Adaptive Control of COVID-19 Outbreaks in India: Local, Gradual, and Trigger-based Exit Paths from Lockdown

Abstract

Managing the outbreak of COVID-19 in India constitutes an unprecedented health emergency in one of the largest and most diverse nations in the world. On May 4, 2020, India started the process of releasing its population from a national lockdown during which extreme social distancing was implemented. We describe and simulate an adaptive control approach to exit this situation, while maintaining the epidemic under control. Adaptive control is a flexible countercyclical policy approach, whereby different areas release from lockdown in potentially different gradual ways, dependent on the local progression of the disease. Because of these features, adaptive control requires the ability to decrease or increase social distancing in response to observed and projected dynamics of the disease outbreak. We show via simulation of a stochastic Susceptible-Infected-Recovered (SIR) model and of a synthetic intervention (SI) model that adaptive control performs at least as well as immediate and full release from lockdown starting May 4 and as full release from lockdown after a month (i.e., after May 31). The key insight is that adaptive response provides the option to increase or decrease socioeconomic activity depending on how it affects disease progression and this freedom allows it to do at least as well as most other policy alternatives. We also discuss the central challenge to any nuanced release policy, including adaptive control, specifically learning how specific policies translate into changes in contact rates and thus COVID-19's reproductive rate in real time.

Seroprevalence of SARS-CoV-2 in slums and non-slums of Mumbai, India, during June 29-July 19, 2020

“…Our findings also suggest that seroprevalence is more than 3 times higher in slums than non-slum areas in the same ward. The difference highlights the importance of geographic specificity in modeling 13 and modeling variation in contact rates 14 . The implied variation in reproductive rates also has implications for the level of herd immunity city-wide 14 .…”

Mitigating Covid-19 outbreaks in workplaces and schools by hybrid telecommuting

“…Such NPIs and organizational adaptations have to balance the competing goals of limiting contagion and maintaining an adequate level of social and economic activity. Assessing the performance of containment and mitigation strategies with respect to the propagation of the epidemic is therefore critical to making the right policy choices and has attracted an immense research effort from all disciplines, from medical science to economics, engineering, and social, computer and statistical sciences [19, 24, 10, 6, 8, 14].…”

Optimal lockdown strategies for SARS-CoV2 mitigation— an Indian perspective

“…However, early lockdowns make a second wave of infection inevitable because the number of susceptible individuals in the population after the lockdown remains comparable to the number of susceptible individuals at the start of the pandemic, far from the HIT of the system. In this scenario, infections climb again once the lockdown is lifted [Rachel, 2020, Malani et al, 2020]. Therefore, such lockdowns do not lead to good long-term outcomes as the second wave of the infection easily takes the number of active cases past the hospitalization threshold (HT).…”