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Main Authors: Sheshanarayana, Rahul, Jha, Prateek K.
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2501.10489
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author Sheshanarayana, Rahul
Jha, Prateek K.
author_facet Sheshanarayana, Rahul
Jha, Prateek K.
contents The dynamics of infection spread in populations has received popular attention since the outbreak of Covid-19 and many statistical models have been developed. One of the interesting areas of research is short-time dynamics in confined, indoor environments. We have modeled this using a simple Monte Carlo scheme. Our model is generally applicable for the peer-to-peer transmission case, when the infection spread occurs only between an infected subject and a healthy subject with a certain probability, i.e., airborne and surface transmission is neglected. The probability of infection spread is incorporated using a simple exponential decay with distance between the subjects. Simulations are performed for the cases of (1) constant subject population and (2) variable subject population due to inflow/outflow. We specifically focus on the large fluctuations in the dynamics due to finite number of subjects. Results of our study may be useful to determine social-distancing guidelines in indoor contexts.
format Preprint
id arxiv_https___arxiv_org_abs_2501_10489
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Monte Carlo Simulations of Infection Spread in Indoor Environment
Sheshanarayana, Rahul
Jha, Prateek K.
Physics and Society
The dynamics of infection spread in populations has received popular attention since the outbreak of Covid-19 and many statistical models have been developed. One of the interesting areas of research is short-time dynamics in confined, indoor environments. We have modeled this using a simple Monte Carlo scheme. Our model is generally applicable for the peer-to-peer transmission case, when the infection spread occurs only between an infected subject and a healthy subject with a certain probability, i.e., airborne and surface transmission is neglected. The probability of infection spread is incorporated using a simple exponential decay with distance between the subjects. Simulations are performed for the cases of (1) constant subject population and (2) variable subject population due to inflow/outflow. We specifically focus on the large fluctuations in the dynamics due to finite number of subjects. Results of our study may be useful to determine social-distancing guidelines in indoor contexts.
title Monte Carlo Simulations of Infection Spread in Indoor Environment
topic Physics and Society
url https://arxiv.org/abs/2501.10489