A phased approach to unlocking during the COVID-19 pandemic-Lessons from trend analysis

Background The COVID-19 pandemic has led to radical political control of social behaviour. The purpose of this paper is to explore data trends from the pandemic regarding infection rates/policy impact and draw learning points for informing the unlocking process. Methods The daily published cases in England in each of 149 Upper Tier Local Authority (UTLA) areas were converted to Average Daily Infection Rate (ADIR), an R value-the number of further people infected by one infected person during their infectious phase with Rate of Change of Infection Rate (RCIR) also calculated. Stepwise regression was carried out to see what local factors could be linked to differences in local infection rates. Findings By the 19th April 2020 the infection R has fallen from 2.8 on 23rd March before the lockdown and has stabilised at about 0.8 sufficient for suppression. However, there remain significant variations between England regions. Regression analysis across UTLAs found that the only factor relating to reduction in ADIR was the historic number of confirmed number infection/000 population, There is, however, wide variation between Upper Tier Local Authorities (UTLA) areas. Extrapolation of these results showed that unreported community infection may be 150 times higher than reported cases, providing evidence that by the end of the 2nd week in April, 26.8% of the population may already have had the disease and so have increased immunity. Interpretation Analysis of current case data using infectious ratio has provided novel insight into the current national state and can be used to make better-informed decisions about future management of restricted social behaviour and movement.