Smallpox outbreak scenarios and reactive intervention protocols: A mathematical model-based analysis applied to the Republic of Korea

Abstract

Smallpox, caused by the variola virus, remains a potential biosecurity threat despite its eradication. This study develops a mathematical model to evaluate outbreak scenarios and the effectiveness of reactive intervention strategies in controlling transmission, with application to the Republic of Korea. The model incorporates age-stratified contact patterns, contact tracing, and vaccination strategies, including targeted vaccination and mass vaccination. Our simulations demonstrate that early outbreak recognition and rapid intervention are critical in mitigating smallpox spread. In scenarios where vaccination rollout was slow or outbreak recognition was delayed, severe patient numbers exceeded healthcare capacity, highlighting the need for preemptive preparedness. Sensitivity analyses revealed that outbreak recognition timing and contact tracing effectiveness were the most influential factors in determining outbreak severity, with later recognition leading to up to 3.5 times more cumulative cases. Furthermore, we compared different vaccination prioritization strategies and found that prioritizing high-transmission age groups was more effective in reducing total mortality than prioritizing high-risk groups based solely on disease severity. This contrasts with COVID-19 vaccination strategies, which focused on protecting vulnerable populations. These findings underscore the importance of early detection, strategic vaccination, and non-pharmaceutical interventions in mitigating a potential smallpox outbreak. Our model provides a quantitative framework for policymakers to evaluate intervention effectiveness and optimize outbreak response strategies.