Modeling Epidemic Spread in Large Cities Using Public Transportation Data

Last updated on Aug 27, 2024
  • Developed a data-driven epidemiological model to assess the impact of human mobility on the spread of COVID-19
  • Calibrated the epidemic model with census and mobility data involving subway transit
  • Estimated the governing epidemic parameters that enable predictions of spread under different diffusion prevention strategies
  • Evaluated the impact of various policies, such as the mask mandates and lockdown to the pandemic spread
  • Predicted accurately the daily cases in NYC with the developed model and the mobility data

Download the paper for this project: Mobility

Network Science
Bowen Gong
Bowen Gong
Quant Software Developer in Citibank

My research interests include Network Science, Machine Learning, Natural Language Processing, Parallel Computing.

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