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Background <p>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.</p> Methods <p>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.</p> Results <p>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.</p> Conclusions <p>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.</p>

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

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  • 发表日期：

    2025年10月31日

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  • Jiwon Han,
  • Eunok Jung

摘要

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.