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Exploring the Knowledge Structure and Trends for Severe COVID-19 Risk Factors Using Text Network Analysis.

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Summary

This study mapped severe COVID-19 risk factors using text network analysis of over 22,000 papers. Key themes include biomedical, occupational, demographic, behavioral factors, and complications, revealing chronological trends in severe COVID-19 risk research.

Keywords:
Coronavirusknowledge structurerisk factorssevere COVID-19text network analysis

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Area of Science:

  • Public Health and Epidemiology
  • Data Science and Network Analysis
  • Infectious Diseases

Background:

  • Severe COVID-19 risk factors are complex and multifactorial.
  • Understanding the evolving knowledge landscape is crucial for effective public health strategies.
  • Previous research has not systematically analyzed the structure and trends of severe COVID-19 risk factors.

Purpose of the Study:

  • To identify the knowledge structure and emerging trends in severe COVID-19 risk factors.
  • To analyze the relationships between different categories of risk factors.
  • To provide a systematic overview of research on severe COVID-19 risk.

Main Methods:

  • Text network analysis of 22,628 research papers published between January 2020 and December 2021.
  • Utilized Text Rank analyzer and Gephi software for analysis and visualization.
  • Grouped identified risk factors into five central themes: biomedical, occupational/environmental, demographic, health behavior, and complications.

Main Results:

  • Identified five core themes encompassing biomedical, occupational/environmental, demographic, health behavior factors, and complications.
  • Revealed chronological trends in the emergence and focus of different risk factors over time.
  • Established a knowledge structure illustrating the interconnectedness of various severe COVID-19 risk factors.

Conclusions:

  • The study provides a systematic understanding of the complex landscape of severe COVID-19 risk factors.
  • The identified themes and trends can inform future research and public health interventions.
  • Text network analysis is a valuable tool for mapping knowledge structures in rapidly evolving research fields like COVID-19.