  The health threat from SARS-CoV-2 airborne infection has become a public
emergency of international concern. During the ongoing coronavirus pandemic,
people have been advised by the Centers for Disease Control and Prevention to
maintain social distancing of at least 2 m to limit the risk of exposure to the
coronavirus. Experimental data, however, show that infected aerosols and
droplets trapped inside a turbulent puff cloud can travel up to 7 to 8 m. We
propose a nuclear physics analogy-based modeling of the complex gas cloud and
its payload of pathogen-virions. We show that the cloud stopping range is
proportional to the product of the puff's diameter and its density. We use our
puff model to determine the average density of the buoyant fluid in the
turbulent cloud. A fit to the experimental data yields $1.8 < \rho_P/\rho_{\rm
air} < 4.0$, where $\rho_P$ and $\rho_{\rm air}$ are the average density of the
puff and the air. We demonstrate that temperature variation could cause an
${\cal O}(\pm 8\%)$ effect in the puff stopping range for extreme ambient cold
or warmth. We also demonstrate that aerosols and droplets can remain suspended
for hours in the air. Therefore, once the puff slows down sufficiently, and its
coherence is lost, the eventual spreading of the infected aerosols becomes
dependent on the ambient air currents and turbulence.
