Estimation of superspreading dispersion
This repository contains a simplified version of the code used in https://www.medrxiv.org/content/10.1101/2021.01.15.21249870v1.
The code makes maximum likelihood estimates of the basic reproduction number R0 and dispersion parameter k of simulated data (a simple simulation code is also included).
Running the code
python simulation.py
python estimate_r0_k.pyDescription
The Bayesian log likelihood model is defined in model.py.
The script estimate_r0_k.py is a simple wrapper
that looks for maximum likelihood estimates for scalar R0 and k.
For more details, see the paper.