From Epidemic to Pandemic Modelling

TL;DR

This paper introduces a systematic methodology for extending basic epidemic models into multilevel, multiscale pandemic models using coloured Petri nets, enabling detailed, scalable, and reusable simulations with a user-friendly platform.

Contribution

It presents a novel approach for building complex pandemic models with Petri nets, supporting deterministic, stochastic, and hybrid simulations, and provides a publicly available platform for model construction and analysis.

Findings

Supports multilevel, multiscale pandemic modeling

Enables visual, scalable, and reusable model construction

Provides reproducible models with analysis tools

Abstract

We present a methodology for systematically extending epidemic models to multilevel and multiscale spatio-temporal pandemic ones. Our approach builds on the use of coloured stochastic and continuous Petri nets facilitating the sound component-based extension of basic SIR models to include population stratification and also spatio-geographic information and travel connections, represented as graphs, resulting in robust stratified pandemic metapopulation models. This method is inherently easy to use, producing scalable and reusable models with a high degree of clarity and accessibility which can be read either in a deterministic or stochastic paradigm. Our method is supported by a publicly available platform PetriNuts; it enables the visual construction and editing of models; deterministic, stochastic and hybrid simulation as well as structural and behavioural analysis. All the models are available as supplementary material, ensuring reproducibility.