# Coronavirus lockdown | Mathematical model estimates staggered resumption may cut peak hospitalisations by 50%

Stitch in time: Employees working at an apparel manufacturing unit during the lockdown, in Noida on Wednesday.

A staggered resumption of work following the end of the nationwide lockdown may reduce peak hospitalisations due to COVID-19 to almost 50% as compared with a total resumption that would force authorities to impose intermittent lockdowns to contain surges in the incidence of the disease, a model built by a group of scientists estimates.

With the third phase of the lockdown set to end on May 17, Indians are set to resume work once the lockdown is lifted. Given that the lockdown has clamped down on the number of infections and hospitalisations due to COVID-19, resuming full-fledged work once the lockdown is lifted would entail a significant increase in the interaction in the population and an ensuing rise in infections. The group of nine Indian scientists therefore modelled the different scenarios to see how best to play off the benefits of a lockdown against the economic need of the population of a mid-sized Indian city and the likely resultant growth in the infection rate of an active workforce. The best solution, they suggest, would be to send only 33% of the workforce to work at a time, in a staggered manner.

## Lockdown scenarios

The nine scientists from across India who are part of the Indian Scientists’ Response to COVID-19 initiative have built up a model of the disease’s progression that can estimate how well different lockdown scenarios work.

They find that the best way to return a city’s population to work after the lockdown would be to have 33% of workers in any organisation work for say, two days. A second 33% should then take over on the third day, and the third set replaces the second on the fifth day. This cycle, which they term a staggered workforce — or a periodic asynchronous lockdown — is preferable to a scenario where 100% of the workforce resumes work simultaneously for some days before a flare up in incidence of the disease forces another full lockdown and so on — or in other words a periodic synchronous lockdown. In their estimation, the former method (staggered workforce) reduces the peak number of hospitalisations in the workforce by almost 50% compared with the latter (synchronous lockdown). This is of course in combination with testing-quarantining.

“Large-scale testing, contact tracing and quarantining must happen in conjunction with the asynchronous periodic lockdown, to keep the infected and hospitalisation numbers in check — this is well demonstrated via our model calculations,” Pinaki Chaudhuri of The Institute of Mathematical Sciences, Chennai, one of the scientists who developed the model, wrote in an e-mail to The Hindu.

“In comparison to periodic synchronous lockdowns, there can be a 50% reduction in the peak number of hospitalisations for periodic asynchronous lockdowns. The hospitalisations for the synchronous case also continue for a longer period compared to the asynchronous case,” Dr. Chaudhuri added.

## Complex model

The standard model used for disease progression modelling is called the SEIR (Susceptible, Exposed, Infected, Recovered) model. The model developed by these scientists is more complex and takes into account particular features of COVID-19. “The standard SEIR model does not take into account the particularities of the specific disease (e.g. symptomatic or asymptomatic patients for COVID-19 or what fraction needs hospitalisation and so on) and the time scale of disease progression in each case,” explained Vishwesha Guttal from the Indian Institute of Science, Bengaluru. “Considering all these aspects, we have a nine-compartmental model as against four compartments in the standard SEIR model.”

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