Getting Started

Dependencies

• Python >= 3.2

• Numpy

• Sklearn

• Scipy

Installation

Open-SIR and all its dependencies can be installed from the repository using pip:

git clone https://github.com/open-sir/open-sir.git
cd open-sir
pip install .

In order to unintall Open-SIR simply execute:

pip uninstall opensir

Usage example

Command line interface

It’s possible to run the model using the CLI:

usage: opensir-cli [-h] [-m {sir,sirx}] [-t TIME] [-f FILE] [-s] [-d DELIMITER]

Run SIR or SIR-X model given a set of initial conditions and model parameters.

optional arguments:
  -h, --help            show this help message and exit
  -m {sir,sirx}, --model {sir,sirx}
  -t TIME, --time TIME  Number of days for the simulation
  -f FILE, --file FILE  Name of the input file. If missing, the input file is read from STDIN
  -s, --suppress_header
                        Suppress CSV header
  -d DELIMITER, --delimiter DELIMITER
                        CSV delimiter

The input file is a TOML file with the following format

[initial_conds]
<cond> = value

[parameters]
<param> = value

For example, You can use Open-SIR to create a 6 days prediction of the number of susceptible (S), infected (I) and removed (R) population. The initial conditions represent Ealing data as of 04/04/2020. The parameters provide a prediction in the hypothetical case that no lockdown would be taking place.

[initial_conds]
S0 = 341555
I0 = 445
R0 = 0

[parameters]
alpha = 0.95
beta = 0.38

Then, it’s possible to run the model with T=6 days:

opensir-cli --model sir --time 6 --file input_file.txt

Or reading the input file from STDIN:

cat input_file | opensir-cli --model sir --time 6

The output of opensir-cli is a .csv file with the output of the model.

Note

Note: On Windows, the CLI must be run from Powershell or any bash shell such as Git BASH

Python API

You can replicate the predictions of the CLI with the following python script:

from opensir.models import SIR
my_sir = SIR() # Initialize an empty SIR model
params = [0.95, 0.38] # Define model parameters (alpha, beta)
w0 = [341555, 445, 0] # Define initial conditions (S0, I0, R0)
my_sir.set_params(p=params, initial_conds=w0) # Set model parameters
n_days = 6 # Define the amount of days to predict
my_sir.solve(n_days, n_days+1) # Call model.solve functions
sol = my_sir.fetch() # Fetch model solution

Try the Jupyter Notebook

Open and run the Jupyter Notebook to:

• Get an overview of the SIR model

• Explore case studies

And learn how the API can be used to:

• Build compartmental models

• Fit parameters to existing data

• Predict susceptible, infected and removed population

• Calculate confidence intervals of the predictions