How might the disease evolve once the restrictions are lifted? What would a post-lockdown scenario look like? To answer these questions, researchers at the Indian Institute of Science (IISc) and Tata Institute of Fundamental Research (TIFR) have carried out city-scale simulation experiments and modelled the outcomes of post-lockdown scenarios.
Their predictions, outlined in a working paper, could provide useful insights for public health officials and policymakers on decisions related to easing of restrictions. According to the researchers, unless we continue to aggressively trace and isolate cases, and prevent the influx of new infections, there is likely to be a second wave of infections and the public health threat will continue to persist.
The team simulated the infection spread in Bengaluru and Mumbai using an agent-based model, which builds a fine-grained replica of a city and mimics various interaction spaces such as households, schools and workplaces.
“If there are 10 million people in Bengaluru, the city’s model also has that many individuals,” says Rajesh Sundaresan, Professor at the Department of Electrical Communication Engineering, IISc, and the corresponding author of the working paper. The model also takes into account population densities, age distribution, household size distribution, commute distances and several other parameters.
In their model, the researchers ‘seeded’ infections in the simulated cities, and tested how the epidemic would spread under different scenarios when restrictions are phased out. For example, one scenario is a return to normal activity on May 4, but with ‘case isolation’ continuing. Another considers an ‘odd-even’ strategy between April 20 and May 3, where half the workforce returns to their offices, along with other restrictions in place. Yet another scenario looks at a complete lockdown for an indefinite period. In all of these, the researchers assumed that cases would continue to be isolated with 90 per cent compliance.
The model forecasts that in a city like Bengaluru, if the lockdown was lifted on 20 April 2020, and normal activity resumes, the number of direct COVID-19 fatalities would have increased to levels under a no intervention scenario, but with some delay.
Similarly, the model also forecasts an increase in COVID-19 fatalities if the lockdown was lifted from 20 April 2020 to 3 May 2020 in the following phases: case isolation, plus home quarantine, plus social distancing of those 65 years and older, plus the closure of schools and colleges, and thereafter normal activity resumes but with case isolation.
On the other hand, if the lockdown were to continue indefinitely, the number of direct COVID-19 fatalities in Bengaluru will likely be much smaller than in the no intervention scenario, the model predicts.
“The agent-based model gives us enough handle to study a targeted intervention, say what if we just close schools and colleges alone. Or if we have only one-half of the workplaces open,” says Sundaresan. “It also gives us a lot more flexibility to test out new interventions before we actually implement them.”
The researchers through the IISc release caution, however, that their study only looks at the public health outcomes of interventions and their relaxations, and does not consider economic or ethical issues.
It does not also take into account the aggressive contact tracing, testing, and isolation which can change the course of the epidemic. Nor does it account for spontaneous changes in people’s behaviour. The case progression in hospitals is also based on the available literature, which is still evolving.
The researchers add another caveat about the report, which has been prepared to help scientists and public health officials understand the effectiveness of COVID-19 interventions: it should not be used for medical diagnostic, prognostic or treatment purposes or for guidance on personal travel plans.