COVID-19: IIT Delhi develops 'risk-index' to implement state-wise lockdown
The IIT Delhi has come up with a risk index to help states under different coronavirus zone implement the forth lockdown effectively to contain its spread.
The Indian Institute of Technology (IIT) Delhi has developed a risk index to help different states in India to implement the fourth lockdown to contain the spread of coronavirus in India.
The 'risk index' was developed by IIT Delhi's Department of Management Studies through research-based on proxy measures for severity, likelihood, and delectability of Covid-19 for each of the states in India.
This risk index has divided the nation into five portions which will be further sub-divided into the orange, red, and green zones. The areas divided are High Risk, Medium High-Risk, Medium Risk, Medium-Low Risk, and Low Risk.
Among the states identified as in the medium high-risk area by the IIT study are Gujarat, Bihar, Maharashtra, Karnataka, Tamil Nadu, and Andhra Pradesh.
In the medium-risk cluster, the states that have been identified are Delhi, Jammu and Kashmir, Haryana, Punjab, Jharkhand, West Bengal, and Chhattisgarh.
Professor Arpan Kumar Kar, who led the research, said at a time when the country is stuck in a trade-off between saving lives and saving the economy, the IIT team has proposed a risk identification and mitigation framework for the development and implication of an orderly state-by-state lockdown instead of a complete nationwide lockdown.
At a specific time, there may not be a better alternative than a complete lockdown to flatten the curve and give the time to the state administration to prepare for the pandemic," he said.
"While many of the states are still at a very critical stage, it is necessary to examine not only on the basis of total current cases of Covid-19 in states but other parameters as well, before planning for further lockdown restrictions," he explained.
"Such other parameters would typically gauge a state's preparedness to address the aftermath of the pandemic as and when it spreads as well as the probability to get impacted in the long run," Kar said.
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