A Stochastic Graph-based Model for the Simulation of SARS-CoV-2
Transmission
- URL: http://arxiv.org/abs/2111.05802v1
- Date: Wed, 10 Nov 2021 16:50:00 GMT
- Title: A Stochastic Graph-based Model for the Simulation of SARS-CoV-2
Transmission
- Authors: Christos Chondros, Stavros D. Nikolopoulos, Iosif Polenakis
- Abstract summary: We propose a graph-based model for the simulation of SARS-CoV-2 transmission.
The proposed approach incorporates three sub-models, namely, the spatial model, the mobility model, and the propagation model.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In this work we propose the design principles of a stochastic graph-based
model for the simulation of SARS-CoV-2 transmission. The proposed approach
incorporates three sub-models, namely, the spatial model, the mobility model,
and the propagation model, in order to develop a realistic environment for the
study of the properties exhibited by the spread of SARS-CoV-2. The spatial
model converts images of real cities taken from Google Maps into undirected
weighted graphs that capture the spatial arrangement of the streets utilized
next for the mobility of individuals. The mobility model implements a
stochastic agent-based approach, developed in order to assign specific routes
to individuals moving in the city, through the use of stochastic processes,
utilizing the weights of the underlying graph to deploy shortest path
algorithms. The propagation model implements both the epidemiological model and
the physical substance of the transmission of an airborne virus considering the
transmission parameters of SARS-CoV-2. Finally, we integrate these sub-models
in order to derive an integrated framework for the study of the epidemic
dynamics exhibited through the transmission of SARS-CoV-2.
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