Wan Yang, PhD

  • Associate Professor of Epidemiology
212-305-0421

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Overview

Wan Yang, PhD, is a computational epidemiologist, and applies mathematical/statistical approaches in combination with data to study mechanisms governing disease systems, devise public health intervention strategies, and forecast epidemic trends. She studies transmission of infectious diseases (e.g., COVID-19, influenza, measles, mpox, and Ebola), as well as tumor kinetics and underlying causes of early-onset cancers (e.g., colorectal cancer).

Academic Appointments

  • Associate Professor of Epidemiology

Gender

  • Female

Credentials & Experience

Education & Training

  • BS, 2006 South China University of Technology
  • MS, 2009 Tsinghua University
  • PhD, 2012 Virginia Tech

Committees, Societies, Councils

2022 – present Member, Herbert Irving Comprehensive Cancer Center (HICCC)
2022 – present Member/co-lead, New York City Preparedness & Recovery Institute
2021 – present Affiliate Member, Data Science Institute, Columbia University

Editorial Boards

Editor, Epidemics (2022 - )

Research

Research Interests

  • Biostatistical Methods
  • Disease Modeling
  • Infectious Diseases

Selected Publications

1. Mohammad Mirzaei N, Hur C, Terry MB, Dalerba P, Yang W. Modeling Early-Onset Cancer Kinetics Reveals Changes in Underlying Risk and the Impact of Population Screening. Cancer Research. 2025. 2025 Aug 29. doi: 10.1158/0008-5472.CAN-25-0186.


2. Bidari S, Yuan H, Yang W. Assessing the transmissibility and outbreak risk of measles in the United States, 2024 – 2030. The Journal of Infectious Diseases 2025:jiaf342. https://doi.org/10.1093/infdis/jiaf342.

3. Yang W, Shaman J. Reconciling the efficacy and effectiveness of masking on epidemic outcomes. Journal of the Royal Society Interface. 2024. 21: 20230666. https://doi.org/10.1098/rsif.2023.0666

4. Chen K, Ma Y, Bell ML, Yang W. Canadian Wildfire Smoke and Asthma Syndrome Emergency Department Visits in New York City. The Journal of the American Medical Association (JAMA). 2023. 330 (14): 1385-1387. doi:10.1001/jama.2023.18768

5. Yang W, Shaman J. Development of Accurate Long-lead COVID-19 Forecast. PLoS Computational Biology. 2023. 19(7): e1011278. https://doi.org/10.1371/journal.pcbi.1011278

6. Yang W, Shaman J. Development of a model-inference system for estimating epidemiological characteristics of SARS-CoV-2 variants of concern. Nature Communications. 2021. 12:5573. doi: https://doi.org/10.1038/s41467-021-25913-9.

7. Yang W, Kandula S, Huynh M, Greene SK, Van Wye G, Li W, Chan HT, McGibbon E, Yeung A, Olson D, Fine A, Shaman J. Estimating the infection-fatality risk of SARS-CoV-2 in New York City during the spring 2020 pandemic wave: a model-based analysis. The Lancet Infectious Diseases. 2021. 21 (2): 203-212. Published: October 19, 2020. DOI: 10.1016/S1473-3099(20)30769-6

8. Yang W. Transmission Dynamics of and Insights from the 2018-2019 Measles Outbreak in New York City: A Modeling Study. Science Advances. 2020. 6(22):eaaz4037. doi: 10.1126/sciadv.aaz4037. DOI: 10.1126/sciadv.aaz4037

9. Yang W, Zhang W, Kargbo D, Yang R, Chen Y, Chen Z, Kamara A, Kargbo B, Kandula S, Karspeck A, Liu C, Shaman J. Transmission network of the 2014-2015 Ebola epidemic in Sierra Leone. Journal of the Royal Society Interface. 2015. 12 (112), 20150536. https://doi.org/10.1098/rsif.2015.0536

10. Yang W, Lipsitch M, Shaman J. Inference of seasonal and pandemic influenza transmission dynamics. Proceedings of the National Academy of Sciences (PNAS). 2015. 112: 2723 -2728. https://doi.org/10.1073/pnas.1415012112

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