On March 11, 2020, the WHO declared Covid-19 a global pandemic. Since then, as on May 26, 2021, the world has seen as many as 16,95,97,415 positive cases and 35,30,582 casualties. It has spared none; world’s largest economies, fast growing economies, emerging economies, poor economies, name any and they will have dreadful accounts on how the pandemic has created havoc in almost all of them.

As an obvious consequence of lockdowns and other prohibitive measures, in 2020, the world GDP declined by about 3.3 per cent. For advanced economies, the dip is deeper (4.7 per cent) when compared to emerging economies (2.2 per cent). While in absolute term, the setback for advanced nations seems more prominent, a marginal shrinkage in growth for developing economies seems to hit harder.

According to World Bank estimates, the pandemic has pushed about 120 million into abject poverty in the low and middle income countries. The International Labour Organization (ILO) report paints a grim picture with 6.47 per cent unemployment rate and a whopping 8.3 per cent decline in labour income in 2020. ILO estimates also project loss of 90-130 million full-time jobs in developing economies during 2021.

Though assessing the impact of Covid-19 on economic activity is a five-finger exercise, it is critical to analyse if the development profile of a country has any bearing on how it impacted human lives. In a narrower sense, development profile may be synonymised to income. But with the general understanding that development is a much broader notion than income, a comparative analysis of the top 10 countries based on GDP (World Bank data for 2019 at PPP: China, US, India, Japan, Germany, Russia, France, Indonesia, UK and Brazil) and HDI (UNDP report 2020 for 2019: Norway, Switzerland, Ireland, Iceland, Germany, Sweden, Australia, Netherlands, Denmark and Singapore ) becomes an imperative call.

Results from our analysis reveal that the world’s largest 10 economies accounted for about 58 per cent of the total positive cases, whereas the total share of the top 10 HDI (Human Development Index) countries was as low as 5 per cent. Arguably. the number of positive cases may not be a suitable indicator to judge efficacy of a nation in handling the pandemic but the share of deaths in the respective groups will definitely be more revealing.

Higher casualties

Economically richer nations contribute a staggering 56 per cent casualties as compared with a meagre 4 per cent by the HDI group. Moving away from respective share of these groups to the world count and turning to number of deaths as a ratio of positive cases within the country, the average figures once again are in favour of the HDI, 1.33 against 2.43.

A valid argument here could be that the number of unfortunate casualties is directly correlated to number of positive cases — that is, more the number of positive cases, more will be the stress on the health sector and hence more fatalities. To completely eliminate the number of positive cases out of the equation, a comparison of the number of deaths per lakh individuals would be handy. Quite similar to earlier observations, on an average, it is 100:1,00,000 in the high income group compared to 63:1,00,000 for those belonging to the HDI group.

At this stage, let it be noted that this point is in no way to implicate that higher GDP leads to higher number of positive cases or deaths since correlation and causality are two different concepts. For that matter, the countries with highest vales of either of the aforementioned ratios are not the largest economies considered earlier. The crux of the argument is to stress that being rich by itself is not a virtue.

For now, with such a simple analysis, it can’t be assured that the components of HDI like life expectancy (a proxy for healthcare facilities) or education levels have contributed over and above income in reducing the impact of pandemic in those countries that have performed well in HDI. But what is clear with due certainty is that, their role is undiscernible.

So the pressing question is: What did the big economies miss? This is where, the hypothesis of number of positive patients driving the death rates loses its merit. A counter argument could be, what made the number of positive cases increase in the first place? China might get a benefit of being the first and caught unguarded. But for others this excuse does not hold water. Even the population cannot be a held responsible. As in 2020, none among the 10 largest economies has population density more than the world average. Moreover, Singapore in the HDI group, one with high population density in the world, has been the best performer.

So, where did the high-income group fail? Why are the deaths so high? The pattern of government investment in health infrastructure may provide some insights. Comparing the two groups, during the time period between 2000 and 2018, while the governments of richer countries spent on an average 4.9 per cent of their GDP on health expenditure, the ones with better HDI devoted 6.3 per cent.

Lower vaccinations

Based on the data from ‘Our World in Data’ project at Oxford University, the average number of people vaccinated in the HDI group is 52:100 as compared to 42:100 in the GDP group.

The percentages of population partially and fully vaccinated are on an average at 35 per cent and 18 per cent respectively in the top 10 HDI countries. But respective rates for its counterpart are only around 27 per cent and 15 per cent. Even with comparatively lesser income, the priorities of the countries in higher HDI domain are proven right with time.

It is time for all countries, developed as well as emerging, to fix their priorities. Obsession with growth may push a country forward economically but it still may leave a fair share of its people far behind in this journey.

The pandemic has evinced the trail of this lost story. Prudent public policies seem to have potential to script a better tale for us, which echoes in noted economist Ragner Nurkse’s comment: “If there is a place for government activity on the investment side, it is by almost general consent in the field of essential public works and services, ranging from roads and railways to telegraph and telephone systems, power plants, water works and — last but not least — schools and hospitals.”

Gopakumar is on the Economics faculty of SSSIHL, and Rajendra is on the Economics and Finance faculty of IIT Patna

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