应数学与统计学院邀请，香港理工大学何岱海教授为我院师生作学术报告。
报告题目：The Effectiveness of the COVID-19 Vaccination Campaign in 2021: Inconsistency in Key Studies
报告摘要：In this work, we revisited the evaluation of the effectiveness of the COVID-19 vaccination campaign in 2021, as measured by the number of deaths averted. The published estimates differ a lot: from one widely referenced paper by Watson et al. (2022) estimating 0.5-0.6% of the USA population being saved, to average-level estimates of 0.15-0.2%, and to some estimates as low as 0.0022%. For other countries, Watson et al. gave much higher estimates than all other works too. We reviewed 30 relevant papers, carried out an in-depth analysis of the model by Watson et al. and of several other studies, and provided our own regression-based analysis of the US county-level data. The model by Watson et al. is very sophisticated and has many features; some of them that make it more realistic (age-structured epidemiology, “elderly first” vaccination, healthcare overload effects), but others that are likely inaccurate (substantial reinfection rates (i.e., immunity loss) for the Alpha and Delta variants, possible overfitting due to overly flexible time-dependent infection transmission rate) or questionable (45% increase in fatality rate for the Delta variant). Yet, the main argument is that Watson et al.’s model does not reproduce the trends observed in the county-level US data. Eventually, we concluded that Watson et al.’s 0.5-0.6% is an overestimate, and 0.15-0.2% of the US population saved by vaccination – as estimated by regression studies on subnational-level data (e.g., Suthar et al. (2022) and by He et al. (2022)) – is much more plausible value. In our view, in order to be considered reliable, mathematical models should be tested on more detailed real data that was not used in model fitting. On the other hand, detailed data bring about new challenges in statistical modelling and uncertainties in data reliability.
报告时间：2025年5月12日16：00
报告地点：致勤楼（原教学9号楼）C101
邀 请 人：韩晓玲 教授
报告人简介：
何岱海，香港理工大学应用数学系教授，博士生导师。分别于1999年获西安交通大学工学博士和2006年加拿大麦克马斯大学数学博士，并且曾在北京师范大学物理系、美国密西根大学生态学系、以色列特拉维夫大学动物学系做博士后研究。主要研究兴趣是传染病建模和数据统计分析，在PNAS, Sci Adv, Ann Intern Med, Eur Respir J, J R Soc Interface等权威期刊发表论文140余篇，研究成果受到国内外媒体的广泛报道。关于非洲安哥拉黄热病的建模获2018年国际疾病监测学会的科学贡献最佳论文第二名；先后获得香港研究资助局项目、香港食品与卫生环境署健康与医疗项目、阿里巴巴合作研究基金等多项基金资助。Google H-index 47. 连续三年入选斯坦福大学发布的全球2%顶尖科学家榜单(2022-2024)，以及ScholarGPS 2024全球前0.05%学者。
甘肃省数学与统计学基础学科研究中心
数学与统计学院
