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. 2020 Jun 1;32(6):061704.
doi: 10.1063/5.0012009.

Likelihood of survival of coronavirus in a respiratory droplet deposited on a solid surface

Affiliations

Likelihood of survival of coronavirus in a respiratory droplet deposited on a solid surface

Rajneesh Bhardwaj et al. Phys Fluids (1994). .

Abstract

We predict and analyze the drying time of respiratory droplets from a COVID-19 infected subject, which is a crucial time to infect another subject. Drying of the droplet is predicted by using a diffusion-limited evaporation model for a sessile droplet placed on a partially wetted surface with a pinned contact line. The variation in droplet volume, contact angle, ambient temperature, and humidity are considered. We analyze the chances of the survival of the virus present in the droplet based on the lifetime of the droplets under several conditions and find that the chances of the survival of the virus are strongly affected by each of these parameters. The magnitude of shear stress inside the droplet computed using the model is not large enough to obliterate the virus. We also explore the relationship between the drying time of a droplet and the growth rate of the spread of COVID-19 in five different cities and find that they are weakly correlated.

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Figures

FIG. 1.
FIG. 1.
Probability density function (PDF) of the normal distribution of the droplet diameter in air considered in this letter.
FIG. 2.
FIG. 2.
Schematic of the problem considered in the present study.
FIG. 3.
FIG. 3.
Effect of droplet volume on evaporation time as a function of ambient temperature, surface wettability, and relative humidity.
FIG. 4.
FIG. 4.
Mean and standard deviation of the probability density function of computed drying time normal distribution. The drying time was calculated for the droplet volume distribution plotted in Fig. 1. The mean and standard deviation are shown by a vertical red bar and error bar, respectively, for different cases considered in this study.
FIG. 5.
FIG. 5.
Comparison among evolution of the total infections in different cities/regions. Day 0 is defined as the day on which the total number of infections is 100 or larger. The slope of the linear fit obtained using the least-squares method is considered as the growth rate of the infection (the number of infections per day).
FIG. 6.
FIG. 6.
Comparison of the growth rate of the infection in different cities/regions (bars) with respective drying times (squares) of a 5 nl droplet. The error bar represents the variability in outdoor weather.

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