A Phased Approach to Unlocking During the Covid-19 pandemic - Lessons
from Trend Analysis
Abstract
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. Results 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 >200 times higher than reported cases,
providing evidence that by the end of the second week in April, 29% of
the population may already have had the disease and so have increased
immunity. Conclusion 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.