Written By: Satata Karmakar | Updated : April 9, 2021 11:51 AM IST
Coronavirus Updates: 2nd COVID-19 Wave To Peak Between April 15-20
India registered a staggering 1,31,968 new COVID-19 cases on Friday, pushing its infection tally to 1,30,60,542, while the death toll increased to 1,67,642 with 780 more fatalities in a day, the highest since October 18. At a time when the country is witnessing such a huge spike in the number of novel COVID cases from across the corners, scientists have predicted that the current second wave will peak somewhere between April 15-20 and then see a decline. According to the experts, the number of 'active' symptomatic cases during this period would hit a high, roughly a week later, at the same level of around 10 lakh cases that the country had seen in September last year.
The scientists have predicted after using a mathematical model that the ongoing second wave of COVID-19 pandemic across the country may see a steep decline by the end of May. During the first wave of COVID-19 infections across India, the mathematical approach, named 'SUTRA', predicted that the initial surge of infections in August would peak by September and lower in February 2021.
Scientists, including Prof. Manindra Agrawal from the Indian Institute of Technology (IIT) Kanpur, applied the model to predict the trajectory of the current surge in infections and found that the number of daily new infections was likely to peak in mid-April for this ongoing pandemic wave.
Prof. Agrawal in the IIT's Department of Computer Science and Engineering was involved with the national 'super model' initiative and said that the peak is expected to see between 80,000-90,000 new infections per day. "We will cross the peak (during April 15-20) and then there will be very a sharp drop over the next 15-20 days," said Agrawal.
The national 'super model' had in October last year predicted the pandemic can be controlled by early 2021 with "minimal active symptomatic infections" in February. Asked about the possible explanation of the second wave, Agrawal said there were two reasons or possibly the combination of the two, that might explain what changed in February which could make it for the sharp rise. Here's what he said:
1. It could be due to gatherings linked to the opening up of schools, colleges, and other working areas where people became comparatively more careless, and
2. The fact that there are some mutations that are spreading faster.
However, like with the first wave of the COVID-19 pandemic, the trajectory of fresh infections would depend on a lot of other factors including measures rolled out by the government and adherence to safety protocols by the public.
A warning in the original prediction by the expert committee in their supermodel may still apply if the number of COVID-19 cases starts declining in the fourth week of April. The warning was: "However, this number will start rising again if proper practices of masking, disinfecting, tracing, and quarantine are not followed. The downward trend will continue only if we continue with the above practices."
In the mathematical model used to predict the COVID wave, there are parameters that measure the rate of spread or the contact rate which may explain how many people could be infected on average by one infected person. Agrawal noted that the model uses three main parameters to predict the course of the pandemic.
The first is called Beta, or contract rate, which measures how many people an infected person infects per day. It is related to the R-naught value, which is the number of people an infected person spreads the virus to over the course of their infection.
The other two parameters, he explained, are 'Reach', which is a measure of exposure level of the population to the pandemic, and 'Epsilon' which is the ratio of detected and undetected cases. "The contact rate had doubled in March and that may be contributing to the very steep rise," said Agrawal.
The 'super model' in October had come out with a 'conditional' prediction. It had predicted that the Covid-19 would be completely under control provided people continue to observe the same precautions such as practices of masking, disinfecting, tracing,and quarantine
However, the IIT Kanpur professor added that the prediction of the new peak is sensitive to the daily new infections data. Even a little bit of change each day, causes the peak numbers to change by several thousand numbers.
"The reason we had to introduce 'Reach' is that, unlike earlier pandemics which start at a location and suddenly spread fast across a place, but in Covid, the spread of the pandemic has been slower due to the many protective measures in place," Agrawal explained. He further said that the 'Epsilon' helps factor in the number of asymptomatic infections across the country. "We try to estimate the undetected and asymptomatic infections," he added.
India's COVID-19 tally had crossed the 20-lakh mark on August 7 last year, 30 lakh on August 23, 40 lakh on September 5 and 50 lakh on September 16. It went past 60 lakh on September 28 last year, 70 lakh on October 11, 80 lakh on October 29, 90 lakh on November 20 and the one-crore mark on December 19.
According to the Indian Council of Medical Research (ICMR), 25,40,41,584 samples have been tested for COVID-19 in the country so far, including 13,64,205 on Thursday.
The 780 new fatalities include 376 from Maharashtra, 94 from Chhattisgarh, 56 from Punjab, 39 from Uttar Pradesh, 36 from Karnataka, 35 from Gujarat, 27 from Madhya Pradesh, 24 from Delhi, 19 from Tamil Nadu, 18 from Kerala and 11 from Haryana.
A total of 1,67,642 deaths due to the disease have been reported so far in the country. The figure includes 57,028 fatalities from Maharashtra, 12,840 from Tamil Nadu, 12,767 from Karnataka, 11,157 from Delhi, 10,370 from West Bengal, 9,003 fromUttar Pradesh, 7,334 from Punjab and 7,268 from Andhra Pradesh.
The Union Health Ministry stressed that more than 70 per cent of the deaths occurred due to comorbidities. "Our figures are being reconciled with the ICMR," the ministry said on its website, adding that state-wise distribution of figures is subject to further verification and reconciliation.
(With inputs from Agencies)
