OpenABM-Covid19 is an agent-based model (ABM) developed to simulate the spread of Covid-19 in a city and to analyse the effect of both passive and active intervention strategies. Interactions between individuals are modelled on networks representing households, work-places and random contacts. The infection is transmitted between these contacts and the progression of the disease in individuals is modelled. Instantaneous contract-tracing and quarantining of contacts is modelled allowing the evaluation of the design and configuration of digital contract-tracing mobile phone apps.
A full description of the model can be found here. A report evaluating the efficacy of various configurations of digital contract-tracing mobile phone apps can be found here and the parameters used in the report are documented here. The model was developed by the Pathogen Dynamics group, at the Big Data Institute at the University of Oxford, in conjunction with IBM UK and Faculty. More details about our work can be found at www.coronavirus-fraser-group.org .
adaptER-covid19, and economics model, is attached to the main OpenABM-Covid19 model so the economic effect of Covid-19 can be modelled jointly with the spread of the disease. More information is here.
OpenABM-Covid19 requires a C compiler (such as gcc) and the GSL libraries installed. Python installation requires Python 3.7+
cd OpenABM-Covid19/src
make all
To install the Python interface, first install SWIG, then:
make install
For developers, the following installs the Python interface inplace, so modifications to the code are applied without needing to reinstall
make dev
cd OpenABM-Covid19/src
./covid19ibm.exe <input_param_file> <param_line_number> <output_file_dir> <household_demographics_file>
where:
input_param_file
: is a csv file of parameter values (see params.h and parameters.pdf for further details of the parameters)param_line_number
: the line number of the parameter file for which to use for the simulationoutput_file_dir
: path to output directory (this directory must already exist)household_demographics_file
: a csv file from which samples are taken to represent household demographics in the model
We recommend running the model via the Python interface (see Examples section with scripts and notebooks below). Alternatively
from COVID19.model import Model, Parameters
import COVID19.simulation as simulation
params = Parameters(
input_param_file="./tests/data/baseline_parameters.csv",
param_line_number=1,
output_file_dir="./data_test",
input_households="./tests/data/baseline_household_demographics.csv"
)
params.set_param( "n_total", 10000)
model = simulation.COVID19IBM(model = Model(params))
sim = simulation.Simulation(env = model, end_time = 10 )
sim.steps( 10 )
print( sim.results )
The examples/
directory contains some very simple Python scripts and Jupyter notebooks for running the model. The examples must be run from the example directory. In particular
examples/example_101.py
- the simplest Python script for running the modelexamples/example_101.ipynb
- the simplest notebook of running the model and plotting some outputexamples/example_102.ipynb
- introduces a lock-down based upon the number of infected people and then after the lock-down turns on digital contact-tracingexamples/example_extended_output.ipynb
- a detailed notebook analysing many aspect of the model and infection transmission.examples/multi_run_simulator.py
- an example of running the model multi-threaded
A full description of the tests run on the model can be found here.
Tests are written using pytest and can be run from the main project directory by calling pytest
. Tests require Python 3.6 or later. Individual tests can be run using, for instance, pytest tests/test_ibm.py::TestClass::test_hospitalised_zero
. Tests have been run against modules listed in tests/requirements.txt in case they are to be run within a virtual environment.