The IISc-TIFR agent-based city simulator for the study of COVID-19 spread

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Over the last few months, since the spread of the COVID-19 pandemic, several epidemiological models have been proposed to understand the spread of the infection in the population. In this talk, we will provide an overview of the agent-based models and compare their pros-and-cons against other models. We will argue that agent-based models let one capture detailed interactions at a granular level and can thus be useful in comparing the impact of various non-pharmaceutical interventions against each other. We will then present the IISc-TIFR agent-based city simulator developed for studying the spread of the COVID-19 infection in the cities of Mumbai and Bengaluru under various “unlocking” strategies. We will conclude with a presentation of the simulator’s estimates for the infection-spread in Mumbai under different lockdown-relaxation scenarios; containment strategies, phased opening of workplaces, gradual resumption of train services, importance of compliance.

Prahladh Harsha (TIFR)

Prahladh Harsha is an Associate Professor at the School of Technology and Computer Science (STCS) at the Tata Institute of Fundamental Research (TIFR), Mumbai. He obtained his Bachelors degree from IIT Madras in 1998 and his Ph.D. from MIT in 2004. After MIT, he was a post-doctoral researcher at Microsoft Research, Silicon Valley, a research assistant professor at the Toyota Technological Institute at Chicago, (2005), a visiting scientist at the University of Texas at Austin and at the Technion, Israel Institute of Technology and has been at the faculty at TIFR since Dec 2009.