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


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.


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

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

June 21, 2019

Contact Us

NSSP Community of Practice



This website is supported by Cooperative Agreement # 6NU38OT000297-02-01 Strengthening Public Health Systems and Services through National Partnerships to Improve and Protect the Nation's Health between the Centers for Disease Control and Prevention (CDC) and the Council of State and Territorial Epidemiologists. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC. CDC is not responsible for Section 508 compliance (accessibility) on private websites.

Site created by Fusani Applications