DNA Explainer: What is R-Factor? Know how it predicts the spread of COVID-19

India’s R-Factor is at the alarming value of 1 for the first time since early May when the second wave was still rampaging through the country, having peaked at 1.37 between March 9 and April 21.

The trend then started declining to reach 0.78 between May 15 and June 26, before starting to climb back up. India’s R-Factor stood at 0.95 between July 3 and July 22. In the recent update, the number is now rising across 8 states. Officials fear the situation may again be getting out of control.

The R-Factor rising back to 1 has become a matter of concern for experts, a fear expressed by many including AIIMS Delhi chief Dr Randeep Guleria.  

What is the R-Factor?

A term restricted to epidemiology before COVID-19 pandemic, the number is fast becoming a part of common lingo. Also known as R-Value, R0 (R-naught) and R0 value, the number simply suggests the number of people being infected from one person in an area.

While an R-Factor of 1 would mean that an infected person is giving the virus to 1 other person, a value of 5 would mean that 1 person on an average is spreading the virus to 5 other people.

The R-Factor going above 1 indicates a fast spreading virus. NITI Aayog member and head of Centre's COVID task force, Dr VK Paul explained the important of R-Factor recently, “Please remember that R number should be 0.6 or below. If it has gone over 1, it shows it is a significant problem and the virus wants to spread.”

Where the R-Factor is rising in India?

As per the most recent update from the country’s COVID-19 task force, 8 states are seeing their R-Factor rising. High positivity is being reported from 44 districts.

The R-Factor is more than 1 in Kerala Tamil Nadu, Karnataka, Jammu and Kashmir, Himachal Pradesh, Mizoram, Puducherry and Lakshadweep. Furthermore, the R-Factor is at 1 in Delhi, Haryana, West Bengal, Nagaland, Jharkhand and Goa.

Two states currently showing a decline in spread of infection are Maharashtra and Andhra Pradesh.

A bigger concern: The time lag in R-Factor

While R-Factor is the foremost tool for understanding the rate of spread in a country, city or state, it has a time lag. This is because detection of any infection is almost always delayed. To understand the R-Factor of an infection spread, scientists collect and analyse data from earlier days.

It is possible that the spread is happening quicker that the data modelling mechanism is able to predict. Hence, a number of other factors like hospitalizations, daily positivity of cases and death toll are taken into account to understand the severity of the spread.