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‘Spike in cases result of under-diagnosis’

Till the time of the final analysis for this study till July 31, India had 16,38,870 confirmed cases.

Published: 25th August 2020 02:04 AM  |   Last Updated: 25th August 2020 11:02 AM   |  A+A-

Health workers collect swab samples for coronavirus through rapid antigen tests in New Delhi.

Health workers collect swab samples for coronavirus through rapid antigen tests in New Delhi. (Photo | Shekhar Yadav, EPS)

By Express News Service

NEW DELHI:  Various containment measures for Covid-19 by the Centre may have delayed the peak of the pandemic by about 100 days, but due to underdiagnosis of the infected asymptomatic subpopulation, India is witnessing a sharp rise in cases, says a new study.

The analysis by researchers at the JNU in Delhi was based on the stratification of the lockdowns and un-lockdowns into seven phases and calculation of the basic reproduction number or R0 for each phase. 
The reproductive factor refers to how many other people will be infected from a single patient.

Till the time of the final analysis for this study till July 31, India had 16,38,870 confirmed cases. The analysts found that while the basic reproduction number R0 decreased significantly for the second phase due to strict lockdown, it started increasing in the upcoming phases due to various relaxations.

“The peaks for different infected subpopulations are considerably delayed. Underdiagnosis of the infected asymptomatic subpopulation will lead to sudden outbreak of cases,” noted researcher. “Without lockdown the peak of cumulative infected cases could have occurred very soon with drastic mortality rate.” They added that modelling results can be used for constructing efficient strategies to prevent further spread. 

The study also pointed out that policies such as social distancing and quarantine alone are not sufficient to end the pandemic. “Other stringent policies like complete lockdown as well as more testing of susceptible populations should be considered and must be incorporated systematically in mathematical models,” it stressed. 

The authors took note that there were some misperceptions in the early phase of pandemic due to lack of information and many asymptomatic cases were not diagnosed, which leads to the underestimation of infected cases.

“Modelling results quantify the approximate error in estimating the actual number of cases due to inadequate number of tests being performed,” they said. “The model predictions help us to explain the long-term effects of insufficient number of diagnostic tests, with sudden outbreak after a long silent period.”

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