Saturday, Oct 01, 2022

India’s Covid-19 Death Rate Could Be Higher Than The US: Govt Advisory Firm

Co-founder and CEO of Sapio Analytics, a government advisory firm, Ashwin Srivastava tells Outlook that India's method of calculating Covid-19 mortality rate is erratic.

Hospital staff carry the body of a person who died of COVID-19 to a morgue in Mumbai. PTI Photo

Sapio Analytics is a government advisory firm, actively working with various government bodies in the fight against Covid-19. Dr Michael Levitt, winner of the Nobel Prize for Chemistry in 2013, who teaches structural biology at the Stanford University and Colonel H.R. Naidu Gade, an Indian Army veteran are a part of Sapio Umbrella, a unit of Sapio Analytics.

Sapio Analytics co-founder and CEO Ashwin Srivastava says the claims of Ministry of Health and Family Welfare about India's low mortality rate of Covid-19 is misleading in an interview to Jeevan Prakash Sharma. Excerpts:

Q1: The Ministry of Health and Family Welfare has been claiming that the mortality rate of Covid-19 positive patients in India at 2.86 per cent is the lowest in the world. Is that correct?

A: Mortality rate is one of the factors that we are tracking to analyse the impact of the virus and its purpose should be to find expected deaths out of a given pool of cases. The government is adopting a wrong method to calculate the case fatality. A patient who is being admitted today may die after ten or fifteen or more days later than that. But the current method is counting all cases together and then finding out the death rate. Such a method shows a low mortality rate because the denominator consists of cases that should not be included in the pool.

Q2: On May 27, the ministry said the mortality rate was 2.86 per cent? How did it arrive at this rate?

A: On May 27, the total number of Corona cases - including active (83004), recovered (64425), death (4337) and migrated (1) - was 151767. The health ministry calculated the percentage of death (4337) against total Corona cases (151767). The calculation came over 2.857 per cent, which was rounded up to 2.86.

Let me explain the flaw in the method in a simple way with a hypothetical instance. For example, 100 cases are coming every day for one week. So in a week, the total case is 700. Now, God forbid, but presume that all 100 patients die on the very first day. So the death rate will be 100 per cent. But if we calculate in respect of all 700 cases then the death rate will be only 14.29 per cent. If there is a disease which takes at least 7 days to lead to death, the data from the last 6 days should not be taken in the pool.

Q3: So what’s the right way to process the data and arrive at a near to accurate fatality rate?

A: In order to get a proper understanding of the actual mortality rate, it's important to do the right mapping of the number of cases to the number of deaths. Assuming the virus remains active for 21 days, leading either to death or recovery, today's fatality or mortality rate would be the number of deaths today divided by the average of all positive cases in the last 21 days.

Q4: So how would you calculate the mortality rate on, say, May 27?

A: In the past 21 days, from May 7 to May 27, total Covid-19 cases were 78956. Now divide this by 21 to get an average number of corona positive cases. So 78956 divided by 21 gives 3760. Now on May 27, the total deaths were 190. So the calculation is X % of 3760 = 190. So, X = 5.0%. This gives a clearer idea of how the mortality rate is changing. Not taking the basis of the 21-day average may give skewed data as the cases that die today will not be from the cases that are detected today.

According to this calculation, on the morning of May 28, while India’s death rate is 5.0%, the US is 6.8%, and the global death rate is 7.6%. It shows the difference between India and the US is 1.8% whereas India and global is 2.6%.

Q5: But still India is 1.8% lower than the US and 2.6% than global average.

A: Yes, but if we take into consideration low medical death certificate numbers, this difference becomes negligible and India's current mortality rate becomes almost the same as that of the USA. In India, traditionally only in 20 per cent death cases medical certificates are issued. It means that the medical reason for death in 80 per cent cases is not known. That’s not the case with the USA where a medical certificate is 100 per cent. Even if we are able to significantly improve this number for COVID-19 cases, a margin of error of around 50% of the numbers seems quite feasible. Keeping this margin of error in mind, India's current mortality rate is almost the same as that of the USA.

Low mortality rate should not be seen as an achievement. The correct mortality rate only helps us plan the situation better. We can be ready with the optimum medical resources if we accept that India is having a similar mortality rate as the USA despite the difference in age demographics.  

Q6: There are allegations that death cases have been under-reported in West Bengal and Madhya Pradesh. It may be true of other states too. So if we take all these factors into consideration, do you think our death rate will go higher than the US?

A: It’s possible, if we take other potential inefficiencies into consideration, as being experienced by our on-ground feedback reports. Hence, it's important that we make the right plans on improving the distribution of healthcare resources based on predictions using the right data points. India needs to work on its healthcare resource planning on the highest priority and we are providing pro bono support to governments in doing so.

Q7: When you look at the data culture in India especially in the government departments, do you think we are good at generating data from the ground zero and people working at the ground have good data sense?

A: It varies across locations. There are certain local bodies and state governments, who we work with, where there is a strong focus on data. Government of Telangana, local bodies of Pimpri Chinchwad and Kalyan Dombivali in Maharashtra, Union Territory of Daman, Diu and DNH, are some examples of the places where there is a deep understanding and appreciation of data that has been fed from the top.