Until a few months ago most people had never heard of the R number. But now, thanks to the new coronavirus, we all know (or think we know) what it is.
The R number is the reproductive number of an infectious disease , and basically indicates how many people an infected person can give it to. In highly contagious diseases, such as measles, the figure can be close to 18. For COVID-19 it is estimated to be somewhat above 3.
The R0 (basic reproductive number) is the starting value that the R number registers at the beginning of an outbreak, when the population as a whole is still susceptible to infection. As the outbreak progresses, the R number becomes Re (effective reproduction number), which varies as infections increase and actions are taken to fight the spread of the virus.
The R number is being widely used as a basic indicator in determining political action in the UK. It is based on the premise that the value of the R number offers a quick assessment of the degree of control that one has over the outbreak. If its value is greater than 1, the disease is spreading. And if it is lower, it means that the outbreak is under control and that it will disappear. This explains why, now that the confinement measures are gradually being relaxed, the Government places so much emphasis on keeping the R number below 1.
However, a group of scientists calling themselves the Independent SAGE (and working in parallel with the Scientific Advisory Group for Emergencies [SAGE], which advises the British Government) is now publicly questioning the value of this indicator. In a recently published report, the group argues that the R number can be misleading and, therefore, they argue that the government should not attach so much importance to this indicator when deciding its policies.
The Independent SAGE is made up of 12 scientists from various fields and was created in response to concern over the lack of transparency blamed on the official SAGE committee. The group is made up of highly regarded scientists and is headed by David King, former Chief Scientific Advisor to the Government. Now, are they right? Is the R number really an adequate indicator to guide public policies?
Environment and human behavior
First, the R number does not depend solely on the virus itself, as it is also influenced by the environment and the behavior of the population . For example, the R number inside the Diamond Princess cruise ship is estimated to have been 11, while the world average is 3.28. Tight spaces and crew mobility throughout the ship facilitated the transmission of COVID-19. The virus was the same, but the environment and the behavior of the people were not, which explains the variation of the R number of the virus.
The R number also varies depending on the model used to calculate it. Using different data sets (for example, data from different countries, something that is done frequently) or using different formulas will return different R-number values for the same virus. In relation to COVID-19 we have seen values of the R number that have ranged between 1.4 and 11 depending on the environment , the data and the models used.
Second, and although we are talking about the R number for the United Kingdom as a whole, its value is not the same in all regions and nations of the country. Some rural areas may have very low transmission rates, while certain densely populated urban areas, as well as those with a high number of nursing homes and hospitals, may have significantly higher transmission rates. Thus, the value of the R number that serves as a reference for political action may not accurately reflect the level of transmission in a given territory, and thus may lead to errors when determining the level of precaution necessary.
Third, the R number does not represent a real-time value, but rather reflects transmission rates with a lag of about a week. For example, if we begin to ease containment measures, it would be important to know immediately if this is causing the viral transmission rate to increase. However, we cannot see these effects until after a week, when many people may have already been infected.
One tool among many others
Finally, by focusing on the R number we are ignoring many other important parameters of viral transmission, such as how long an infected person is contagious, or at what speed the number of cases increases. The R number is just one of many factors used to understand how an infectious disease spreads.
To fully understand virus transmission, it is necessary to examine a set of factors under conditions as close as possible to real-time analysis. In addition, the R number says nothing about how many people will need hospitalization, or how many will die, both data that are essential to design public health policies during an outbreak.
Therefore, and taking into account all these doubts about the reliability and usefulness of the R number, should it continue to serve as a guide for health policies?
The answer, without a doubt, is yes. However, no policy should be based on or evaluated based on a number drawn from a single calculation model. Instead, we should conceive of the R number as one more factor in the huge inventory of methods available to us to measure the progress of the outbreak. If we use specific data from each region and rely on real-time models, we will also be able to increase the level of precision of the R number. The objective is to know up to the minute the transmission of the disease and thus be able to analyze the effectiveness of actions course. The R number plays a crucial, but not unique, role in this assessment.
Jeremy Rossman, Honorary Senior Lecturer in Virology and President of Research-Aid Networks, University of Kent
This article was originally published on The Conversation. Read the original.
