National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically?

Muegge, R. , Dean, N. , Jack, E. and Lee, D. (2023) National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically? Spatial and Spatio-Temporal Epidemiology, 44, 100559. (doi: 10.1016/j.sste.2022.100559) (PMCID:PMC9719849)

Abstract

Quantifying the impact of lockdowns on COVID-19 mortality risks is an important priority in the public health fight against the virus, but almost all of the existing research has only conducted macro country-wide assessments or limited multi-country comparisons. In contrast, the extent of within-country variation in the impacts of a nation-wide lockdown is yet to be thoroughly investigated, which is the gap in the knowledge base that this paper fills. Our study focuses on England, which was subject to 3 national lockdowns between March 2020 and March 2021. We model weekly COVID-19 mortality counts for the 312 Local Authority Districts in mainland England, and our aim is to understand the impact that lockdowns had at both a national and a regional level. Specifically, we aim to quantify how long after the implementation of a lockdown do mortality risks reduce at a national level, the extent to which these impacts vary regionally within a country, and which parts of England exhibit similar impacts. As the spatially aggregated weekly COVID-19 mortality counts are small in size we estimate the spatio-temporal trends in mortality risks with a Poisson log-linear smoothing model that borrows strength in the estimation between neighbouring data points. Inference is based in a Bayesian paradigm, using Markov chain Monte Carlo simulation. Our main findings are that mortality risks typically begin to reduce between 3 and 4 weeks after lockdown, and that there appears to be an urban-rural divide in lockdown impacts.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lee, Professor Duncan and Dean, Dr Nema and Muegge, Mr Robin and Jack, Dr Eilidh
• Authors: Muegge, R., Dean, N., Jack, E., and Lee, D.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Spatial and Spatio-Temporal Epidemiology
• Publisher: Elsevier
• ISSN: 1877-5845
• ISSN (Online): 1877-5853
• Published Online: 05 December 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Spatial and Spatio-Temporal Epidemiology 44: 100559
• Publisher Policy: Reproduced under a Creative Commons licence