Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures

Abstract

We describe regional variation in the reproduction number of SARS-CoV-2 infections observed using publicly reported data in the UK, with a view to understanding both if there are clear hot spots in viral spread in the country, or other spatial patterns. Based on case data up to the 9th April, we estimate that the viral replication number remains above 1 overall in the UK but that its trend is to decrease. This suggests the peak of the first wave of COVID-19 patients is imminent. We find that there is significant regional variation in the UK and that this is changing over time. Within England currently the reproductive ratio is lowest in the Midlands (1.11 95% CI 1.07; 1.14) , and highest in the North East of England (1.38 95% CI 1.33-1.42) . There are long and variable time delays between infection and detection of cases, and thus it remains unclear whether the reduction in the reproductive number is a result of social distancingmeasures. If we are to prevent further outbreaks, it is critical that we both reduce the time taken for detection and improve our ability to predict the regional spread of outbreaks.

Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework

“…Similar to most other COVID-19 models, we use a variant on a susceptible-exposed-infectious-recovered structure. 8–10 16 26 32 33 We do not spatially structure the population as in other UK modelling, 9 10 but we do include age-specific mixing based on POLYMOD data 22 and the postlockdown CoMix study. 11 We also explicitly measure the total asymptomatic infection, and the total in each of the clinically relevant hospital classes (acute or IC), which is a strength of our approach.…”

“…8 A more recent study factoring spatial distribution of the population indicated the peak to follow in early April due to reducing to below 1 in many settings in weeks following lockdown. 9 Other modelling indicated that deaths in the UK would peak in mid-late April; furthermore, that the UK would not have enough acute and IC beds to meet demand. 35 While modelling from the European Centre for Disease Prevention and Control estimated peak cases to occur in most European countries in mid-April, 20 these estimations were largely at a national level.…”

“…Mathematical modelling has been used to predict the course of the COVID-19 pandemic and to evaluate the effectiveness of proposed and enacted interventions. 6–11 Prem et al 6 showed that the premature lifting of control strategies at the national level (within China) could lead to an earlier secondary peak; Flaxman et al 7 used a semimechanistic model to predict the total COVID-19 infections in 11 countries; Ferguson et al 8 used an individual-based simulation model of COVID-19 transmission to explore the effects of non-pharmaceutical interventions within the USA and Great Britain; Challen et al 9 estimated the R number among regions of the UK; Danon et al 10 used a spatial model to predict the potential course of COVID-19 in England and Wales in the absence of control measures; while Jarvis et al 11 analysed the behavioural monitoring data to quantify the impact of control measures on COVID-19 transmission. These models have been predominantly aimed at the national level and have largely been based on epidemiological and biological data sourced from the initial epidemic in Wuhan, China, 12 and the first large outbreak in Lombardy, Italy.…”

“… 9 South West England (SW) is the region with the lowest number of total cases in England (as of 11 May 2020), lagging behind the national data driven by the earlier epidemic in London. 9 14 …”

“…5 Mathematical modelling has been used to predict the course of the COVID-19 pandemic and to evaluate the effectiveness of proposed and enacted interventions. [6][7][8][9][10][11] Prem et al 6 showed that the premature lifting of control strategies at the national level (within China) could lead to an earlier secondary peak;…”