A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India

Adiga, A and Hurt, B and Kaur, G and Lewis, B and Marathe, M and Porebski, P and Venkatramanan, S and Dukkipati, A and Gracious, T and Gupta, S and Rathod, N and Sundaresan, R and Yasodharan, S and Bhimala, KR and Mudkavi, V and Patra, GK and Athreya, S (2023) A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India. In: 2023 Winter Simulation Conference, 10 December 2023 through 13 December 2023, San Antonio, pp. 994-1005.

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Abstract

During the COVID-19 pandemic, India has seen some of the highest number of cases and deaths. Quality of data, continuously changing policy, and public health response made forecasting extremely difficult. Given the challenges in real-time forecasting, several countries had started a multi-team collaborative effort. Inspired by these works, academic partners from India and the United States setup a repository for aggregating India-specific forecasts from multiple teams. In this paper, we describe the effort and the challenges in setting up the repository. We discuss the development of simulations of compartmental models to model specific waves of the pandemic and show that the simulation model designed specifically for the Omicron wave was able to predict the onset and peak sizes accurately. We employed a median-based ensemble model to aggregate the individual forecasts. We observed that median-based ensemble was relatively stable compared to the constituent models and was one of better performing models. © 2023 IEEE.

Item Type:	Conference Paper
Publication:	Proceedings - Winter Simulation Conference
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	03 Jul 2024 07:37
Last Modified:	03 Jul 2024 07:37
URI:	http://eprints.iisc.ac.in/id/eprint/84534

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