India’s single-day recovery outstripped the number of new infections as nearly 96,000 people recuperated from the novel coronavirus, even as the total caseload went past 53 lakh, according to the Union Health Ministry data updated on Saturday.
The figures released at 8 am showed that while 95,880 people recovered from COVID-19 in a span of 24 hours, 93,337 new infections were recorded during the period.
With the latest inclusions, the total number of cases mounted to 53,08,014 and the recoveries to 42,08,431, pushing the recovery rate to 79.28 per cent.
The death toll, meanwhile, climbed to 85,619 with the virus claiming 1,247 lives in a span of 24 hours, the updated data showed.
The COVID-19 case fatality rate has further dropped at 1.61 per cent, the data showed.
There are 10,13,964 active cases of COVID-19 in the country, which constitute 19.10 per cent of the total caseload, the data stated.
The country’s COVID-19 tally had crossed the 20-lakh mark on August 7, the 30-lakh mark on August 23, 40 lakh on September 5, and it went past 50 lakh on September 16.
According to the Indian Council of Medical Research, a cumulative 6,24,54,254 COVID-19 samples have been tested up to September 18 — 8,81,911 of them on Friday.
The 1,247 new deaths include 440 from Maharashtra, 179 from Karnataka, 98 from Uttar Pradesh, 67 each from Andhra Pradesh and Tamil Nadu, 62 from Punjab, 59 from West Bengal, 31 from Puducherry and 30 from Delhi.
The total 85,619 deaths reported so far in the country include 1,791 from Maharashtra followed by 8,685 from Tamil Nadu, 7,808 from Karnataka, 5,244 from Andhra Pradesh.
The national capital has reported 4,907 deaths while 4,869 fatalities have been recorded in Uttar Pradesh, 4,242 in West Bengal, 3,286 in Gujarat, 2,708 in Punjab and 1,901 in Madhya Pradesh.
The health ministry stressed that more than 70 per cent of the deaths have 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.