The Covid-19 coronavirus reproduction number or R value in England remains unchanged from last week and is between 1.2 and 1.4 according to the latest government figures.
However, the South West and North East and Yorkshire regions have higher R-rates and growth rates.
R stands for the average number of people that each Covid-19 positive person will later become infected.
When the number is above 1, an outbreak can grow exponentially, but when it is below 1 it means the epidemic is shrinking.
The government website states, “These estimates represent the transmission of COVID-19 2 to 3 weeks ago due to the time lag between a person becoming infected, developing symptoms, and needing health care.
An R value between 1.2 and 1.4 means that an average of every 10 infected people infect between 12 and 14 other people.
“A growth rate between 3% and 5% means that the number of new infections is growing between 3% and 5% every day.
“These estimates represent the transmission of COVID-19 2 to 3 weeks ago due to the time lag between a person becoming infected, developing symptoms, and needing health care.”
|region||R.||Growth rate% per day|
|England||1.2 to 1.4||3 to 5|
|East of england||1.1 to 1.3||2 to 5|
|London||1.1 to 1.3||2 to 5|
|Mittelland||1.2 to 1.4||3 to 6|
|North East and Yorkshire||1.2 to 1.5||4 to 8|
|northwest||1.1 to 1.4||3 to 6|
|South east||1.1 to 1.3||2 to 5|
|southwest||1.3 to 1.7||6 to 11|
The government website states: “If the number of cases, hospitalizations, or deaths is low, and / or there is high variability in transmission in a region, then care should be taken in interpreting estimates of R and growth rate.
“For example, significant variability in a region due to a local outbreak may mean that a single average does not accurately reflect the way infections are changing in that region.
“Estimates for R and growth rates are presented as a range, and the true values are likely to be within that range. The estimation intervals for R and growth rate may not exactly match due to the presentation of different independent estimates and roundings. “