What’s still saving Saarc countries from coronavirus pandemic?

When the world's average death per million population from coronavirus is 26.1, the globe's most densely populated Saarc countries are somehow still escaping the wrath of the virus with very low mortality rates. 

Whereas coronavirus deaths per million is close to 600 in Belgium, the rate is 1 or below in Sri Lanka, India, Bangladesh, Pakistan and Afghanistan. No death has been reported in the Maldives, Bhutan and Nepal so far.

In terms of death rate per 1,000 infections, again the sub-continental patients are doing better than those in European nations. Bangladesh has 28 deaths and the other Saarc nations have similar figures. This figure is one-fourth to one-fifth lower than the hard-hit European nations.

Experts attribute low mortality in this region mainly to the younger population compared to the European nations. Population below the age of 24 represent half of the total in Bangladesh or India. But European countries are high in older population, who may already be suffering from other diseases – making them more vulnerable to coronavirus infections.

All the Saarc countries reported deaths from coronavirus in March. India reported its first death on March 12, Bangladesh on March 18 and Pakistan, Afghanistan and Sri Lanka later that month.

To contain the virus' spread, all these countries enforced lockdowns or partial lockdowns from late March and these were being extended up to early May or the second week of May.

All the while the number of infections and deaths in the regions continued to spiral up just like the rest of the world. By mid-April, the world witnessed the spread and death from the coronavirus pandemic in geometric rate. But most of these increases were taking place in the USA and Europe. In contrast, the number of cases in the Saarc region marked a slower growth.

But the Saarc countries like Bangladesh or India have not been able to carry out enough tests to prove that the coronavirus spread is really slow here. Bangladesh has so far conducted a paltry 262 tests per million people – which is nothing compared to the European, Middle Eastern or American testing numbers.

Among the Saarc nations, Bhutan has conducted the highest number of tests per million people (11,603) followed by the Maldives. Only Afghanistan falls behind Bangladesh in terms of testing. 

This means that there may be many more unreported coronavirus deaths and therefore the official data may not give us the exact picture of the depth of the pandemic in the region.

But if we can add the overall number of deaths in the sub-continental countries and the types of mortality, we can have the actual picture. Due to the lockdowns, the number of accidental deaths or death from pollution in the region may have declined; but still, getting the actual data and analysing it would be very complicated.

Four explanations for slow spread in India

In explaining why India has so few Covid-19 cases, three scholars wrote in Quartz India on April 16 that there were four possible explanations.

Anup Malani, Arpit Gupta and Reuben Abraham noted that the epidemic might have struck later than in other countries. Since epidemics have exponential growth at the start, a small delay can have massive effects on the number of cases.

They also noted that India's lockdown might have successfully suppressed the epidemic. 

Thirdly, India had not been able to test enough to count all cases and deaths. Without sufficient testing, many deaths may not be labelled with Covid-19 for official statistics, leading to an underestimation of the severity of the crisis.

And fourthly, India might have protective characteristics against Covid-19. Researchers have proposed that the low share of elderly in the population, the high temperatures and humidity in India, widespread BCG vaccination for tuberculosis, or resistance to malaria have helped India escape the brunt of the pandemic.

Anup Malani is a professor at the University of Chicago Law School and Pritzker School of Medicine, Arpit Gupta an assistant professor of finance at the NYU Stern School of Business and Reuben Abraham the CEO of the IDFC Foundation and IDFC Institute in Mumbai.

Hotter temperature slows Covid 19?

Anup Malani et al said that hotter temperatures in India may slow the virus. 

"There is some evidence consistent with this theory. Countries with latitudes between 30-50 degrees above or below the equator, and average temperatures between 5 and 11 degrees Celsius have, thus far, borne a higher burden from Covid. However, some preliminary research has suggested that India may face higher transmission rates during the monsoon, which is India's flu season. Humidity may also play a role; studies have found varying results on its importance as a factor. In addition, a brand new study at Harvard has suggested that Covid-19 may not go away in warm weather as colds do, because significant parts of the population remain vulnerable to the virus. The weather alone is insufficient to protect India."

In an interview with Business Standard of India on April 19, professor and chair of biostatistics at the University of Michigan Bhramar Mukherjee noted that there was some suggestive evidence of declining incidence with temperature, but it's not as strong as to say that something is going to really rescue us. 

"This summer belt is confounded with so many other things. There are countries with different vaccinations, so there have been several hypotheses about each structure of a community. The use of the BCG or the anti-malarial vaccines is also correlated with temperature," she said. 

Mukherjee is leading a team of researchers that is using epidemiological modelling to do a situational assessment of the coronavirus crisis in India.

BCG vaccinations and malarial drugs

Anup Malani et al held that other explanations centre on universal BCG vaccination in India, or domestic hydroxychloroquine use to combat malaria. While it is true, for instance, that countries with BCG vaccination appear so far to have less transmission, these countries are also warmer, have younger populations, and – because they are poorer – likely tested late.