them to be around 6,800 on 8th March, when schools reopen; see Figure 2. This figure has been revised upwards from 3,900 last week.
  • Regional differences, shown in Figure 3, are still apparent and are responsible for driving up the overall UK figure.  It is no longer the case that all regional R number estimates are below one as it was last week. Currently, London has the lowest R number while Scotland and Yorkshire and the Humber again have the highest, with both slightly above 1.0.
  • There may be a number of explanations for the rise, one of which may simply be increased testing.  On the other hand, it may reflect a behavioural response to the success of the vaccination roll out and the fall in deaths and hospital admissions.

“According to the latest data on new cases, our work shows an R number for the UK in the range 0.9 – 1.0, taking it above the range of 0.8 – 0.9 that it has been in since mid-January. Strong data relative to that forecast in the previous week has increased our estimates of R number and regional differences remain pronounced with Scotland, Northern Ireland and Yorkshire and the Humber above 1.0.”

Dr Craig Thamotheram
Senior Economist - Macroeconomic Modelling and Forecasting