Estimation of superspreading dispersion

This repository contains a simplified version of the code used in https://www.nature.com/articles/s41598-021-03126-w

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.py

Description

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.