Distinguished Lecture Series - Learning from COVID-19 Data on Transmission, Health Outcomes and Interventions
- Date & Time
- Jan 14, 2021 (Thurs) | 10:30am (HKT)
- Venue
- ZOOM online lecture (https://bit.ly/2IY8Ajg)
- Speaker
- Professor Xihong Lin
Professor of Biostatistics and of Statistics at Harvard University
COVID-19 is an emerging respiratory infectious disease that has become a pandemic.
In this talk, Professor Xihong Lin will first provide a historical overview of the epidemic in Wuhan, with the provision of analysis results of 32,000 lab-confirmed COVID-19 cases in Wuhan to estimate the transmission rates using Poisson Partial Differential Equation based transmission dynamic models. This model is also used to evaluate the effects of different public health interventions on controlling the COVID-19 outbreak, such as social distancing, isolation and quarantine. Professor Lin will present the results on the epidemiological characteristics of the cases, which show that multi-faceted intervention measures successfully controlled the outbreak in Wuhan.
Professor Lin will next present the transmission regression models for estimating transmission rates in USA and other countries, as well as factors including intervention effects using social distancing, test-trace-isolate strategies that affect transmission rates. She will present the analysis results of >500,000 participants of the HowWeFeel project on symptoms and health conditions in US, and discuss the risk factors of the epidemic.
Estimation of the proportion of undetected cases will also be discussed, including asymptomatic, pre-symptomatic cases and mildly symptomatic cases, the chances of resurgence in different scenarios, and the factors that affect transmissions. Professor Lin will also present the US county-level analysis to study the demographic, social-economic, and comorbidity factors that are associated with COVID-19 case and death rates, and will provide several takeaways and discuss priorities.
Revisit the lecture:
Speaker Professor Xihong Lin
Professor of Biostatistics and of Statistics at Harvard University
Professor Lin’s research interests lie in development and application of scalable statistical and computational methods for analysis of massive data from genome, exposome and phenome, such as large scale Whole Genome Sequencing studies, integrative analysis of different types of data, biobanks, as well as complex epidemiological and observational studies, and statistical learning methods for big data. She has been active in COVID-19 research. Awards and Achievements
