Session Details
[SS10]Epidemic Modeling: Advances in Disease Control and Future Challenges
Tue. Jul 8, 2025 10:10 AM - 11:50 AM JST
Tue. Jul 8, 2025 1:10 AM - 2:50 AM UTC
Tue. Jul 8, 2025 1:10 AM - 2:50 AM UTC
Room 03
Chair:Sunmi Lee(Kyunghee University, Korea)
Epidemic Modeling: Advances in Disease Control and Future Challenges" underscores the essential role of mathematical and computational models in managing infectious diseases. These models predict disease spread, identify hotspots, and evaluate intervention effectiveness, guiding policymakers in resource allocation and public health measures. With advancements in methodologies, such as machine learning and network theory, models have become more accurate and realistic. They also enable real-time surveillance and adaptive management of outbreaks, while anticipating future challenges like antimicrobial resistance and zoonotic diseases. Additionally, the field promotes interdisciplinary collaboration, enhancing model robustness and improving public understanding of health risks, ultimately strengthening disease control efforts.
[SS10-01]Estimating vaccine effectiveness among wildlife without using population dynamics data
*Ryosuke Omori1, Ryota Matsuyama2, Yoko Hayama2, Takehisa Yamamoto2 (1. Hokkaido Univerisity (Japan), 2. National Agriculture and Food Research Organization (Japan))
[SS10-02]Human Mobility and Effectiveness of Non-Pharmaceutical Interventions: A High-Fidelity Agent-Based Model of COVID-19
*Young Kim1, Sunmi Lee1 (1. Kyung Hee University (Korea))
[SS10-03]Modeling the Transmission Dynamics of Tuberculosis in South Korea to Assess the National Control Program
*Kyeongah Nah1 (1. National Institute for Mathematical Sciences (Korea))
[SS10-04]Forecasting Seasonal Infectious Disease Outbreaks using Statistical and Machine Learning Methods
*Hyojung Lee1 (1. Department of Statistics, Kyungpook National University (Korea))
[SS10-05]Estimation of Effective Reproduction Number for a Heterogenous Model
*Sunmi Lee1 (1. Kyung Hee University (Korea))