Taking a dig on the authorities, Congress chief Rahul Gandhi in the present day mentioned its “nicely deliberate battle” in opposition to coronavirus has allegedly put India in an “abyss” of GDP discount of 24 per cent, 12 crore job losses, 15.5 lakh crore further careworn loans and globally highest every day COVID-19 instances and deaths.
The Congress has accused the Modi authorities of not dealing with the COVID-19 pandemic successfully.
The federal government has dismissed all such claims previously.
“Modi Govt’s well-planned battle’ in opposition to Covid has put India in an abyss of: 1. Historic GDP discount of 24% 2. 12 crore jobs misplaced 3. 15.5 lac crores further careworn loans 4. Globally highest every day Covid instances & deaths,” Rahul Gandhi mentioned in a tweet.
Modi Govt’s ‘well-planned battle’ in opposition to Covid has put India in an abyss of:
1. Historic GDP discount of 24%
2. 12 crore jobs misplaced
3. 15.5 lac crores further careworn loans
4. Globally highest every day Covid instances & deaths.
However for GOI & media ‘sab changa si’.
– Rahul Gandhi (@RahulGandhi) September 12, 2020
However for the federal government of India and the media “sab changa si (all is nicely)”, the previous Congress chief mentioned.
Rahul Gandhi’s reference to “well-planned battle” in opposition to COVID-19 is seen as a jibe at Residence Minister Amit Shah. Mr Gandhi’s tweet comes days after Amit Shah mentioned that India is placing up a “well-planned” battle in opposition to the pandemic beneath Prime Minister Narendra Modi’s management.
Amit Shah, on Thursday, mentioned “Coronavirus is an unprecedented problem for us. However we’re preventing in opposition to it in a well-planned method beneath the management of Prime Minister Narendra Modi and your complete world has recognised our efforts.”
India’s COVID-19 caseload has gone previous 46 lakh, whereas 36,24,196 folks have recuperated thus far taking the nationwide restoration charge to 77.77 per cent on Saturday, in response to Union well being ministry information.
(With inputs from PTI)