A Deterministic Pathogen Transmission Model Based on High-Fidelity Physics

TL;DR

This paper introduces a physics-based deterministic model that combines fluid and crowd dynamics to accurately simulate viral aerosol transmission in large areas, enhancing pandemic modeling precision.

Contribution

It presents a novel integration of high-fidelity physics with computational crowd and fluid dynamics for detailed pathogen transmission simulation.

Findings

Can simulate viral spread over large areas with modest resources

Provides detailed tracing of viral particles in real-time

Improves accuracy of pandemic propagation models

Abstract

A deterministic pathogen transmission model based on high-fidelity physics has been developed. The model combines computational fluid dynamics and computational crowd dynamics in order to be able to provide accurate tracing of viral matter that is exhaled, transmitted and inhaled via aerosols. The examples shown indicate that even with modest computing resources, the propagation and transmission of viral matter can be simulated for relatively large areas with thousands of square meters, hundreds of pedestrians and several minutes of physical time. The results obtained and insights gained from these simulations can be used to inform global pandemic propagation models, increasing substantially their accuracy.