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Using Active Matter to Model Different Types of Epidemic Behavior

ORAL

Abstract

Active matter describes self motile systems including particle based systems that undergo run-and-tumble or driven diffusive motion. Here we show how particle-based active matter systems can be used to model and tune between Susceptible-Infected (SI) and Susceptible-Infected-Recovered (SIR) regimes. The motility-induced phase separation that occurs in active matter permits the easy introduction of spatial heterogeneity, quenched disorder, and mobility changes among the active agents, which can infect each other with some probability upon contact. When we encode the standard SIR model into active particles interacting with quenched disorder, we show when the infection rate is low and the spread of the infection is heterogeneous, the quenched disorder has a strong impact on the epidemic, whereas when the infection rate is high, the impact of the quenched disorder is reduced and the epidemic spreads via well defined waves [1]. For the case where spontaneous recovery is absent, as in the zombie outbreak model [2], we show that by introducing two species of susceptible agents and giving only one species the ability to cure the zombies, it is possible to induce a novel tunable transition between SI and SIR behavior. This type of model could address situations such as HIV in which there are limited resources for reducing infection. We discuss how active matter systems could be used to produce table top epidemic model experiments.

[1] "Using active matter to introduce spatial heterogeneity to the susceptible infected recovered model of epidemic spreading," P. Forgacs, A. Libal, C. Reichhardt, N. Hengartner, and C. J. O. Reichardt, Sci. Rep. 12, 11229 (2022).

[2] "You can run, you can hide: The epidemiology and statistical mechanics of zombies," A. A. Alemi, M. Bierbaum, C. R. Myers, and J. P. Sethna, Phys. Rev. E 92, 052801 (2015).

Presenters

  • Cynthia Reichhardt

    Los Alamos National Laboratory

Authors

  • Cynthia Reichhardt

    Los Alamos National Laboratory

  • Peter Forgacs

    Babes-Bolyai University

  • Andras Libal

    Babes-Bolyai University

  • Nick Hengartner

    Los Alamos National Laboratory

  • Charles M Reichhardt

    Los Alamos National Laboratory