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India may see 7 million COVID-19 cases by October, says study by BITS Pilani

The Union Health Ministry data on Friday said the number of coronavirus cases in India breached the 45 lakh mark while a data released by a national public health institute in the US said the number of infections in the North American country crossed six million as of September 8.

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Hyderabad Updated on: September 11, 2020 12:24 IST
India may see 7 million COVID-19 cases by October, says study by BITS Pilani
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India may see 7 million COVID-19 cases by October, says study by BITS Pilani

India may witness over seven million COVID-19 cases by the first week of October, surpassing the US and emerging as the country with the highest number of infections, a team of researchers from BITS Pilani, Hyderabad said on Friday.

The Union Health Ministry data on Friday said the number of coronavirus cases in India breached the 45 lakh mark while a data released by a national public health institute in the US said the number of infections in the North American country crossed six million as of September 8.

The team has been engaged in forecasting COVID-19 pandemic in India using advanced statistical learning techniques, lead researcher Dr TSL Radhika of the Department of Applied Mathematics, BITS Pilani, Hyderabad Campus said.

The team has recently communicated its findings to the ‘International Journal of Infectious Diseases’ published by the well-known publisher Elsevier.

“Our results obtained using a model based on statistical learning techniques applied to the existing data, indicate that India is likely to become the top COVID-19 country in the world, surpassing the United States by about the first week of October, that is in about a month’s time.

The total number of cases is also likely to cross the 70 -lakh mark by this time.

The figure, however, is contingent on the number of tests being carried out,” Dr Radhika said in email communication to PTI.

The researchers are now working on refining their model based on advanced machine learning techniques to make predictions for the longer term, the researcher added.

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