IIT-K to assess COVID curves & predict trajectories for Lucknow, Kanpur & other UP districts!

IIT-K to assess COVID curves & predict trajectories for Lucknow, Kanpur & other UP districts!

This would facilitate a sound and effective grip over the pandemic situation in different regions of Uttar Pradesh.
Published on
2 min read

In a bid to enhance its preparedness for managing COVID patients, the Uttar Pradesh government has roped in IIT Kanpur to predict the expected caseload in all of the state's 75 districts. Through a focused evaluation of the count of infections that may be witnessed in the upcoming days, the state administration aims to amp up the ongoing measures for the patients. This would facilitate a sound and effective grip over the pandemic aituation in different regions of Uttar Pradesh, especially Lucknow, the worst-hit city.

Inferences from the analysis to assist in avoiding medical emergencies

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In a recent review meeting to address the current COVID crisis, the Chief Minister of Uttar Pradesh was quoted saying, "In view of the Covid peak, experts all over the country have been coming up with analysis. We should coordinate with IIT-K for district-wise rigorous analysis of UP".

Deploying mathematical models, various experts in the country have converged their efforts to predict the future of the pandemic. Professors and academics at IIT-Kanpur have also been involved in this analysis ever since the start of the contagion in March 2020. Now, it will help the state government to initiate targeted steps based on its findings.

Professor Abhay Karandikar, director of IIT-K, asserted that Professor Mahindra Agarwal from the institute was involved in the national supermodel along with other specialists from across the country. It is anticipated that district-wise scrutiny of the current circumstances can help in deciphering trustworthy figures for the future. Though the study can aid in being ready for medical emergencies, the state officials need to keep the worst possible situation in their wider vision while planning interventions.

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