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When it comes to loosening COVID restrictions all eyes are usually trained on the famous R number. But as epidemiologists Julia Gog and Thomas House recently explained to us, there's also another important factor to consider alongside R. That's the prevalence of COVID-19 in the population: the proportion of people who currently have the disease.
Put simply, if prevalence has been so high that the NHS is in crisis, then opening up might stretch it to breaking point, even if R is less than 1, or would remain so. If, on the other hand, prevalence is very low, we might be able to tolerate a higher value of R as it would not immediately lead to many cases. This is true particularly if prevalence has been low for some time.
We've illustrated this idea in the schematic plot below. The vertical axis measures prevalence and the horizontal axis measures R. Any point on this plot, such as the one we marked in black right in the middle, corresponds to a situation where we have the value of R that lies directly beneath the point on the horizontal axis, and the value of prevalence that lies directly to the left of the point on the vertical axis
read this excellent piece at https://plus.maths.org/content/R-not-all?nl=0
