Ping Yan, PhD
Current research and/or projects
Dr. Yan applies biostatistics, applied probability and mathematical models in the area of epidemiology of communicable disease transmission and control; also conducts research in the development of mathematical and statistical models and methods for investigating infectious diseases. He both manages a research group in disease modelling and publishes his own research in collaboration with other scientists.
Research and/or project statements
Manages Modelling, Projection and Risk Assessment Section, composed of applied mathematicians and statisticians, specializes in modelling, simulation, biostatistics, prediction and operations research
Section provides modelling and risk assessment service to Centre for Communicable Diseases and Infection Control (CCDIC) and supports core functions of the Infectious Diseases Prevention and Control Branch
Focuses on HIV, Hepatitis C and TB, using models to guide development of professional guidelines as well as statistical services to estimation of disease burden
Provides modelling and simulation services regarding pandemic influenza preparedness, vaccination and emergency preparedness/responses
Education and awards
Ph.D. Statistics, University of Waterloo, 1992
M.Math Statistics, University of Waterloo, 1987
B.Sc. Mathematics, University of Science and Technology of China, 1982
International experience and/or work
Member of the UNAIDS Global Reference Group on Estimation and Modelling of HIV/AIDS
Member of the WHO HIV Incidence Assay Working Group
Between 1994-2004, Collaborated on special projects studying and analyzing epidemics, and surveillance and monitoring HIV/AIDS in China, Spain, Paraguay, Colombia, Argentina and Romania.
As a member of the WHO delegation, participated in and contributed to a special workshop on the development of vaccines for SARS and Bird Flu in Beijing, China, 2004.
Participated in and contributed to DIMACS Working Group on Modeling Social Responses to Bio-terrorism Involving Infectious Agents, New Jersey, U.S.A., 2004
Participated in and contributed to a collaboration network with United Kingdom Centre for Applied Microbiology and Research, Health Protection Agency and Department of Health, on the risk assessment modelling for smallpox, anthrax and plague, 2002-2003
Yan, P. and Chowell, G. Quantitative Methods for Investigating Infectious Disease Outbreaks. Text in Applied Mathematics. August 2019. Springer Nature. (Book) ISBN: 978-3-030-21923-9; 978-3-030-21922-2.
Yan P. and Zhang F. (2018) A case study of nonlinear programming approach for repeated testing of HIV in a population stratified by subpopulations according to different risks of new infections. Operations Research for Health Care.
Yan P. (2018) A frailty model for intervention effectiveness against disease transmission when implemented with unobservable heterogeneity. Mathematical Biosciences & Engineering,15 (1): 275-298.
Trubnikov M., Yan P., Archibald C. (2014) Estimated prevalence of Hepatitis C virus infection in Canada, 2011. Canadian Communicable Disease Report 12/2014; 40(19):429-436.
Nishiura H., Yan P., Sleeman CK and Mode CJ. (2012) Estimating the transmission potential of supercritical process based on final size distribution of minor outbreaks. Journal of Theoretical Biology 294: 48-55
Yan P, Zhang F and Wand H. (2011) Using HIV diagnostic data to estimate HIV incidence: method and simulation. Statistical Communications in Infectious Diseases, De Gruyter, Vol. 3 (1): Article 6.
Yan P. and Feng, Z. (2010) Variability order of the latent and the infectious periods in a deterministic SEIR epidemic model and evaluation of control effectiveness. Mathematical biosciences 224(1):43-52.
Yan P. (2008) Separate roles of the latent and infectious periods in shaping the relation between the basic reproduction number and the intrinsic growth rate of infectious disease outbreaks. Journal of Theoretical Biology 251(2):238-52
Gentleman RC, Lawless JF, Lindsey C and Yan P. (1994) Multi-state Markov models for analysing incomplete disease history data with illustrations for HIV disease. Statistics in Medicine 13(8):805-21