Journal Article

Quantitative analysis of self-reporting and contact tracing in heterogeneous risk groups: a stochastic modeling study of the COVID-19 outbreak in Daegu, Korea

Han, Jiwon, Jung, Eunok

2025

Overview

Background In the early stages of a novel infectious disease outbreak, when vaccines, treatments, and herd immunity are lacking, non-pharmaceutical interventions—particularly self-reporting and contact tracing—play a critical role in suppressing transmission. During the first wave of COVID-19 in Korea, a large outbreak centered around a religious community in Daegu rapidly escalated, thus highlighting the transmission risks associated with a closed and low-reporting high-risk group. This study aimed to quantitatively assess the effectiveness of self-reporting and contact tracing strategies across heterogeneous risk groups. Methods The population of Daegu was stratified into two groups: a high-risk group characterized by high transmissibility and low reporting rate, and a low-risk group with lower transmissibility and higher reporting compliance. We developed a stochastic model and applied a modified Gillespie algorithm incorporating both Markovian and non-Markovian processes. Scenario-based simulations were conducted to evaluate the impact of changes in self-reporting rates and delays in contact tracing. We simulated each scenario 10,000 times to estimate the mean and 95% credible intervals for the number of infections. Results When the self-reporting rate in the high-risk group was lowered to 0.1, the total infections increased by approximately 22%, while unreported infections rose by 164% compared to the baseline. Conversely, increasing the self-reporting rate in the high-risk group to 0.8 reduced the total cases by approximately 21% and unreported infections by 86%. Notably, unreported infections in the low-risk group increased by approximately 416% when their reporting rate declined to 0.4, although this group had a lower transmission potential. Even a modest contact tracing delay of 4–7 d resulted in an 85% increase in unreported cases, with diminishing returns for longer delays, highlighting the critical importance of timely tracing in outbreak control. Conclusions In situations with heterogeneous risk groups, improving the self-reporting behavior of high-risk populations and maintaining high compliance in the low-risk group are essential for effective outbreak control. Contact tracing should be completed within 1–4 d to prevent further spread. Our study which accounts for behavioral heterogeneity, provides a scientific foundation for designing group-specific intervention strategies in future outbreaks of emerging infectious diseases.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Adult / Biostatistics / Community / Contact tracing / Contact Tracing - methods / Contact Tracing - statistics & numerical data / Control / COVID-19 / COVID-19 - epidemiology / COVID-19 - transmission / Disease control / Disease Outbreaks / Disease transmission / Effectiveness / Environmental Health / Epidemics / Epidemiology / Female / Health aspects / Herd immunity / Heterogeneity / Heterogeneous risk groups / Humans / Infectious diseases / Male / Medicine / Medicine & Public Health / Mpox / Non-pharmaceutical interventions / Outbreaks / Public Health / Religion / Republic of Korea - epidemiology / Risk / Risk Factors / Risk groups / Self Report - statistics & numerical data / Self-reporting / Simulation / Social behavior / Social distancing / South Korea / Stochastic modeling / Stochastic models / Stochastic Processes / Vaccine