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    Department of Systems Engineering and Engineering Management

                       The Chinese University of Hong Kong

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Date: Thursday, June 27, 2:00 pm – 3:00 pm

Venue: ERB 513, The Chinese University of Hong Kong

Title: Shift, Scale and Restart Smaller Country Level Models to Estimate Larger Ones: Agent-based Simulators for Covid Modelling

Speaker:  Prof Sandeep Juneja, Ashoka University

Abstract:

Agent-based simulators are a popular epidemiological modelling tool to study the impact of various non-pharmaceutical interventions in managing an evolving pandemic. They provide the flexibility to accurately model a heterogeneous population with time and location varying, person specific interactions. To accurately model detailed behaviour, typically each person is separately modelled. This however, may make computational time prohibitive when the region population is large and when time horizons involved are large.  We observe that simply considering a smaller aggregate model and scaling up the output leads to inaccuracies. In this talk we primarily focus on the COVID-19 pandemic and dig deeper into the underlying probabilistic structure of an associated agent based simulator (ABS) to arrive at modifications that allow smaller models to give accurate statistics for larger models. We exploit the observations that in the initial disease spread phase, the starting infections behave like a branching process.  Further, later once enough people have been infected, the infected population closely follows its mean field approximation. We build upon these insights to develop a shifted, scaled and restart version of the simulator that accurately evaluates the ABS's performance using a much smaller model while essentially eliminating the bias that otherwise arises from smaller models. We also discuss our ongoing work on generalising these ideas to multi-region, country level models where inter-region migration becomes an important transmission feature.

Biography:

Sandeep Juneja is a professor of computer science and the director for Centre for Data, Learning and Decision Sciences at Ashoka University. He is on leave from TIFR where he is a senior professor at the School of Technology and Computer Science (STCS). Formerly, he was a Dean of STCS. His research interests lie in applied probability including in sequential learning, mathematical finance, Monte Carlo methods, and game theoretic analysis of queues. Lately, he has been involved in epidemiological modelling as well as in use of machine learning techniques for monsoon weather modelling in India. He is currently the area editor for Operations Research in simulation. Earlier he has been on editorial boards of Stochastic Systems, Mathematics of Operations Research, Management Science and ACM TOMACS.

Everyone is welcome to attend the talk!

SEEM-5202 Website: http://seminar.se.cuhk.edu.hk

Email: seem5202@se.cuhk.edu.hk