The spreading of viruses by airborne aerosols: lessons from a first-passage-time problem for tracers in turbulent flows

TL;DR

This paper models how airborne viruses spread via aerosols in turbulent flows using a first-passage-time approach, providing insights for social distancing strategies based on aerosol dispersion statistics.

Contribution

It introduces a novel first-passage-time framework for turbulent aerosol dispersion and derives analytical models for the probability distribution of aerosol travel times.

Findings

Power-law tail with exponent 4 for small radii

Exponential decay for larger radii

Models enable improved social distancing guidelines

Abstract

We study the spreading of viruses, such as SARS-CoV-2, by airborne aerosols, via a new first-passage-time problem for Lagrangian tracers that are advected by a turbulent flow: By direct numerical simulations of the three-dimensional (3D) incompressible, Navier-Stokes equation, we obtain the time $t_R$ at which a tracer, initially at the origin of a sphere of radius $R$, crosses the surface of the sphere \textit{for the first time}. We obtain the probability distribution function $\mathcal{P}(R,t_R)$ and show that it displays two qualitatively different behaviors: (a) for $R \ll L_{\rm I}$, $\mathcal{P}(R,t_R)$ has a power-law tail $\sim t_R^{-\alpha}$, with the exponent $\alpha = 4$ and $L_{\rm I}$ the integral scale of the turbulent flow; (b) for $l_{\rm I} \lesssim R $, the tail of $\mathcal{P}(R,t_R)$ decays exponentially. We develop models that allow us to obtain these asymptotic behaviors analytically. We show how to use $\mathcal{P}(R,t_R)$ to develop social-distancing guidelines for the mitigation of the spreading of airborne aerosols with viruses such as SARS-CoV-2.