How Big Will an Epidemic Be? From SIR Models to COVID-19
日期：May 11, 2026 ｜ 時間：13:00 - 14:00
| 講者姓名(Speaker Name) | 黃侑仁 |
|---|---|
| 現職職稱(Current Job Title) | 臺師大博士後及兼任助理教授 |
| 最高學歷(Highest Education) | 國立彰化師範大學博士 |
| 經歷(Experience) | 1. 2023/08～目前：國立臺灣師範大學數學系博士後研究員(三年期) 2. 2024/08～目前：國立臺灣師範大學數學系兼任助理教授。 3. 2026/07～2026/08：國立臺灣師範大學數學系兼任助理教授，授課大學先修課程微積分乙（一），並擔任大學先修課程（AP）微積分領域召集人。 4. 2023/02～2023/06：嶺東科技大學資訊管理系兼任講師。 |
演講摘要 (Speech Summary)
In this talk, we start from the classic SIR model to understand how infectious diseases spread, and gradually connect it to real-world applications. We focus on how to estimate the final size distribution, an important indicator of epidemic impact, using COVID-19 as a case study. By comparing three Monte Carlo approaches, we find that Sellke’s method is the most efficient. We further develop a new algorithm that reduces computation time by at least 20%, making large-scale simulations more practical. This improvement also allows us to perform sensitivity analysis and explore how different factors influence outcomes. Our results reveal the long-lasting impact of COVID-19.
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