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The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach

SIMPLE SUMMARY: In this study, we conducted a quantitative assessment and compared the COVID-19 pandemic spread in two countries based on selected methods from the graph theory domain. The results indicate that while the applied experimental procedures are useful, we could draw limited conclusions a...

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Autores principales: Davahli, Mohammad Reza, Karwowski, Waldemar, Fiok, Krzysztof, Murata, Atsuo, Sapkota, Nabin, Farahani, Farzad V., Al-Juaid, Awad, Marek, Tadeusz, Taiar, Redha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773348/
https://www.ncbi.nlm.nih.gov/pubmed/35053123
http://dx.doi.org/10.3390/biology11010125
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author Davahli, Mohammad Reza
Karwowski, Waldemar
Fiok, Krzysztof
Murata, Atsuo
Sapkota, Nabin
Farahani, Farzad V.
Al-Juaid, Awad
Marek, Tadeusz
Taiar, Redha
author_facet Davahli, Mohammad Reza
Karwowski, Waldemar
Fiok, Krzysztof
Murata, Atsuo
Sapkota, Nabin
Farahani, Farzad V.
Al-Juaid, Awad
Marek, Tadeusz
Taiar, Redha
author_sort Davahli, Mohammad Reza
collection PubMed
description SIMPLE SUMMARY: In this study, we conducted a quantitative assessment and compared the COVID-19 pandemic spread in two countries based on selected methods from the graph theory domain. The results indicate that while the applied experimental procedures are useful, we could draw limited conclusions about the dynamic nature of infection diffusion. We discussed the possible reasons for the above and used them to formulate research hypotheses that could serve the scientific community in future research efforts. ABSTRACT: Coronavirus disease 2019 (COVID-19) was first discovered in China; within several months, it spread worldwide and became a pandemic. Although the virus has spread throughout the globe, its effects have differed. The pandemic diffusion network dynamics (PDND) approach was proposed to better understand the spreading behavior of COVID-19 in the US and Japan. We used daily confirmed cases of COVID-19 from 5 January 2020 to 31 July 2021, for all states (prefectures) of the US and Japan. By applying the pandemic diffusion network dynamics (PDND) approach to COVID-19 time series data, we developed diffusion graphs for the US and Japan. In these graphs, nodes represent states and prefectures (regions), and edges represent connections between regions based on the synchrony of COVID-19 time series data. To compare the pandemic spreading dynamics in the US and Japan, we used graph theory metrics, which targeted the characterization of COVID-19 bedhavior that could not be explained through linear methods. These metrics included path length, global and local efficiency, clustering coefficient, assortativity, modularity, network density, and degree centrality. Application of the proposed approach resulted in the discovery of mostly minor differences between analyzed countries. In light of these findings, we focused on analyzing the reasons and defining research hypotheses that, upon addressing, could shed more light on the complex phenomena of COVID-19 virus spread and the proposed PDND methodology.
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spelling pubmed-87733482022-01-21 The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach Davahli, Mohammad Reza Karwowski, Waldemar Fiok, Krzysztof Murata, Atsuo Sapkota, Nabin Farahani, Farzad V. Al-Juaid, Awad Marek, Tadeusz Taiar, Redha Biology (Basel) Article SIMPLE SUMMARY: In this study, we conducted a quantitative assessment and compared the COVID-19 pandemic spread in two countries based on selected methods from the graph theory domain. The results indicate that while the applied experimental procedures are useful, we could draw limited conclusions about the dynamic nature of infection diffusion. We discussed the possible reasons for the above and used them to formulate research hypotheses that could serve the scientific community in future research efforts. ABSTRACT: Coronavirus disease 2019 (COVID-19) was first discovered in China; within several months, it spread worldwide and became a pandemic. Although the virus has spread throughout the globe, its effects have differed. The pandemic diffusion network dynamics (PDND) approach was proposed to better understand the spreading behavior of COVID-19 in the US and Japan. We used daily confirmed cases of COVID-19 from 5 January 2020 to 31 July 2021, for all states (prefectures) of the US and Japan. By applying the pandemic diffusion network dynamics (PDND) approach to COVID-19 time series data, we developed diffusion graphs for the US and Japan. In these graphs, nodes represent states and prefectures (regions), and edges represent connections between regions based on the synchrony of COVID-19 time series data. To compare the pandemic spreading dynamics in the US and Japan, we used graph theory metrics, which targeted the characterization of COVID-19 bedhavior that could not be explained through linear methods. These metrics included path length, global and local efficiency, clustering coefficient, assortativity, modularity, network density, and degree centrality. Application of the proposed approach resulted in the discovery of mostly minor differences between analyzed countries. In light of these findings, we focused on analyzing the reasons and defining research hypotheses that, upon addressing, could shed more light on the complex phenomena of COVID-19 virus spread and the proposed PDND methodology. MDPI 2022-01-13 /pmc/articles/PMC8773348/ /pubmed/35053123 http://dx.doi.org/10.3390/biology11010125 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Davahli, Mohammad Reza
Karwowski, Waldemar
Fiok, Krzysztof
Murata, Atsuo
Sapkota, Nabin
Farahani, Farzad V.
Al-Juaid, Awad
Marek, Tadeusz
Taiar, Redha
The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach
title The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach
title_full The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach
title_fullStr The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach
title_full_unstemmed The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach
title_short The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach
title_sort covid-19 infection diffusion in the us and japan: a graph-theoretical approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773348/
https://www.ncbi.nlm.nih.gov/pubmed/35053123
http://dx.doi.org/10.3390/biology11010125
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