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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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Graph modelling for tracking the COVID-19 pandemic spread.

Rasim Alguliyev1, Ramiz Aliguliyev1, Farhad Yusifov1

  • 1Institute of Information Technology, Azerbaijan National Academy of Sciences, Baku, Azerbaijan.

Infectious Disease Modelling
|January 1, 2021
PubMed
Summary

This study introduces graph-based modeling to understand COVID-19 spread, analyzing factors like social distancing and contact duration to identify transmission patterns and undetected cases.

Keywords:
COVID-19Epidemiological characteristicsGraph visualizationModellingPandemic

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Area of Science:

  • Epidemiology
  • Computational Biology
  • Network Science

Background:

  • Infectious disease modeling is crucial for mitigation strategies.
  • Modeling the complex spread of COVID-19 is a current research priority.

Purpose of the Study:

  • To develop a graph-based model for understanding COVID-19 transmission dynamics.
  • To analyze factors influencing the spread, including social distancing and demographic characteristics.

Main Methods:

  • Investigated existing literature on COVID-19 modeling.
  • Proposed a conceptual graph model incorporating social distance, contact duration, and location-based demographics.
  • Visualized the virus spread from initial cases to human-to-human transmission.

Main Results:

  • The graph model effectively visualizes COVID-19 spread, considering epidemiological characteristics.
  • This approach allows for numerical experiments and reverse analysis of infection spread.
  • The model aids in identifying undetected cases by analyzing social distance and contact duration, reducing uncertainty.

Conclusions:

  • Graph-based modeling offers a powerful tool for analyzing pandemic dynamics and identifying transmission factors.
  • This method enhances understanding of infectious disease spread and aids in public health interventions.
  • Future research should incorporate a wider range of socio-economic and demographic factors for more comprehensive modeling.