Python-Growth rate estim: Reproducible model for: "Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England” (2022)

growth-rate-estim

Reproducible model for: "Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England” (2022).

Language: R.

To see an example to run the model, go to main.R (it runs the model for the validation section).

Main functions:

  • setParametersFn(): sets up the main parameters of the model (e.g. priors).
  • runModelGrowthRate(): runs the model for the data in countTable.

Requires the following packages:

  • data.table.
  • INLA.
  • ggplot2.

Comments

  • Paper code
    Paper code

    Jan 11, 2022

    Hi,

    Thanks for sharing this code. I enjoyed reading the preprint. Could you point me in the direction of the code reproducing the analysis in the paper (i.e the case study). I'm particularly interested in understanding more on the comparison you did between your case count model and your test positive model.

    Sam

    Reply