Modelling the impact of the tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns

BMJ Open. 2021 Apr 22;11(4):e050346. doi: 10.1136/bmjopen-2021-050346.

Abstract

Objective: To measure the effects of the tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.

Design: This is a modelling study combining estimates of real-time reproduction number Rt (derived from UK case, death and serological survey data) with publicly available data on regional non-pharmaceutical interventions. We fit a Bayesian hierarchical model with latent factors using these quantities to account for broader national trends in addition to subnational effects from tiers.

Setting: The UK at lower tier local authority (LTLA) level. 310 LTLAs were included in the analysis.

Primary and secondary outcome measures: Reduction in real-time reproduction number Rt .

Results: Nationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system, Rt averaged 1.3 (0.9-1.6) across LTLAs, but declined to an average of 1.1 (0.86-1.42) 2 weeks later. Decline in transmission was not solely attributable to tiers. Tier 1 had negligible effects. Tiers 2 and 3, respectively, reduced transmission by 6% (5%-7%) and 23% (21%-25%). 288 LTLAs (93%) would have begun to suppress their epidemics if every LTLA had gone into tier 3 by the second national lockdown, whereas only 90 (29%) did so in reality.

Conclusions: The relatively small effect sizes found in this analysis demonstrate that interventions at least as stringent as tier 3 are required to suppress transmission, especially considering more transmissible variants, at least until effective vaccination is widespread or much greater population immunity has amassed.

Keywords: COVID-19; epidemiology; infectious diseases.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • COVID-19*
  • Communicable Disease Control
  • Humans
  • Pandemics
  • SARS-CoV-2*
  • United Kingdom / epidemiology