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Tuesday, September 22, 2020

India can prevent 200,000 Covid-19 deaths by December, suggest new computer modelling of pandemic

Even to reach the death count of 2.91 lakh, close to 2,500 deaths would have to happen every day in the 94 days to December 1

Written by Anuradha Mascarenhas | Pune | Updated: August 29, 2020 3:37:55 pm
Authorities sanitize an ambulance in Pune. (Express Photo: Arul Horizon)

A new computer modelling of the COVID-19 pandemic in India shows that while the disease will continue to pose a major public health threat, it may be possible to prevent more than 200,000 deaths by December 1, 2020, with more widespread adoption of masks and data-driven physical distancing measures in the most affected states.

The modelling, produced by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, suggests that India’s death count could go up to 2.9 lakh (291,145) by the start of December. India has seen more than 62,500 coronavirus deaths till now. This scenario assumes that people would continue to follow social distancing, the usage of face masks would be near-universal (95 per cent), and that states would re-impose lockdowns if the daily death rate exceeded 8 per million. This threshold is based on when governments worldwide have typically imposed lockdowns to stop Covid19 transmission.

But if the lockdown restrictions are removed and face-mask usage remains at current levels, then the death count could go much higher, almost till 4.92 lakh, by December 1.

However, even to reach the death count of 2.91 lakh, close to 2,500 deaths would have to happen every day in the 94 days to December 1. India is currently recording just over 1,000 deaths every day, some days much less. Only 45 deaths have happened per million population, which is way below the current world average of 108. Similarly, the case fatality ratio, calculated as deaths out of the total number of infections, is down to 1.81 per cent, again much below the world average of 3.3 per cent.

Long-period projections have a lot of uncertainty built-in, especially in situations that are continuously evolving. Some dire predictions about the number of infections and deaths in India at the start of the outbreak have not turned out to be very accurate.

However, India does continue to be one of the most active countries of the epidemic right now.

“India’s epidemic is far from over, as a large proportion of the population is still susceptible,” IHME Director Dr. Christopher Murray told The Indian Express on Saturday morning. “In fact, our modelling shows there is a wide range of potential outcomes, depending on the actions that governments and individuals take today, tomorrow, and into the near future. Mask-wearing and social distancing are crucial to mitigate the spread of the virus.”

“There is an opportunity to further limit the toll of COVID-19 in India and highlights the critical need for people to comply with face mask use, social distancing, and other COVID-19 prevention guidelines as advised by public health authorities,” Dr Murray said.

Forecasts show opportunity to prevent more than 200,000 deaths by December 1.

India’s response to COVID-19 has produced some significant successes that highlight the opportunity to limit the pandemic’s toll in the country. In some urban areas, including Delhi, containment measures that include intensive contact tracing, widespread testing, mask-wearing, and social distancing mandates have helped reduce the spread of the virus. In addition, COVID-19 testing in India has scaled up rapidly.

“India is at a tipping point,” Murray said. “If hospitals in those states are unable to accommodate everyone needing COVID-19 care, the result will be more deaths and greater long-term harm to state and local economies.”

IHME’s projections for India are based on an epidemiological model that includes data on cases, deaths, and antibody prevalence, as well as state-specific COVID-19 testing rates, mobility, social distancing mandates, mask use, population density and age structure, and pneumonia seasonality, which shows a strong correlation with the trajectory of COVID-19.

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