Coronavirus: Does the reproduction number tell us less than it used to?

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At the start of the coronavirus outbreak in the UK much was made of the reproduction number (R) of Covid-19.

This is the average number of people an infected person passes the disease onto and crucially, if that figure exceeds one, the disease could rapidly spread throughout the population again.

For a number of weeks the R value in the UK has remained below one, ranging from 0.7-1.0, and is currently at 0.7-0.9.

But experts say that as the number of infections in the UK drops, R becomes a less effective way of looking at transmission rates, especially regional R values.

As a result, from next week the Government will publish growth rates.

This is because at some point the focus needs to be on the numbers of cases and the incidence prevalence and growth.

The growth numbers will be based on the data rather than assumptions.

Scientists say that as the number of infections drop, it is not uncommon for the R value to increase.

For example, if one person passes it on to one other, the R rate jumps to 1.0, and if that infected person infects two others, it jumps further to 2.0, despite a small number of people in the population having the virus.

So policy implications of R = 1.0 when there are 1,000 new infections per day are very different to when there are 100,000 per day.

Experts explain that this is just an inaccuracy of the R, rather than a true reflection of the trajectory of the epidemic.

The Government advisers also say that going forward it is important to look at local outbreaks, and trace clusters of local outbreaks, rather than looking at regional figures.

They add that within the next few weeks they should be able to provide data looking at the numbers of cases, and incidents rather than just the R.

So why does R become less useful?

– When there are few cases, R is impossible to estimate with accuracy and will have wide confidence intervals that are likely to include one. But this does not necessarily mean the epidemic is increasing.

– As incidence decreases, R will tend towards 1, and has to be evaluated in conjunction with incidence.

– R is an average measure. When incidence is low, an outbreak in one place could result in estimates of R for the entire region to become higher than one.

Conversely, small, local outbreaks will not be detected. Estimates of R based on small numbers may also not capture change in the area fast enough to inform policy in a useful way.

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