Applications of Likelihood-based inference with non-mechanistic and mechanistic models in infectious disease modeling

Description: 

Presented June 21, 2019.

In this talk, Dr. Daihai He presents his recent works on applications of likelihood-based inference with non-mechanistic and mechanistic models in infectious disease modeling. Examples include modeling of the transmission of influenza, measles, yellow-fever virus, Zika virus, and Lassa-fever virus. Combined non-mechanistic and mechanistic models, we gain new insight into the mechanisms under the transmission of infectious diseases. 

his presentation is an expansion on the article on "Modelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccination," which won second prize for the 2019 Awards for Outstanding Research Article in Biosurveillance in the category of Scientific Achievement.

Presenter

Daihai He, Ph.D. in Engineering and Mathematics, Associate Professor, Department of Applied Mathematics, Hong Kong Polytechnic University

Author: 
Primary Topic Areas: 
Original Publication Year: 
2019
Event/Publication Date: 
June, 2019

June 21, 2019

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