Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave

Abstract

England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lockdown' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management throughout the first wave. Estimates on the 10 May showed lockdown had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally varying impact was largest in London with a reduction of 81% (95% credible interval: 77-84%). Reproduction numbers have since then slowly increased, and on 19 June the probability of the epidemic growing was greater than 5% in two regions, South West and London. By this date, an estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9-1.4%) overall but 17% (14-22%) among the over-75s. This ongoing work continues to be key to quantifying any widespread resurgence, should accrued immunity and effective contact tracing be insufficient to preclude a second wave. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Keywords: Bayesian; COVID-19; dynamics; forecasting; nowcasting; real-time.

Figure 1.

(a) Data on deaths by region, and (b) age; and (c) serological positivity by region and sampling date.

Figure 2.

Estimated and projected COVID-19 infections and deaths by efficacy of social restriction measures.

Figure 3.

(a) Sequentially obtained estimates infection trajectories; R_t; and three-week forecast of the number of deaths by date of analysis (rows). (b) Probability that R_t exceeds 1 as of 3 June, by region. See the electronic supplementary material, figure S3 for 10 May and 19 June. In both plots, vertical blue lines indicate the timings of significant policy changes, vertical red lines indicate the time of analysis.