How covid-19 compares against other killer diseases in India

Last Thursday, covid-19 became India’s most deadly infectious disease, with the exception of tuberculosis. In its National Health Profile (NHP) statistics for 2019, the government listed eleven communicable diseases with the highest case fatality rates (over 1%). In just four months, officially reported deaths from covid-19 surpassed the annual count of officially reported deaths from H1N1, which was until now the infectious disease from this list that resulted in the most deaths in 2018 (the most recent year for which comparable data is available for all eleven diseases).

It can sometimes be unclear where the novel coronavirus fits into India’s disease landscape. Is it truly as extraordinary as is being made out, or is it just that it is new? India’s data on death and disease - both official and scholarly - helps place the epidemic in its proper perspective: genuinely unique among infectious diseases, in a country that was moving away from such infections.

While data on all the deadly diseases are not yet available for 2019, there were 28,798 cases of H1N1 in 2019 and 1218 deaths, according to the National Centre for Disease Control, a number that covid-19 surpassed on Saturday.

The NHP data on communicable diseases with a high fatality rate, however, has an important omission - tuberculosis (TB). Official statistics suggest there were 1.7 million cases of TB in 2017, and it killed 56,277 people, numbers regarded by experts to be gross underestimates. These numbers suggest that TB had a case fatality rate of 3.2% in 2017, meaning it was comparably fatal to covid-19. Where it differs is in the number of cases (multiple times more than covid-19 cases detected so far in the country) and in its treatment (TB has a known cure and treatment regimen unlike covid-19).

India’s official health statistics, including the NHP numbers cited above have major limitations, and hence must be interpreted with care. Statistics from the government’s National Health Profile (2019) are based largely on government institutions, and capture very limited data from private institutions. Hence, the NHP figures are gross underestimates of the real extent of disease and death in a country where more people visit private healthcare providers than public ones.

The NHP estimates 194 deaths from malaria in 2017, while the Global Burden of Disease (GBD) initiative, which uses multiple sources, estimated 50,000 deaths for the same year. Estimates for TB incidence are ten times the official numbers.

Data for the novel coronavirus currently comes exclusively from the government, making official statistics on other diseases the most useful dataset for comparison. However, the GBD numbers provide better context for India’s disease burden. This data suggests three important lessons for India’s covid-19 response.

One, the data shows that India’s infectious disease burden remains high. The GBD data shows that while the top two causes of mortality in Indians are now non-communicable diseases, three of the five biggest causes of mortality are still infectious diseases. Between them, the top five diseases kill over 11,000 Indians every day.

While the data does not diminish the scale of the coronavirus epidemic in India, it does show that a return to normal for healthcare systems is vital for broader public health. In the 40 days since the first novel coronavirus case was detected in India, there would have been nearly 50,000 deaths in India from tuberculosis alone.

Secondly, the data shows that upper respiratory infections are the most common ailment among Indians, indicating that covid-like symptoms are common. In epidemiology, “incidence” refers to the number of new instances of a disease during a fixed time period. The GBD data shows that on average, every Indian experienced nearly two bouts of upper respiratory infections in the 2017 calendar year, and every day over 7 million new cases of upper respiratory infections presented themselves. Given that India’s current testing strategy extends to people with “mild symptoms” including a cough and/or runny nose, India’s testing authorities will have their work cut out for them if they follow these strictly.

Lastly, the GBD data points to the dangers of trying to fill in the blanks of India’s poor data on deaths. Since only 22% of registered deaths in India are medically certified, and even those diagnoses are more often wrong than right, some analysts have suggested using all-cause mortality to estimate the “real” number of deaths due to Covid-19. What this would mean in practical terms is comparing deaths in an area or country with those in previous months or years to pick up on any unexplained spike over the last few months. However, in a country such as India, where road accidents are among the biggest killers (according to GBD data) this could be a flawed strategy.

The heavy burden of deaths from road accidents in India means that all-cause mortality during a lockdown will likely fall.

As India approaches peak Covid-19 incidence, lessons from its disease burden history can help guide public health strategy better.

Rukmini S. is a Chennai-based journalist.