COVID-19 transmission dynamics: age-specific patterns and super spreaders in South Korea

Analyzing age-specific infection networks is vital for clarifying transmission patterns and susceptibility across different age groups. Our study provides valuable evidence for identifying vulnerable populations and key cohorts that drive dissemination within the infection network. These insights can directly inform policy formulation, particularly in prioritizing vaccination strategies and tailoring age-targeted prevention measures. More broadly, this network-based approach offers a framework for designing effective control strategies against future emerging infectious diseases.

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Publication Details

Journal
BMC Public Health
Published
2026-02-24
DOI
https://doi.org/10.1186/s12889-026-26712-x
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00
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article

COVID-19 transmission dynamics: age-specific patterns and super spreaders in South Korea

Arsen Abdulali, Hayoung Choi, Ganghyun Yoon, Hyosun Lee et al.
BMC Public Health
COVID-19 epidemiological studies
article

COVID-19 transmission dynamics: age-specific patterns and super spreaders in South Korea

Arsen Abdulali, Hayoung Choi, Ganghyun Yoon, Hyosun Lee, Sunmi Lee, Gerardo Chowell
article en

Abstract

Analyzing age-specific infection networks is vital for clarifying transmission patterns and susceptibility across different age groups. Our study provides valuable evidence for identifying vulnerable populations and key cohorts that drive dissemination within the infection network. These insights can directly inform policy formulation, particularly in prioritizing vaccination strategies and tailoring age-targeted prevention measures. More broadly, this network-based approach offers a framework for designing effective control strategies against future emerging infectious diseases.

BMC Public Health
Queen Mary University of London (GB), Georgia State University (US), Trinity College (CA), University of Cambridge (GB), Kyungpook National University (KR), Kyung Hee University (KR)
Openalex Percentile: Top 49%
COVID-19 epidemiological studies
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