Active COVID-19 cases in India may peak at 48 lakh between May 14 and 18: IIT Scientists

New Delhi: A mathematical model by IIT scientists have stated that active cases in the ongoing second COVID-19 wave in India may peak at 38-48 lakh between May 14-18 and daily new infections could hit a high of 4.4 lakh from May 4-8.

As India today saw a single-day rise of 3,52,991 (3.52 lakh) COVID-19 infections and 2,812 fatalities with 28,13,658 (28.13 lakh) active cases, the scientists from the Indian Institute of Technology (IIT) in Kanpur and Hyderabad applied the Susceptible, Undetected, Tested (positive), and Removed Approach' (SUTRA) model to predict that active cases would go up further by over 10 lakh by mid-May. The latest projection tweaks the time frame as well as the numbers.Read more

Last week, the researchers predicted that the pandemic may peak between May 11-15 with 33-35 lakh total active cases and decline steeply by the end of May.

However, earlier this month, their modelling approach projected that active infections in the country would peak by April 15, which didn't come true.

Maninder Agrawal, professor at the Department of Computer Science and Engineering, IIT-Kanpur, said this time, he has also computed minimum and maximum for predicted values and posted it and he is reasonably confident that the actual values will be within the minimum and maximum values mentioned.

On Sunday, the professor shared the new peak values for active and new COVID cases in a Twitter thread.

"Peak timing: May 14-18 for active infections and May 4-8 for new infections. Peak value: 38-48 lakhs for active infections and 3.4 to 4.4 lakhs for new infections. So it is not clear what will the final values be.

Peak timing: May 14-18 for active infections and May 4-8 for new infections.

Peak value: 38-48 lakhs for active infections and 3.4 to 4.4 lakhs for new infections."

Also, he noted that it was not clear what the final values would be.

Explaining the changing projections of the model over time, he said that the primary reason is there is a continuous slow drift in parameter values of the current phase for India. This makes the guess of the right values difficult. That is causing a slow change in predictions.

As per the source, some fraction of asymptomatic patients could also be detected due to contact tracing and other such protocols, whereas previous papers divided the patient population into asymptomatic and Infected, the new model also accounts for the fact that.

The professor also noted that the SUTRA model uses three main parameters to predict the course of the pandemic. The first is called 'beta' or 'contact rate,' which measures how many people are infected per day. Read more

He explained that it is related to the R-nought value, which is the number of people an infected person spreads the virus to over the course of their infection.

The other two parameters are 'reach' which is a measure of the exposure level of the population to the pandemic and 'epsilon' which is the ratio of detected and undetected cases.

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