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

Mohammad Reza Davahli1, Waldemar Karwowski1, Krzysztof Fiok1

  • 1Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA.

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The pandemic diffusion network dynamics (PDND) approach revealed minor differences in COVID-19 spread between the US and Japan. Further research is needed to understand the complex dynamics of virus transmission.

Keywords:
COVID-19 pandemicgraph theorynetwork densitypandemic diffusion

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Area of Science:

  • Epidemiology
  • Network Science
  • Public Health

Background:

  • Coronavirus disease 2019 (COVID-19) rapidly spread globally, becoming a pandemic.
  • The pandemic's impact and spread dynamics varied across different regions.
  • Understanding regional transmission patterns is crucial for effective public health interventions.

Purpose of the Study:

  • To apply the pandemic diffusion network dynamics (PDND) approach to analyze COVID-19 spread in the US and Japan.
  • To compare the network dynamics of COVID-19 diffusion between the US and Japan.
  • To identify key network characteristics influencing pandemic spread.

Main Methods:

  • Utilized daily confirmed COVID-19 cases from January 2020 to July 2021 for US states and Japanese prefectures.
  • Developed diffusion graphs where nodes represent regions and edges signify synchronized COVID-19 case data.
  • Employed graph theory metrics (e.g., path length, efficiency, centrality) to analyze network structures and compare spreading dynamics.

Main Results:

  • The PDND approach generated diffusion graphs for both the US and Japan.
  • Graph theory metrics indicated mostly minor differences in COVID-19 spreading dynamics between the two countries.
  • Analysis highlighted the utility of network metrics for characterizing complex pandemic behaviors.

Conclusions:

  • COVID-19 spread dynamics in the US and Japan, when analyzed via PDND, showed largely similar network characteristics.
  • Further investigation is warranted to explore the underlying reasons for observed similarities and differences.
  • The study underscores the value of network science in understanding and potentially mitigating future pandemics.