Rejection-Based Epidemic Simulation for Complex Networks

Overview

Implementation of Monte-Carlo (Gillespie) simulation for epidemic type processes on complex networks.

Installation

Install Rust with:

curl https://sh.rustup.rs -sSf | sh

Compile the Rust code (in the rust_reject folder) with:

cd rust_reject && cargo build --release

Usage

Start the SIS simulation with

./rust_reject/target/release/rust_reject example_networks/gamma_2.0_nodes_1000.txt out_trajectory.txt

where the first argument is the input network and the second argument is the output-filepath.

Network File

The network file contains containing a labeled graph specifying the initial state, each line having the form <Nodeid>;<Label>;<Neighbor1>,<Neighbor2>,...

0;I;31,29,94,13,83
1;S;66,15,73
2;S;29,61,26,80,16,83,30,62,3,93,27,87,68,18,79,6
3;I;83,2,29,4,28,61,46,21,9,49,41,68,16,74
4;S;82,28,12,83,3,62,66,68
...

Nodes start with id 0 and are sorted. Isolates (nodes withouth neighbors) are not supported (yet). There should be at least one node for each possible label.

Rates

Currently, it is only possible to specify the rate parameters directly in the main.rs source file:

const RECOVERY_RATE: f64 = 1.0;
const INFECTION_RATE: f64 = 0.6;
const HORIZON: f64 = 10.0;
const SAVEINTERVAL: usize = 1000;

SAVEINTERVAL specifies the time resolution of the output.

SIR and Competing Pathogens Model

To use one of the other models simply rename them to main.rs.