Pandemic

Between 2020 and 2022, China imposed a rigorous zero-Covid policy to control its spread and keep the infections and fatalities at or near zero. Stringent lockdowns, frequent PCR tests, and strict restrictions on entry into China were important features of this policy. Although extremely successful during the first two years of the pandemic in preventing the spread of deadly COVID-19 variants such as the Delta, the policy proved ineffective against the Omicron variant. This article examines China’s response to the spread of COVID-19, the framing of this response through nationalist narratives, and the eventual chaotic pivot from zero-Covid policy.

The paper attempts to forecast the growth pattern of the COVID-19 spread in India and examines the impact of the lockdown on its spread and deaths. Comparing different models for short-term forecasts—hybrid autoregressive integrated moving average with errorremodelling using fast Fourier transform—has been found to have better accuracy. It is observed that the data set starting from the first phase of the lockdown generates more accurate estimates. The impact analysis shows a clear trend break on 3 March for confirmed cases and 11 March for the deaths.

The slump and recovery in growth varied substantially and adversely affected disparate states.

Lack of access to disadvantaged minorities and discriminated social groups limits the gains.

Paired with the borrower score/ rating, a credit resilience score would better equip the fi nancial institutions to account for borrower resilience and make credit decisions accordingly. The requirement for CRS in India helps credit to fl ow uninterruptedly during good and bad times. Recognising the parameters used in the existing credit score for individuals and corporate credit rating, a framework for the development of CRS is suggested.