Quantitative Biology > Populations and Evolution
[Submitted on 27 Jul 2020 (v1), last revised 1 Sep 2020 (this version, v3)]
Title:Analyzing the dominant SARS-CoV-2 transmission routes towards an ab initio SEIR model
View PDFAbstract:Identifying the relative importance of the different transmission routes of the SARS-CoV-2 virus is an urgent research priority. To that end, the different transmission routes, and their role in determining the evolution of the Covid-19 pandemic are analyzed in this work. Probability of infection caused by inhaling virus-laden droplets (initial, ejection diameters between $0.5-750\mu m$) and the corresponding desiccated nuclei that mostly encapsulate the virions post droplet evaporation, are individually calculated. At typical, air-conditioned yet quiescent indoor space, for average viral loading, cough droplets of initial diameter between $10-50 \mu m$ have the highest infection probability. However, by the time they are inhaled, the diameters reduce to about $1/6^{th}$ of their initial diameters. While the initially near unity infection probability due to droplets rapidly decays within the first $25s$, the small yet persistent infection probability of desiccated nuclei decays appreciably only by $\mathcal{O} (1000s)$, assuming the virus sustains equally well within the dried droplet nuclei as in the droplets. Combined with molecular collision theory adapted to calculate frequency of contact between the susceptible population and the droplet/nuclei cloud, infection rate constants are derived ab-initio, leading to a SEIR model applicable for any respiratory event - vector combination. Viral load, minimum infectious dose, sensitivity of the virus half-life to the phase of its vector and dilution of the respiratory jet/puff by the entraining air are shown to mechanistically determine specific physical modes of transmission and variation in the basic reproduction number $\mathcal{R}_0$, from first principle calculations.
Submission history
From: Swetaprovo Chaudhuri [view email][v1] Mon, 27 Jul 2020 14:28:28 UTC (748 KB)
[v2] Sat, 1 Aug 2020 01:45:52 UTC (739 KB)
[v3] Tue, 1 Sep 2020 15:24:07 UTC (699 KB)
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