An interesting comment by Chris T Bauch in The Lancet Infectious Diseases published October 22, 2020 looked at this point. The basic reproduction number (R0) is the average number of infections produced by a single infectious person in a population with no immunity. 

R0 has a close relative named the effective reproduction number (R). This is the average number of infections reduced by a single infected person in a population with partial immunity. 

Yu Li and colleagues estimated how the imposition and lifting of non-pharmaceutical interventions (NPIs) changed the R number for SARS-CoV-2 in 131 countries in the first half of 2020 and published this in The Lancet Infectious Diseases. 

If the R value is less than 1, an epidemic will eventually die out because each infected person generates less than one new infection. Ending an epidemic by keeping the R value below 1 could take a long time if there are many infections. However, when the R value is higher than 1, the epidemic could continue to grow. 

R values change over time: NPIs such as closing schools, physical distancing and mask use reduce the R. Hence R is often used to gauge whether a pandemic mitigation is working. 

Li and colleagues compared daily estimates of R at the country level against a database describing which NPIs each country applied and when. 

Generally, they found that imposing NPIs reduced R and lifting them later on, increased R. 

School closure, a public events ban, requirements to stay at home, and internal movement limits – both when being imposed and when lifted, had the biggest individual effects, changing R value between 3 and 25%. 

NPIs in combination were even more effective – the combined effect of school and workplace closure, a ban on public events and gatherings of more than 10 people, internal movement limits and stay at home requirements reduced the R by 52% some 28 days after they were introduced. 

The R0 value for SARS-CoV-2 lies somewhere between two and three, hence early pandemic interventions must reduce R by between 50% and 67% to bring it below 1. 

This estimate suggests that it might have been extremely difficult to flatten the curve in spring 2020 had the R0 for SARS-CoV-2 been a little higher. 

However, the R value is difficult. A single number cannot provide a complete picture of the state of a pandemic. 

National level estimates can hide local heterogenecity. 

Seasonal differences in contact patterns from spring to autumn are not captured by the short term wisdoms used in many epidemiological studies. 

Reporting delays, stochastic effects and super spreading can also bias R. 

Moreover, R does not tell us what proportion of infections are caused by an infected individual before symptom onset. 

This crucial distinction for infection control might explain why severe acute respiratory syndrome coronavirus did not cause a pandemic whereas SARS-CoV-2 has despite comparable R0 values. 

Li and colleagues discuss some of these limitations and also raise the issue of behavioural inertia. 

Timelines of decision making lend the perception that governments can turn NPIs on and off like a switch, but in fact, populations can take weeks to adjust their mobility patterns in response to imposition of NPIs. This effect probably contributes to the author’s finding that NPIs did not exhibit their maximum effect on R until up to 28 days later. 

Despite R’s imperfections, the findings of Li and colleagues tell us that NPIs work and which ones work best. This information is crucial, given that some NPIs have massive socioeconomic effects. 

In a similar vein, transmission models that project COVID-19 cases and deaths under different NPI scenarios could be highly valuable for optimising a country’s portfolio of NPIs. The success of large scale NPIs require population adherence – R can stimulate populations to act and gives them useful feedback on the fruits of their labour. This is probably why the R number is now so carefully considered by all. 

The London General Practice has kept abreast of all aspects of COVID-19 disease and is happy to offer a diagnosis, testing and safety net service for those affected individuals. 

Dr Paul Ettlinger 
The London General Practice 

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