Delaying COVID-19 peak was important, says professor M Vidyasagar as India bends the curve

COVID-19 has prompted many mathematical and statistical models to map the spread of the pandemic. Some of these models look at the spread of the infection over time at the local and global levels. In India, the latest and fittest of these models is a recent study commissioned by the Department of Science and Technology and carried out by a panel of seven expert scientists from some of the country's best academic institutions.

The "supermodel", as the panel's report referred to it, is based on various parameters such as the timing of the lockdown, alternative lockdown scenarios, impact of migrant workers returning to their homes, and the future course of the pandemic including the impact of not following safety protocols.

Using the model, the expert panel predicted that India has crossed its peak of new cases in September, and could see minimal cases by February if the current trend continues and the festival season doesn't see an anticipated surge in transmission.

Chaired by professor M Vidyasagar (IIT Hyderabad), the panel also includes professor Manindra Agrawal (IIT Kanpur), professor Biman Bagchi (IISc), professor Arup Bose (ISI Kolkata), professor Gagandeep Kang (CMC Vellore), professor Sankar K Pal (ISI Kolkata) and Lt Gen Madhuri Kanitkar (HQ IDS MoD).

Based on the model, many predictions were made of how the COVID-19 pandemic might progress in India. Some of them included alternative scenarios of COVID-19 spread in the past, depending on when the lockdown began. Others were likely outcomes in the future, based on the current trend, relaxation of lockdown measures, and more stringent measures. All these predictions were made using "robust data" publicly available at the COVID-19 India database.

India's 'supermodel': Some conclusions

Past

1. Delaying the initial lockdown (starting 25 March) would have made the pandemic more difficult to manage
2. The actual lockdown saw over 10 lakh active symptomatic cases peaking around end of September, and one lakh recorded COVID-linked deaths. The No lockdown scenario predicts over 140 lakh peak active (symptomatic) cases by June, and 26 lakh deaths by end August.
3. A lockdown from 1 Apr onwards predicted 40-50 lakh peak active cases by June and 7-10 lakh deaths by end of August.
4. The mass exodus of reverse migration of labourers from Punjab and Haryana in May-June did not significantly alter overall outcomes at the state and national levels

Future

1. More people could contract COVID-19 during the upcoming festival and winter seasons
2. Relaxing the lockdown/other protective measures currently in place can result in a steep rise – up to 26 lakh infections within a month
3. District and higher level lockdowns not much effective now
4. All activities can be resumed provided proper safety protocols continue to be followed
5. If everyone follows these protocols, the pandemic can be controlled by early next year with minimal active symptomatic infections by February-end

'Delaying the peak was important'

In an email interview, professor Vidyasagar, chairman of the DST-appointed COVID-19 panel spoke to Firstpost about the various scenarios that were predicted by the COVID-19 "supermodel" and what lies ahead for the country in the fight against the novel coronavirus. Edited excerpts from the interview:

The panel concluded in its report that the timing of the actual lockdown helped “flatten the curve”. Didn’t the change in trend come very recently, in September, after many surges in cases before it?

Pushing out the peak of infections several months into the future, from end-May or early June to mid-September, is an important part of flattening the curve.

File image of professor professor M Vidyasagar, chairmain of chairman of the DST-appointed COVID-19 panel. Wikimedia Commons

So, can it be said that the worst of COVID-19 transmission is behind us? 

We have emphasised repeatedly that the worst is behind us only if people continue to observe the safety protocols.

Why was an earlier date – 14 Feb, for example – not included as an alternative timeline to assess the effectiveness of the actual lockdown? 

In February, the number of cases were tiny. No meaningful modelling could be done with such small numbers.

Was there a "best case" scenario model for reduced healthcare burden/effective pandemic management? 

Staying the course would lead to a steady reduction in cases, while any departure in terms of slackening safety protocols would lead to a slower reduction in cases.

Will the panel be submitting any more public reports (observations/suggestions/recommendations) towards India's pandemic strategy going forward?

As and when needed, yes.

Any interesting inferences from the effectiveness of lockdown measures so far?

The inferences about the impact of the lockdown are quite interesting by themselves, we believe.

Can we expect a similar assessment of vaccine distribution preparedness?

Vaccine development was not a part of our Terms of Reference.

The SAIR model

One of the ways the spread of an infection in a population can be modelled, uses the S-A-I-R (Susceptible-Asymptomatic-Infected-Removed) model. It breaks down the population into broad groups of individuals, depending on their relationship with the infection – and importantly, how that relationship changes over time.

The supermodel for India was made by tweaking this SAIR model, and dividing the population into four similar groups:

• Susceptible – people who are not yet infected,
• Asymptomatic – people who are infected, but with no or little symptoms,
• Infected – people who are infected with significant symptoms, and infectious,
• Removed – people who were infected, but are now recovered or deceased

The number of individuals in each of these categories changes as a pandemic progresses. The SAIR model tries to capture the change in infection rate over time, considering the changes to the number of people in the various different groups.

The number of individuals in each of these categories changes as a pandemic progresses. The SAIR model tries to capture the change in infection rate over time, considering the changes to the number of people in the different groups.

Impact of festivities on COVID-19 trajectory<h,2>
The committee’s report also looks into past evidence of COVID-19 spread in large gatherings, especially keeping in the mind the ongoing festive season. Citing the example of Kerala during the Onam celebrations between 22 August and 2 September 2020, the report states how this period was followed by a sharp rise in cases from 8 September in the state.

As per the report, the probability of infection soared by approximately 32 percent, and the effectiveness of medical response dropped by approximately 22 percent for Kerala in September. In other words, the likelihood of people getting infected increased, and the likelihood of a patient getting treated decreases.

India is in the middle of Navratri celebrations already, with Durga Puja just around the corner, and Diwali coming up in November. Kerala may serve as an example of why festivities need to be subdued, and why the government is perfectly justified in reiterating guidelines for physical distancing and other COVID-19 precautions.

For more information on the COVID-19 supermodel for India, you can head to the official website, Professor Vidyasagar's slides from his media presentation on Tuesday, and the complete report of the panel's findings.