City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic

08/11/2020

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We highlight the usefulness of city-scale agent-based simulators in studying various non-pharmaceutical interventions to manage an evolving pandemic. We ground our studies in the context of the COVID-19 pandemic and demonstrate the power of the simulator via several exploratory case studies in two metropolises, Bengaluru and Mumbai. Such tools become common-place in any city administration's tool kit in our march towards digital health.

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City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic

City-scale Simulation of Covid-19 Pandemic and Intervention Policies using Agent-based Modelling

The Effects of Stringent Interventions for Coronavirus Pandemic

DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks

Deep Learning-based Spatially Explicit Emulation of an Agent-Based Simulator for Pandemic in a City

BESSIE: A Behavior and Epidemic Simulator for Use With Synthetic Populations

Collaborative City Digital Twin For Covid-19 Pandemic: A Federated Learning Solution

Neural Network Augmented Compartmental Pandemic Models

City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic

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