To ask the Secretary of State for Health and Social Care, pursuant to the Answer of 10 September 2020 to Question 84231 on Coronavirus: Disease control, whether (a) the published R is an estimate and (b) his Department has taken steps to verify the value of R (i) published at a given date in the past and (ii) in the light of further evidence of transmission which becomes accessible over time.
This answer is the replacement for a previous holding answer.
12 October 2020
The reproduction number (R) is the average number of secondary infections produced by a single infected person. The Government Office for Science currently publishes the latest estimate of R for the United Kingdom and NHS England regions on a weekly basis.
R is an average value that can vary in different parts of the country, communities, and subsections of the population. It cannot be measured directly, and is an estimate based on data such as numbers of cases, hospitalisations and deaths. There is always uncertainty around its exact value.
R is estimated by a number of independent modelling groups based in universities and Public Health England. The modelling groups discuss their individual estimates at the Science Pandemic Influenza Modelling group (SPI-M) – a subgroup of the Scientific Advisory Group for Emergencies (SAGE). Attendees compare the different estimates and SPI-M collectively agrees a range which R is very likely to be within, which is then reviewed and endorsed by SAGE.
As part of this weekly review by SPI-M and SAGE, estimates of R are considered alongside other metrics, such as estimates of prevalence and incidence from the Office for National Statistics COVID-19 Infection Survey, or trends from Pillar 2 testing. These additional metrics, together with supplementary sources of information such as social contact surveys (which assess changes in contact patterns and behaviour) and mobility data, offer assurance of the R estimates.
As our understanding of the epidemic improves and new evidence emerges, SPI-M and SAGE updates its advice accordingly. For instance, individual modelling groups may adjust their models to incorporate new data streams or to reflect updated evidence on transmission dynamics; whilst relevant new studies are considered as part of the wider discussion and assurance process.