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  1. 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 improvementmore »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.« less
  2. 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 specified, and the system computes multi-contagion dynamics over time. This is a significant improvement over simulationmore »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.« less
  3. We describe a software system called ExecutionManager (abbreviated EM) that controls the execution of third-party software (TPS) for analyzing networks. Based on a configuration file that contains a specification for the execution of each TPS, the system launches any number of stand-alone TPS codes, if the projected execution time and the graph size are within user-imposed limits. A system capability is to estimate the running time of a TPS code on a given network through regression analysis, to support execution decision-making by EM. We demonstrate the usefulness of EM in generating network structure parameters and distributions, and in extracting meta-datamore »information from these results. We evaluate its performance on directed and undirected, simple and multi-edge graphs that range in size over seven orders of magnitude in numbers of edges, up to 1.5 billion edges. The software system is part of a cyberinfrastructure called net.science for network science.« less
  4. Contagion dynamics on networks are used to study many problems, including disease and virus epidemics, incarceration, obesity, protests and rebellions, needle sharing in drug use, and hurricane and other natural disaster events. Simulators to study these problems range from smaller-scale serial codes to large-scale distributed systems. In recent years, Python based simulation systems have been built. In this work, we describe a new Python-based agent-based simulator called CSonNet. It differs from codes such as Epidemics on Networks in that it performs discrete time simulations based on the graph dynamical systems formalism. CSonNet is a parallel code; it implements concurrency throughmore »an embarrassingly parallel approach of running multiple simulation instances on a user-specified number of forked processes. It has a modeling framework whereby agent models are composed using a set of pre-defined state transition rules. We provide strong-scaling performance results and case studies to illustrate its features.« less