For months, we’ve heard about the coronavirus R and K rate.
Both values are calculated by mathematicians and scientists working to combat the pandemic and used to influence public health policies. The experts analyse vast amounts of data – including hospital admissions, ICU admissions, deaths, self-reported symptoms and behaviour surveys – to estimate the R and K values. Each value offers a slightly different insight into the virus.
Confused about these terms and the difference between the two? Here’s what you need to know.
What is the R number?
The R number – sometimes referred to as the R0 – is the “basic reproduction number”. It’s used to measure the transmission potential of a disease.
The R value represents the number of people that one infected person will, on average, pass the virus on to. It’s influenced by characteristics of the specific disease (in this case, Covid-19), such as how easily it passes from person to person. Human behaviour – i.e. how closely we follow social distancing measures – will also impact the R number.
When the R number is below one, this suggests the number of cases is shrinking. Anything above one suggests cases and subsequent infections are growing – and is a cause for concern, because cases snowball.
While it can help indicate if lockdown measures are working, the R number doesn’t offer the full picture; the R value can show if an epidemic is getting bigger or smaller, but not how large it is.
“R should always be considered alongside the number of people currently infected,” the government website explains. “If R equals 1 with 100,000 people currently infected, it is a very different situation to R equals 1 with 1,000 people currently infected.”
What is the K number?
The K number, or K value, is a metric used to shed light on the variations of the R number across Covid-19 cases. It provides scientists with a more nuanced view of how the disease is spreading, rather than simply tracking if it’s spreading.
While the R number represents the average number of people a single infected person will go on to infect, the K number highlights that not all infected people will go on to infect the same number. It shows the difference in infection rates.
For example, if an infected person self-isolates straight away once contracting Covid-19, they are likely to infect fewer people than someone who has attended a mass gathering. The K value shows how much statistical variation there is in the spread of the virus.
When the K value is less than one, this indicates a high variation in spreading patterns.
“Once K is below one, you have got the potential for super-spreading”
“The general rule is that the smaller the K value is, the more transmission comes from a smaller number of infectious people,” Dr Dr Adam Kucharski, an expert at the London School of Hygiene and Tropical Medicine told The Guardian. “Once K is below one, you have got the potential for super-spreading.”
“Once K is above about five or 10, it tells you most people are generating pretty similar numbers [of secondary cases], you’re not getting these super-spreading events.”
Research indicates that before lockdown, the K number for Covid-19 was around 0.1 and 0.5, meaning a small amount of people were generating a large amount of new cases. In other words, “super spreaders” were influencing the R number.
As lockdown measures ease, the K number will help scientists identify what’s more likely to lead to super-spreading – be that pubs reopening, the use of public transport or mass events such as festivals, sports and weddings.
Alongside the R number, the K number may determine which areas of life can resume and which must remain on hold in order to control the virus.