• 演讲人： 张原（中国人民大学统计学院副教授）
• 时间：2022年09月23日 周五上午10:00
• 地点：腾讯会议 ID：225-406-375
• 主办单位：浙江大学数据科学研究中心

张原，1988年6月出生，2010年于北京大学获得学士学位，2015年于美国杜克大学获得博士学位，现任中国人民大学统计学院副教授。张原研究方向主要集中于概率论中随机几何、随机相互作用粒子系统，以及流行病随机动力学建模；共有30余篇中英文论文被PNAS, Trans AMS, AoAP, SIMA, M3AS, SPA等国内外学术刊物发表或接收。

摘要：

Abstract:The current outbreak of coronavirus disease 2019 (COVID-19) has been going on for over two years and is deemed as a once-in-a-century health crisis. A major driving force in the persistence of COVID-19 is believed to be the transmission caused by those who are unaware of their infection and thus can easily pass on the pathogen to their family members. We employ stochastic dynamic models to  study the covertness and household transmissions of the COVID-19 base on epidemiological data in Hubei, China. Our models estimates that 79.8% (76.7% - 82.7%) of the spread of COVID-19 in Wuhan, 2020 was caused by hidden carriers; while 38.5% (22.7%-54.4%) of the total infections were caused by household transmissions in Yichang after the implementation of a strict city lock-down.  Our findings supports the necessity of prompt contact tracing followed by quarantine at designated sites.

联系人：苏中根（suzhonggen@zju.edu.cn）