Effects of Interactions Between Individuals and Spatial Dynamics on The Spread of Infectious Diseases using Voronoi Tessellation and The Ising Model

This study investigates the spatial distribution of individuals within a randomly distributed sample population and their interactions with an infectious disease. For this purpose, an Ising model enhanced with Voronoi tessellation is used to create a more realistic framework for modeling disease spread. The model simulates the process of spreading infectious disease by considering the interactions between individuals and their movement dynamics. The sample population in this study was created for simulation purposes only and is not based on actual demographic of epidemiological data. To assess the infectiousness in the model, the parameter J, defined as the transmission coefficient, is analyzed.

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Publication Details

Journal
Bitlis Eren Üniversitesi Fen Bilimleri Dergisi
Published
2025-06-27
DOI
https://doi.org/10.17798/bitlisfen.1584111
Primary Topic
COVID-19 epidemiological studies
Type
article
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article

Effects of Interactions Between Individuals and Spatial Dynamics on The Spread of Infectious Diseases using Voronoi Tessellation and The Ising Model

Hasan Bulut, Şeyma Firdevs Hızal
Bitlis Eren Üniversitesi Fen Bilimleri Dergisi
COVID-19 epidemiological studies
article

Effects of Interactions Between Individuals and Spatial Dynamics on The Spread of Infectious Diseases using Voronoi Tessellation and The Ising Model

Hasan Bulut, Şeyma Firdevs Hızal
article en

Abstract

This study investigates the spatial distribution of individuals within a randomly distributed sample population and their interactions with an infectious disease. For this purpose, an Ising model enhanced with Voronoi tessellation is used to create a more realistic framework for modeling disease spread. The model simulates the process of spreading infectious disease by considering the interactions between individuals and their movement dynamics. The sample population in this study was created for simulation purposes only and is not based on actual demographic of epidemiological data. To assess the infectiousness in the model, the parameter J, defined as the transmission coefficient, is analyzed.

Bitlis Eren Üniversitesi Fen Bilimleri DergisiVol. 14(2)
Fırat University (TR)
Openalex Percentile: Top 82%
COVID-19 epidemiological studies
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