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README.md
covid19model
Code for modelling estimated deaths and cases for COVID19 from Report 13 published by MRC Centre for Global Infectious Disease Analysis, Imperial College London: Estimating the number of infections and the impact of nonpharmaceutical interventions on COVID-19 in 11 European countries
Version 2 Release
In this update we extend our original model to include (a) population saturation effects, (b) prior uncertainty on the infection fatality ratio and (c) a more balanced prior on intervention effects. We also (d) included another 3 countries (Greece, the Netherlands and Portugal). The updated technical detail is available here.
You can directly look at our results here
This repository has code for replication purposes. The bleeding edge code and advancements are done in a private repository. Ask report authors for any collaborations.
Contributing
We welcome all potential collaborators and contributors from the wider community. Please see contributing for more details.
Installing dependencies
Using Conda
An environment.yml file is provided and can be used to build a virtual
environment containing all model dependencies. Create the environment using:
conda env create -f environment.yml
Then activate the environment for use:
conda activate covid19model
Using Docker
A Docker image providing all model dependencies is available. See docker/README.md for details of running the model with Docker.
Other
If you wish to install packages into your native R environment or with a system
package manager please see environment.yml for a full list of dependencies.
How to run the code
There are two ways to run our code:-
- Open the rstudio project covid19model.Rproj file in rstudio and run/source base.r file
- To run from commandline please enter the cloned directory and type 'Rscript base.r base' in terminal
Results
- The results are stored in two folders results and figures.
- Results has the stored stan fits and data used for plotting
- Figures have the images with daily cases, daily death and Rt for all countries.
Notice
- Please note to not make you wait for long we have by default run sampling for short period. For proper estimates please uncomment the line 202 and comment out line 203. This will run sampling for 4000 iterations with 2000 warmups and 4 chains.
- Python code is right now not updated and won't work. Python code is good for only version 1 model and data.