A health worker collecting a sample from a patient in Mumbai
A health worker collecting a sample from a patient in Mumbai
AFP

India's COVID-19 caseload mounted to 84,62,080 with 50,356 infections being reported in a day, while the number of people who have recuperated from the disease crossed 78 lakh pushing the national recovery rate to 92.41%, according to data updated by the Union Health Ministry on Saturday.

The coronavirus death toll climbed to 1,25,562 with 577 new fatalities, the data updated at 8 am showed.

A total of 78,19,886 people have recuperated from COVID-19 so far pushing the national recovery rate to 92.41 per cent, while the case fatality rate has further declined to 1.48 per cent.

The number of active cases of COVID-19 remained below 6 lakh for the ninth consecutive day.

There are 5,16,632 active cases of coronavirus infection in the country as on date which comprises 6.11 per cent of the total caseload, the data stated.

India's COVID-19 tally had crossed the 20-lakh mark on August 7, 30 lakh on August 23 and 40 lakh on September 5.

It went past 50 lakh on September 16, 60 lakh on September 28, 70 lakh on October 11 and crossed 80 lakh on October 29.

According to the Indian Council of Medical Research (ICMR), a cumulative total of 11,65,42,304 samples have been tested up to November 6 with 11,13,209?samples being tested on Friday.

The 577 new fatalities include 161?from Maharashtra, 64 from Delhi, 55 from West Bengal, 52?from Chhattisgarh, 35 from Karnataka, and 27 each from Tamil Nadu and Kerala.

Total 1,25,562 deaths reported so far in the country include 44,965 from Maharashtra, 11,347 from Karnataka,?11,299 from Tamil Nadu, 7,177 from West Bengal, 7,155 from

Uttar Pradesh, 6,833 from Delhi, 6,768 from Andhra Pradesh, 4,295 from Punjab, and 3,748 from Gujarat.

The Health Ministry stressed that more than 70% of the deaths occurred due to comorbidities.

"Our figures are being reconciled with the Indian Council of Medical Research," the ministry said on its website, adding that state-wise distribution of figures is subject to further verification and reconciliation.

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