Fast and principled simulations of the SIR model on temporal networks

TL;DR

This paper introduces a highly optimized, open-source simulation method for the SIR epidemic model on temporal networks, balancing analytical comparability with realistic contact dynamics.

Contribution

It presents a fast, principled simulation approach for the SIR model on temporal networks, including detailed assumptions and an open-source implementation.

Findings

Optimized simulation code for SIR on temporal networks

Balance between analytical tractability and realism

Discussion of assumptions and implementation details

Abstract

The Susceptible-Infectious-Recovered (SIR) model is the canonical model of epidemics of infections that make people immune upon recovery. Many of the open questions in computational epidemiology concern the underlying contact structure's impact on models like the SIR model. Temporal networks constitute a theoretical framework capable of encoding structures both in the networks of who could infect whom and when these contacts happen. In this article, we discuss the detailed assumptions behind such simulations -- how to make them comparable with analytically tractable formulations of the SIR model, and at the same time, as realistic as possible. We also present a highly optimized, open-source code for this purpose and discuss all steps needed to make the program as fast as possible.