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Before lockdown in Scotland one person with coronavirus had the potential to infect six other people. We are now eight weeks on from the “stay at home” restrictions, so is that infection level still the same?

Well, scientists and statisticians briefing journalists on Thursday morning outlined their thinking.

They begin their “technical” explainer by talking about a computer. It’s based at Edinburgh University and has taken nearly 60 hours to make an important calculation.

This isn’t a throwback to the age of slow dial-up internet, nor is it an attempt to compute the answer to life, universe, and everything,

Rather it’s taken an entire weekend for this top of the line computer to run varying models to calculate something called the R number.

Put simply, the R (or reproduction) value is a way of rating a disease’s ability to spread.

It’s the number of people that one infected person, who for example has coronavirus, will pass on, on average.

What is a bad number?

For example, measles has one of the highest R numbers of 15 in populations without immunity.

But what does that really mean? Let me illustrate.

At a rate of 1.1 (or R 1.1), 1,000 people could potentially cause the infections of almost 25,000 people over 60 days.

But at R 0.5, the number of infections would be under 2,500.

So the take-home point? Anything over R 1 = very bad.

• Follow the latest on the coronavirus outbreak in Scotland

Covid-19 has been broadly estimated to have a reproduction number of three (before lockdown), but this value varies region to region.

And so the unenviable task that this Edinburgh-based computer has is to calculate the R number for the coronavirus outbreak in Scotland.

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At the government briefing, journalists learned that estimates for the R number in Scotland ranged as high as 6 before social distancing measures were put in place.

This R value since then has hovered around the 0.7 – 1 mark.

But why the range, and why does it take a computer so long to generate a single number?

Well, reporters were told that a range of data has to be used to calculate the R value.

This data includes;

• the number of confirmed coronavirus cases across Scotland
• ICU admissions
• the average length of a person’s hospital stay
• the number of deaths
• and even deprivation data.

On that latter note, figures published on Wednesday by the National Records of Scotland revealed how the death rate from Covid-19 is significantly higher in the top quintile of people living in deprived areas

Even then, we learned there’s still a great deal of uncertainty over the accuracy of this calculation as experts try their best to analyse what is a rapidly moving and evolving target.

So, to improve this accuracy, multiple computer models from institutions such as Imperial College London and The London School of Hygiene and Tropical Medicine are run to better pinpoint a consistent rate.

Population matters

For example the Imperial model has generated an R number of 0.7 to 1, whereas The London School of Hygiene and Tropical Medicine has produced a value greater than 1 in just the last week.

Given the complexity of the task and the lack of real-time data, it’s then no surprise to learn that separate R numbers for care homes, hospitals and other communities are not forthcoming.

The technical briefing also revealed that age and underlying health conditions are the main reasons for why the R rate is higher in Scotland than say, London which has a rate of 0.4.

An essential point is that Scotland has a larger aging population than other regions.

At the end of the day though, journalists were told there is no magic R number that will trigger the end of a Scottish lockdown.