Agent-Based Modeling Suggests We Can Modulate COVID-19 Spread — Part One

This article was first published on SingularityNET - Medium
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Agent-Based Modeling Suggests We Can Modulate COVID-19 Spread By Encouraging Localized Social Interactions — Part One

In the 5 months since organizing the COVID-19 Simulation Summit, SingularityNET and Singularity Studio have been gradually evolving our software framework for Agent-Based Modeling of the pandemic and leveraging it to run simulations of COVID-19 spread in various contexts. In this post, we describe some of the early results we’ve obtained in this quest, and some of the policy directions they tentatively suggest.

A sequel post gives more in-depth supplementary information, for those who want to dig into some of the simulation results we’ve been looking at here in the SingularityNET research lab.

A more informal take on these ideas and results can be found in my talk in the Medical Applications stream of the D.OS (Decentralized OS Summit) event that SingularityNET and Cardano co-organized on November 9, 2020.

As a number of the talks at the COVID-19 Simulation Summit pointed out, the agent-based simulation paradigm allows a finer-grained sort of modelling than is displayed in the simplistic epidemiological models of COVID-19 spreading dynamics that are driving current policy decisions. Most critically, the commonly used simplistic models fail to account for the different behaviour patterns of different classes of people — that is, they leave out the social element, which is accounted for directly in the agent-based approach in which a region (or the world as a whole) is modelled as a specific geometry occupied by interacting autonomous agents with a diversity of specific behaviour patterns.

Our SingularityNET Agent-Based Modeling (ABM) framework can be used to construct multiple types of simulation models, including fine-grained models of particular cities, states or nations, or more universal models of generic simulated environments intended to highlight general properties of COVID-19 dynamics in various sorts of real-world situations.

The simulation results we’ll describe here ...

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