Active COVID-19 Cases In India To Hit Peak Of 2.6 Lakh On July 15: Report

India will hit a peak of 2.6 lakh active COVID-19 cases on July 15, according to the ‘most likely’ scenario, and a peak of 3.9 lakh cases on July 25 as per the Susceptible Exposed Infected Recovered (SEIR) model, said the latest projections released by Times Fact-India Outbreak Report for both national and state levels.

Key takeaways for July

1. Maharashtra, which is the worst-hit state, is projected to hit its peak of 82,723 active cases according to the ‘most likely’ model on July 5 and 1.1 lakh active cases as per the SEIR model, on July 17.

2. Tamil Nadu is projected to hit its peak of 30,247 active cases according to the ‘most likely’ model on July 5 and 32,909 active cases as per the SEIR model on July 6.

3. Delhi is projected to hit its peak of 47,461 active cases according to the ‘most likely’ model and 47,159 active cases as per the SEIR model both on July 4.

4. Gujarat is projected to hit its peak of 6,761 active cases according to the ‘most likely’ model and 7,044 active cases as per the SEIR model both on June 29.

5. West Bengal is projected to hit its peak of 7,149 active cases according to the ‘most likely’ model and 10,417 active cases as per the SEIR model both on June 30.

6. Mumbai and Chennai are projected to hit their peaks of 37,194 active cases and 21,268 active cases on June 30 and July 3, respectively, according to the most likely model. As per the SEIR model, Mumbai is projected to hit is peak of 38,899 active cases on July 15 and Chennai will reach its peak of 19,054 active cases on July 6, respectively.

Led by insights and efficacy, the report has achieved an accuracy rate of 96 per cent for active cases, with an overall prediction level of 92 per cent plus for its previous projections. The report showcases several pertinent data points which include India’s possible peak points, state & city wise projections, and active cases over a period of time and report follows a sophisticated and vigorous mathematical modelling.

The models are dynamic and with fresh data drawn from central government, state government bulletins, and daily updates provided by the Health Ministry, the graphs are changed accordingly on a weekly basis, thereby presenting the best projections.

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