Releasing the lockdown in the UK Covid-19 epidemic: a stochastic model

Abstract

Background

In a classic epidemic, the infected population has an early exponential phase, before slowing and fading to its peak. Mitigating interventions may change the exponent during the rising phase and a plateau can replace a peak. With interventions comes the risk that relaxation causes a second-wave. In the UK Covid-19 epidemic, infections cannot be counted, but their influence is seen in the curve of the mortality data. This work simulated social distancing and the lockdown in the UK Covid-19 epidemic to explore strategies for relaxation.

Methods

Cumulative mortality data was transposed 20 days earlier to identify three doubling periods separated by the 17 ^th March—social distancing, and 23 ^rd March—lockdown. A set of stochastic processes simulated viral transmission between interacting individuals using Covid-19 incubation and illness durations. Social distancing and restrictions on interactions were imposed and later relaxed.

Principal Findings

Daily mortality data, consistent with that seen in the UK Covid-19 epidemic to 24 ^th April 2020 was simulated. This output predicts that under a lockdown maintained till early July 2020, UK deaths will exceed 31,000, but leave a large susceptible population and a requirement for vaccination or quarantine. An earlier staged relaxation carries a risk of a second-wave. The model allows exploration of strategies for lifting the lockdown.

Interpretation

Social distancing and the lockdown have had an impressive impact on the UK Covid-19 epidemic and saved lives, caution is now needed in planning its relaxation.

Funding

Unfunded research.

Research in context

Evidence before this study

The classical Susceptible, Infected, Recovered, (SIR) epidemiological model with additional compartments and sophistications have been widely used to make forecasts in the Covid-19 pandemic but are not easily accessible.

Added value of this study

This study adds reassurance that the interventions of social distancing introduced on the 17 ^th March and the lockdown of the 23 ^rd March 2020 have reduced mortality. The risks of a second-wave on their relaxation are real and illustrated graphically.

Implications of all the available evidence

Together with other models, credence is given to the risks of a second-wave in the UK Covid-19 epidemic on the relaxation of restrictions.

Article activity feed

SciScore for 10.1101/2020.04.28.20083329: (What is this?)

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

Table 1: Rigor

NIH rigor criteria are not applicable to paper type.

Table 2: Resources

Software and Algorithms
Sentences	Resources
An easily modified stochastic model was written in Microsoft Excel VBA v7·1 operating in Windows 10.	Microsoft Excel suggested: (Microsoft Excel, RRID:SCR_016137)

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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

Results from TrialIdentifier: No clinical trial numbers were referenced.

Results from Barz…