Why does the rate of reproduction of the epidemic vary around the country, and which areas are worst?
Scientists are struggling to explain why the coronavirus infection rate varies in different parts of the country.
The so-called ‘R-number’ – the number of people each infected person passes the virus to – has been estimated at between 0.7 and 1.0. If it’s under 1.0, that means the rate of infection is going down; if it’s over, it’s going up, and as the rate of spread increases exponentially, any figure over 1.0 is very dangerous.
A survey by the Office of National Statistics suggests that 1 in 400 people in the UK may be infected – that’s about 148,000 people. But the survey excluded people in hospitals or care homes, where the rate of infection is likely to be much higher.
And modelling published by the University of Cambridge suggests that the R-number varies according to where in the country you are, ranging from 0.4 in London to 0.8 in the North East, and a study at the London School of Hygiene and Tropical Medicine agrees, though putting the number for London at 0.6, Wales at 0.8 and the South West at 0.9, suggesting a slow decline in infections; but in both Scotland and Northern Ireland the value is 1.0, suggesting no fall in the infection rate.
Cumberland, Durham, Herefordshire and Norfolk now have 12 times as many cases of coronavirus as counties like Devon, Cornwall and Dorset.
Different studies use different base figures and reporting methods, which makes it harder to explain the results, so there’s still no conclusion on why the figure varies in different areas. Possibly the type of work in different regions is a factor – one possible explanation is that more Londoners do service jobs which can be done from home.
Even in areas where the R-number is under 1.0, there’s no room for complacency; reports of only 49 new cases in London hospitals on Thursday 14th May might be hiding hundreds of undiagnosed cases.
NHS England national medical director Stephen Powis said: “There will be variations between different parts of the country, that occurs naturally in epidemics. We see that, for instance, in flu season each winter. What’s important going forward is increasingly we will be able to measure R direct.”
The Office for National Statistics this week published its first direct testing of a random sample of the population, and over the next few weeks should be able to supply better information of the directly measured R-rate, rather than one derived from models and other observations.
“That I think will give us a clearer picture of exactly how the infection is progressing in different parts of the country’, said Stephen Powis.
Prof Matt Keeling from the University of Warwick said: “I am extremely worried about the media message that London could be coronavirus free in days. If people think London is coronavirus-free that could be dangerous, and could lead to complacency, undermining all the struggles and sacrifices that everyone has made so far. A relaxation of vigilance could easily see R increasing above 1.0, and a second epidemic wave.”