Leung, Sze Man Kathy

Assistant Professor

Division of Epidemiology and Biostatistics

  • PhD (HKU), MPhil (HKU), BS (Peking U)

Kathy Leung received her BS in Biological Sciences from School of Life Sciences and BA in Economics from China Center for Economic Research at Peking University, MPhil, and PhD from School of Public Health at The University of Hong Kong.

Kathy was initially a wet-bench trainee in biochemistry working to elucidate the signalling pathways of innate immunity against virus infections. Later she found her interest lies more in mathematics and statistics involved in biological processes. In recent years, Kathy is interested in mathematical modelling of a wide range of diseases such as influenza, MERS, COVID-19, hand-foot-and-mouth disease, HPV, cervical cancer, colorectal cancer, and breast cancer. She also conducts epidemiological and economic evaluations of disease intervention strategies, such as HMFD vaccination, public health and social measures against COVID-19, and risk-based breast cancer screening. Leveraged on the latest development of data science, she also uses machine learning to interpret SARS-CoV-2 genomic data and participates in the development of tools to tackle misinformation about COVID-19 vaccination with natural language processing.   

Kathy is a member of HKU’s COVID-19 Response Team and has contributed to the earliest studies about COVID-19 epidemiology. She is the principal investigator or co-investigator of research studies funded or commissioned by the General Research Fund and Health and Medical Research Fund. She is one of the core developers of HKU's first Massive Open Online Course (MOOC) Epidemics, and also an investigator of Programme 1 of the Laboratory of Data Discovery for Health (D²4H) at the Hong Kong Science Park.

Google Scholar: https://scholar.google.com.hk/citations?hl=en&user=Ki1eg2UAAAAJ

Selected Publications
  1. Leung K*, Wu JT*, Leung GM. Real-time tracking and prediction of COVID-19 infection using digital proxies of population mobility and mixing. Nature communications. 2021 Mar 8;12(1):1-8. DOI: 10.1038/s41467-021-21776-2
  2. Leung K, Shum HH, Leung GM, Lam TT, Wu JT. Early transmissibility assessment of the N501Y mutant strains of SARS-CoV-2 in the United Kingdom, October to November 2020. Eurosurveillance. 2021 Jan;26(1):2002106. DOI: 10.2807/1560-7917.ES.2020.26.1.2002106
  3. Leung K*, Wu JT*, Liu D, Leung GM. (2020) First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment. The Lancet. DOI: 10.1016/S0140-6736(20)30746-7
  4. Leung K*, Wu JT*, Wong IO*, Shu XO, Zheng W, Wen W, Khoo US, Ngan R, Kwong A, Leung GM. Using Risk Stratification to Optimize Mammography Screening in Chinese Women. JNCI Cancer Spectrum. 2021. DOI: 10.1093/jncics/pkab060
  5. Wu JT*, Leung K*, Bushman M, Kishore N, Niehus R, de Salazar PM, Cowling BJ, Lipsitch M, Leung GM. (2020) Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China. Nature Medicine. DOI: 10.1038/s41591-020-0822-7
  6. Wu JT*, Leung K*, Leung GM. (2020) Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet. DOI: 10.1016/S0140-6736(20)30260-9
  7. Leung K, Lipsitch M, Yuen KY, Wu JT. (2017) Monitoring the fitness of antiviral-resistant influenza strains during an epidemic: a mathematical modelling study. The Lancet Infectious Diseases, 17(3), 339-347. DOI: http://dx.doi.org/10.1016/S1473-3099(16)30465-0
  8. Wu JT, Leung K, Lam TT, Ni MY, Wong CK, Peiris JM, Leung GM. Nowcasting epidemics of novel pathogens: lessons from COVID-19. Nature Medicine. 2021 Mar;27(3):388-95. DOI: 10.1038/s41591-021-01278-w
  9. Leung K*, Jit M*, Lau EHY, Wu JT. (2017) Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Scientific Reports, 7(1), 7974. DOI: http://dx.doi.org/10.1038/s41598-017-08241-1
  10. Wu JT, Leung K, Perera RAPM, Chu DKW, Lee CK, Hung IFN, et al. (2014) Inferring influenza infection attack rate from seroprevalence data. PLoS Pathogens 10(4), e1004054. DOI: https://doi.org/10.1371/journal.ppat.1004054

*Co-first author