What is R-number, why you should know about it, and what it says about COVID-19 situation in India-India News , Justnewsday

According to some estimates, India’s R-value has increased slightly to 0.88 in the first week of July after being at its lowest-ever value of 0.78 in June-end

**New Delhi:** From CFR (case fatality ratio) to subunit and mRNA vaccines to spike protein, words previously restricted to academic journals and research papers have appeared at the forefront of public discussion during the COVID-19 outbreak. One such term is the **R-number**, which several policymakers across the globe have kept at the core of their strategies against the pandemic. At the same time, some infectious disease experts say the ominous-sounding R could be getting **too much importance**.

On Wednesday, the Indian government cautioned against “blatant violation (of COVID-19 guidelines) in several parts of the country”, especially in public transport, hill stations and marketplaces. The consequent increase in the R-factor is a cause for concern, the government said.

**What is the R-number?** According to the website of global vaccine alliance Gavi, the R (reproduction) number of a virus tells us how **easily it spreads in a population**. It is the average number of people who will get the virus from an infected person.

- Experts say a higher R-number means that the virus is more contagious. For example, according to the Gavi website, measles is extremely contagious with an R-value of about 18. This means one infected person on average will infect 18 more people.
- The
**Sars-CoV-2 virus**, which causes COVID-19 , would have a reproduction number of about three if no action was taken to stop its spread, according to a BBC report. It means one infected person would on average pass on the virus to three more people. These three people would infect nine more, and so on.

**Why does the R-number matter?** It gives experts an indication of **how fast an infection is spreading**. Across the world, governments have put emphasis on keeping the R-value at 1 or below; this would mean an outbreak would slow down and eventually fizzle out because there would not be enough new patients/carriers to sustain an outbreak. Anything **above 1 is dangerous**, as it would mean the virus would keep spreading.

- According to the BBC report cited above, the R-number is among the Big 3 of the pandemic — alongside
**severity of the disease**(which could result in fatalities) and the**number of cases**, which is an indicator of when and how to act (for example, if a lockdown has to be imposed or eased). - Bringing “the pandemic under control means monitoring the R-number, as well as keeping the number of cases below hospital capacity, and balancing social and economic considerations”, according to Gavi.

**How is the R-number calculated? **It’s complicated. As the BBC report cited above suggests, “scientists work backwards” and rely on data on **fatalities, hospitalisation and number of people testing positive** for the virus to calculate the R-number. But still, there are variables.

- The R-value in an outbreak keeps changing.
**Lockdowns, social distancing and low population density**can help check the spread of the virus. - The R-number can also depend on
**immunity levels**(from prior infections or vaccination) in a population. - Because of so many
**variables**, detecting the real the R-number could be challenging. There have been instances of the R-number shooting up in the wake of relaxation of restrictions. - Calculating the R-value entails surveillance and gathering of
**comprehensive data**on hospitalisations, mortalities etc. — which at times could be challenging for even high-income countries.

**Does vaccination help?** Yes. For example, if the R-number of a virus is five, it means an infected person would give the disease to five people. Now, if three of these people are vaccinated (and protected against the virus), it would mean a drop in the R-value.

**The flip side:** Some infectious disease experts worry about placing too much focus on R, according to an article in the Nature. “Epidemiologists are quite keen on downplaying R, but the politicians seem to have embraced it with enthusiasm,” Mark Woolhouse, an infectious diseases expert at the University of Edinburgh in the United Kingdom, tells the journal.

The article details the argument on the limitations of R. Here’s a summary:

- The R-number “
**doesn’t capture**the current status of an epidemic”. Unless there are regular tests of a country’s entire population, it’s impossible to measure Rdirectly; so it is “usually estimated retrospectively”. - “Disease modellers look at current and previous numbers of cases and deaths,
**make some assumptions**to find infection numbers that could have explained the trend and then derive Rfrom these,” the article says. - R is an “
**average for a population**and therefore can hide local variation” (a regional cluster, for example). - Too much focus on R could cast a shadow on the importance of other measures, “such as trends in numbers of new infections, deaths and hospital admissions”.

**R in India:** According to some estimates, India’s R-value has increased slightly to **0.88** in the first week of July after being at its lowest-ever value of **0.78** in June-end. This means, at present, every 10 people with COVID-19 would infect nine others.

- This rise comes in the wake of
**several states relaxing restrictions**with cases ebbing after the peak of a disastrous second wave of infections. - Sitabhra Sinha, professor of physics and dean of computational biology at Chennai’s Institute of Mathematical Sciences, told news agency ANI the R-value had
**increased in February**to 1.02 from 0.93 (he led the study that came up with the 0.88 figure). - This was just before the second wave hit India with tremendous ferocity. During the second wave, R reached a
**peak of 1.31**on April 26. - Since then, according to ANI, the R-value had been declining — before the recent uptick, which has
**sounded alarm bells and**sparked fears of a**possible third wave**. - When the pandemic began in India in mid-March 2020, Sinha told ANI that R was at around
**2.5**. Then it dropped to**1.7**between 4 and 16 April, and then to**1.34**between 13 April and 15 May, thanks to the nationwide lockdown.

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