GS PAPER II
Lessons from India’s all-cause mortality data
Why in News
- The scale of devastation caused by India’s COVID-19 epidemic is gradually becoming clearer.
- The mortality data, from State and city civil registration systems, paint a grim picture of a major increase in deaths across the country during the novel coronavirus pandemic.
- Very few of these additional deaths have been recorded as COVID-19 deaths.
Cautious estimate
- The data suggest an approximate answer: during 15 months from April 2020 to June 2021, there were 3.5 million-3.7 million “excess deaths” nationwide. This amounts to 35% more deaths than expected.
- This estimate is cautious, and likely to increase as more data come in. Data for June and beyond are very limited, and so the story is incomplete.
Data in the pandemic period
- Death registration data for the pandemic period are limited. It is unavailable for some States, and incomplete in others.
- Some data are organized according to date of death, and some by date of registration.
- Moreover, there are uncertainties about death registration prior to the pandemic.
- In some States, official estimates of levels of registration, which we use, appear to be overestimated.
- Compounding the difficulties, registered deaths show complex trends in some States, for example, gradually increasing prior to the pandemic, but dropping sharply around the time of the national lockdown before the pandemic deaths start to show.
- Data from 12 States where partial or complete civil registration data are available for at least January 2018 to May 2021: Andhra Pradesh, Bihar, Haryana, Himachal Pradesh, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Punjab, Rajasthan, Tamil Nadu and West Bengal.
- These States comprise roughly 60% of the national population.
- During April 2020-May 2021 we found six million death registrations in the data; that is 1.3 million more than expected from 2019 data.
- If we assume that the deaths which were not captured in these registration systems, including unregistered deaths, rose proportionately, we arrive at an estimate of around 1.7 million excess deaths in these States up to May.
- If these 12 States reflect the national picture, then India saw around 2.8 million excess deaths nationwide during April 2020-May 2021. This is 8.5 times the official COVID-19 death toll of 3,32,000 over the same period.
Global comparison
- Assuming the ratio of excess deaths to official COVID-19 deaths does not change rapidly, 3.5 million-3.7 million excess deaths nationwide by the end of June. Over a 15-month period, for every three expected deaths, there was a further “pandemic death”.
- This places India among the harder hit countries in the world. It would mean that relative to baseline, India’s surge in mortality is lower than that of Mexico, similar to that of Brazil and South Africa, and considerably higher than in the United States, the United Kingdom and most of western Europe.
- Moreover, the estimates are conservative. There are also hints that disruption may have prevented, and not merely delayed, many death registrations.
- Moreover, there are good reasons to believe the mortality surge may have been greatest in marginalised communities where death registration is weaker.
- According to the latest national sero-survey, around 60%-70% of people in India may have been infected with the virus by June.
- If so, international data on fatality rates suggest we should expect two million to four million COVID-19 deaths.
- So, it is quite plausible that the majority of India’s excess deaths have been from COVID-19.
Individual States
- In individual States, all-cause mortality data paint diverse pictures.
- Kerala, Punjab and Himachal Pradesh stand out for having somewhat lower excess mortality than expected, even after we adjust for possible disruptions to registration.
- Andhra Pradesh and Madhya Pradesh, on the other hand, saw considerably more deaths than expected.
- Overall, around two-thirds of the excess deaths took place during a shocking mortality spike around May 2021.
- Madhya Pradesh’s explosive second wave accounted for 80-90% of its excess deaths. By contrast, Maharashtra saw more even surges, with over 40% of its excess deaths during its first wave.
- There are striking variations in the ratio of excess deaths to recorded COVID-19 deaths. In Maharashtra excess deaths up to May 2021 are roughly four times recorded COVID-19 deaths, or less if we factor in reconciliations of COVID-19 deaths during June and July.
- By contrast, in Madhya Pradesh, excess deaths are an astonishing 25-30 times recorded COVID-19 deaths.
- Some civil registration data are available for Uttar Pradesh up to April 2021, and these appear to show a major surge in mortality; but there are huge fluctuations in registrations, and unexplained discrepancies with historical data which make it hard to use this data with any confidence.
A perspective
- If we accept the estimate that 92% of deaths were registered in 2019, higher registration coverage could not cause a 35% surge in death registrations.
Conclusion
- During the relatively quiet period between the two COVID-19 waves (January-March 2021), we see death registrations return close to 2019 baseline levels.
- There are no easy ways to explain away or deny the scale of the catastrophe.
- Yes, there are uncertainties, and details will change as more data become available.
- Most likely, the numbers will increase.
- One thing is clear: during the COVID-19 pandemic, India has witnessed a surge in mortality on a scale not seen since Independence.
GS PAPER III
Optimistic assessment
Why in News
- Less than a fortnight after the RBI announced its latest monetary policy, a team of its officials has provided an optimistic assessment of the ‘State of the Economy’ in the August issue of the central bank’s monthly bulletin.
- Pivoting from what the bank posited on August 6 when it said, “the outlook for aggregate demand is improving, but still weak and overcast by the pandemic”, the officials led by Deputy Governor asserted that aggregate demand conditions had been buoyed by pent-up demand released by unlocking and vaccination.
Monetary Policy
- The economy was gaining traction could be seen in manufacturing activity gradually turning around even as the contraction in services had moderated.
- Several high-frequency indicators including E-way bills, toll collections, fuel consumption, automobile dispatches and registrations, and rail freight volumes to buttress their view that demand is regaining momentum.
- The team has also pointed to a private forecaster’s data showing a sizeable sequential decline in the unemployment rate July, to 6.95% from 9.17% in June, and that with a pronounced rural bias, to posit that this reflects the “resilience of the rural sector on brightened agricultural prospects”.
- But the authors elide over the fact that the CMIE, whose survey-based unemployment rate they have cited, is far less sanguine about the addition of approximately 16 million jobs in July.
- CMIE MD contends in an analysis that “all the additional employment provided by India in July was of poor quality” while better quality salaried jobs shrank by 3.2 million, noting that the bulk of the rural jobs added were of temporary farm labor linked to delayed kharif sowing.
- The RBI officials also throw no additional light on the concerns that earlier this month prompted the central bank’s Monetary Policy Committee (MPC) to cut its own June forecast for GDP growth in the second, third and fourth fiscal quarters by between 0.5 and 0.9 percentage points.
- On inflation too, the article’s authors have pitched an upbeat prognosis citing July’s 70 basis points month-on-month deceleration in retail price gains to 5.6% as “reinforcing the view that the recent upsurge has peaked and the worst would be behind us”.
Conclusion
- However, official food price data for the August 1-12 period reveals an uptick in cereal prices, while edible oils continue to see price pressures after July’s 32.5% inflation rate for oils and fats, belying the authors’ optimism.
- The RBI Deputy Governor overseeing monetary policy admits the internal dilemma at the MPC observing that ultimately the policy decision was “a judgment call” as any move to tame inflation by one percentage point would mean ‘sacrificing’ 1.5-2 percentage points of GDP growth.
- In postulating an either-or trade-off, monetary authorities risk achieving neither goal and sending the economy into a harder to redress state of ‘stagflation’.