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Exploring Coronavirus Disease 2019 Risk Factors: A Text Network Analysis Approach.

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  • 1Department of Nursing, Keimyung College University, Daegu 42601, Republic of Korea.

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Text network analysis identified key risk factors for severe COVID-19, including age and hypertension. Research focus shifted from acute symptoms to long COVID and vaccine efficacy over time.

Keywords:
coronavirus disease 2019risk factorstext network analysis

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Area of Science:

  • Public Health
  • Epidemiology
  • Data Science

Background:

  • The COVID-19 pandemic profoundly impacted global health and societies.
  • Understanding factors influencing COVID-19 spread and severity is crucial.

Purpose of the Study:

  • To analyze interconnections among risk factors for severe COVID-19 using text network analysis.
  • To track the evolution of research focus during the pandemic.

Main Methods:

  • Text network analysis of published studies (Jan 2020-Dec 2021).
  • Identification of key determinants like age, hypertension, and comorbidities.
  • Temporal trend analysis of research themes.

Main Results:

  • Five clusters of risk factors identified: biomedical, occupational, demographic, behavioral, and complication-related.
  • Early research focused on acute COVID-19 clinical characteristics.
  • Later research emphasized long COVID, quality of life, and vaccine efficacy against variants (Alpha, Delta, Omicron).

Conclusions:

  • Findings provide insights for targeted public health interventions for high-risk groups.
  • Text network analysis is a valuable tool for synthesizing complex pandemic data.
  • Supports evidence-based decision-making for pandemic preparedness and response.