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Title: A Framework for Simulating Multiple Contagions Over Multiple Networks
Many contagion processes evolving on populations do so simultaneously, interacting over time. Examples are co-evolution of human social processes and diseases, such as the uptake of mask wearing and disease spreading. Commensurately, multi-contagion agent-based simulations (ABSs) that represent populations as networks in order to capture interactions between pairs of nodes are becoming more popular. In this work, we present a new ABS system that simulates any number of contagions co-evolving on any number of networked populations. Individual (interacting) contagion models and individual networks are speci ed, and the system computes multi-contagion dynamics over time. This is a signi cant improvement over simulation frameworks that require union graphs to handle multiple networks, and/or additional code to orchestrate the computations of multiple contagions. We provide a formal model for the simulation system, an overview of the software, and case studies that illustrate applications of interacting contagions.  more » « less
Award ID(s):
1918656 1916805
NSF-PAR ID:
10300632
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Complex Networks and Their Applications
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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