India reported the highest number of new COVID-19 cases in three weeks on Friday. Although the rise in new cases is largely restricted to a few states, it has renewed fears that a third wave could be imminent. Authorities have attributed the steady increase in coronavirus cases to a rise in the R0 (R-naught) value. Epidemiologists use this number to understand the movement of a virus in a geographical area during a specific period. Knowing the R-Value is a crucial first step in curbing the spread of any virus.
Since the beginning of the pandemic, this value has leapt out of academic journals and found a place in public discourse by politicians, health experts and even the general public. But what is this number that has so many people interested as well as scared?
What Is An R-Value?
Also known as R0-Value, R Factor or number, it is the effective reproductive number of a virus. That is - the number of people an infected person will pass on the virus to. For example: If measles - a highly contagious infectious disease - has an R number of 10 in populations without immunity, this means every infected person will spread the virus to 10 others, on average, who will then infect 10 more and so on.
During the second wave, when COVID-19 spread was rampant across India, scientists had estimated that the overall R-value in the country to be 1.37 from March 9-April 21. It declined to 1.18 between April 24 and May 1 and further to 1.1 between April 29 and May 7.
On Friday, India reported 44,230 new cases. It was the highest recorded case in three weeks. The states contributing the biggest chunk to the national caseload are Kerala, Karnataka and the states in the Northeast.
With an R-Value of 1.11, Kerala has been reporting over 22,000 cases for the past three days, accounting for more than 37 per cent of the country's active cases, government sources say. Karnataka, too, has reported a steep growth of 34 per cent in fresh Covid cases between Wednesday and Thursday. Similarly, many parts of the Northeast are reporting a positivity rate of more than 5 per cent, some even over 10 per cent.
With over 85% of the districts recording less than a 5% test positivity rate, India is fighting #COVID19 with all its might!— MyGovIndia (@mygovindia) July 29, 2021
But the pandemic is NOT over yet, let's #Unite2FightCorona & take the #JanAndolan pledge today: https://t.co/gaCIhQQ7u3#IndiaFightsCoronapic.twitter.com/X5tQugw83W
Why Is R-Value Of More Than 1 Dangerous?
Because this indicates that every infected person is spreading the virus to more than one person, resulting in a continuous increase in viral cases. Authorities all over the world try to bring the value of R to less than one to control the movement of a virus and eventually stop the outbreak.
How Is It Calculated?
It is difficult to capture the moment when a person catches the infection. Almost always, infections are detected with a delay. So, scientists work backwards to collect the data related to the spread of a virus – such as the number of people dying, admitted to hospital or testing positive for the virus over time. This data is used to estimate how easily the virus is spreading.
Initially, the R-Value was used to understand whether a population was growing or not within geography. Scientists later deployed the same method to know the viral spread.
How Accurate Is It?
Some scientists have argued against relying only on R-Value to decide when to impose restrictions, saying R-Values are only an indication of the spread and it has a time lag. The virus could be moving at a faster pace than this modelling would suggest.
There are two other ways, they say, that should also be considered in addition to the R-Value. One is the severity of the infection and the other is the number of cases. Together, they can give the clearest picture of the outbreak so that authorities could decide when to act.