/COVID-19

Primary LanguageJupyter Notebook

COVID-19

References:

  • Li, J. (2020). A Robust Stochastic Method of Estimating the Transmission Potential of 2019-nCoV. arXiv preprint arXiv:2002.03828.
  • Wu, J. T., Leung, K., & Leung, G. M. (2020). Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet.
  • Imai, N., Dorigatti, I.,Cori, A., Riley, S., & Ferguson, N. M. (2020). Estimating the potential total number of novel Coronavirus cases in Wuhan City, China. Imperial College London, 17.

Current Progress:

March. 02. 2020 Simulating the Epidemic Process with estimated flow between provinces, adding individual quarantine effects.
Current Parameters:

  • alpha: The rate at which an exposed person becomes infective. 1/7

  • beta: The parameter controlling how often a susceptible-infected contact results in a new exposure. 0.65

  • gamma:The rate an infected recovers and moves into the resistant phase.0.135

  • R0:beta/gamma

  • Mobility Factor: 85% meaning 85% of the peak flow between governments

  • Simulation Starts with assumption: Hubei has one person get exposed to the virus at Day 1.

  • Number of beds available for each province : this parameter subjective to many other variables' impact

  • total population: 2018 census

  • flow matrix between cities: simulation

Current Visualization: output/kepler.html (drag the time bar to see the transition)

Data is from DXY-COVID-19-Data