The reproduction number R for COVID-19 in England: Why hasn’t “lockdown” been more effective?

  1. Alastair Grant

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The reproduction number R, the average number of people that a single individual with a contagious disease infects, is central to understanding the dynamics of the COVID-19 epidemic. Values greater than one correspond to increasing rates of infection, and values less than one indicate that control measures are being effective. Here, we summarise how changes in the behaviour of individuals alter the value of R. We also use matrix models that correctly recreate distributions of times that individuals spend incubating the disease and being infective to demonstrate the accuracy of a simple approximation to estimate R directly from time series of case numbers, hospital admissions or deaths. The largest uncertainty is that the generation time of the infection is not precisely known, but this challenge also affects most of the more complex methods of calculating R. We use this approximation to examine changes in R in response to the introduction of “lockdown” restrictions in England. This suggests that there was a substantial reduction in R before large scale compulsory restrictions on economic and social activity were imposed on 23 rd March 2020. From mid-April to mid-June decline of the epidemic at national and regional level has been relatively slow, despite these restrictions (R values clustered around 0.81). However, these estimates of R are consistent with the relatively high average numbers of close contacts reported by confirmed cases combined with directly measured attack rates via close interactions. This implies that a significant portion of transmission is occurring in workplaces; overcrowded housing or through close contacts that are not currently lawful, routes on which nationwide lockdown will have limited impact.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.07.02.20144840: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    It is possible that these initial values represent an over-estimate, as there may have been lower identification rates of symptomatic COVID cases in the early period of the epidemic, and limitations on testing capacity may have reduced the proportion of infected individuals being tested. So some of this initial high rate of increase may reflect an increase in diagnosis rates over time rather than an increase in disease prevalence. In all cases the rates of increase reduce below 1.0 around week ending 17th April 2020. At a national level all show geometric mean weekly rates of change close to 0.75 over this period (equivalent to R = 0.81 for a serial interval of 5 days), although there is some spatial and temporal variability in rates of decline. Is the pattern of these changes consistent with the expected consequences for R of policy interventions? On 16th March 2020, the English government introduced recommendations on “social distancing” and voluntary self-isolation of those with pre-exiting health conditions that made them more vulnerable to COVID-19 (Public Health England, 2020b). Advice on personal hygiene and maintaining vigilance for COVID symptoms was in place before this and there is evidence that travel, and particularly use of public transport, began to decrease around 9th March 2020 (Rieger, 2020). This was followed on 23rd of March 2020 by mandatory restrictions on movement, meetings between more than two people, and non-essential economic activity, usually abbre...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.07.02.20144840v1 on medRxiv