Variability in the serial interval of Covid-19 in South Korea

A comprehensive analysis of age and regional influences

Bibliographic Data

ID22088797
AuthorsHyosun Lee (0000-0002-0107-3100, Kyung Hee University), Gira Lee (0000-0002-2111-1995, Kyung Hee University), Tobhin Kim (Kyung Hee University), Suhyeon Kim (0000-0002-8525-5138, Kyung Hee University), Hyoeun Kim (0000-0002-7334-9700, Kyung Hee University), Sunmi Lee (0000-0003-1126-0660, Kyung Hee University, corresponding author)
Year2024
Volume12
Pages1362909-1362909
Publication date2024-03-07
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1362909
PMID38515590
OpenAlexW4392559413
LanguageEN
Citations received1
References cited35

Introduction: Quantifying the transmissibility over time, particularly by region and age, using parameters such as serial interval and time-varying reproduction number, helps in formulating targeted interventions. Moreover, considering the impact of geographical factors on transmission provides valuable insights into the effectiveness of control measures. Methods: Drawing on a comprehensive dataset of COVID-19 cases in South Korea, we analyzed transmission dynamics with a focus on age and regional variations. The dataset, compiled through the efforts of dedicated epidemiologists, includes information on symptom onset dates, enabling detailed investigations. The pandemic was divided into distinct phases, aligning with changes in policies, emergence of variants, and vaccination efforts. We analyzed various interventions such as social distancing, vaccination rates, school closures, and population density. Key parameters like serial interval, heatmaps, and time-varying reproduction numbers were used to quantify age and region-specific transmission trends. Results: Analysis of transmission pairs within age groups highlighted the significant impact of school closure policies on the spread among individuals aged 0-19. This analysis also shed light on transmission dynamics within familial and educational settings. Changes in confirmed cases over time revealed a decrease in spread among individuals aged 65 and older, attributed to higher vaccination rates. Conversely, densely populated metropolitan areas experienced an increase in confirmed cases. Examination of time-varying reproduction numbers by region uncovered heterogeneity in transmission patterns, with regions implementing strict social distancing measures showing both increased confirmed cases and delayed spread, indicating the effectiveness of these policies. Discussion: Our findings underscore the importance of evaluating and tailoring epidemic control policies based on key COVID-19 parameters. The analysis of social distancing measures, school closures, and vaccine impact provides valuable insights into controlling transmission. By quantifying the impact of these interventions on different age groups and regions, we contribute to the ongoing efforts to combat the COVID-19 pandemic effectively

2019-20 coronavirus outbreak · Disease · Geography · Outbreak · COVID-19 and Mental Health · COVID-19 epidemiological studies · Demography · Mathematics · Medicine · Vaccine Coverage and Hesitancy · Internal Medicine · Virology

Tools

Open DOIOpen Access