An Integrated Epidemic Simulation Workflow for Submodular Intervention Strategies

Fuente: arXiv
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Main Authors: Barik, Reet, Minutoli, Marco, Halappanavar, Mahantesh, Kalyanaraman, Ananth
Format: Preprint
Published: 2024
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author Barik, Reet
Minutoli, Marco
Halappanavar, Mahantesh
Kalyanaraman, Ananth
author_facet Barik, Reet
Minutoli, Marco
Halappanavar, Mahantesh
Kalyanaraman, Ananth
contents Owing to the ongoing COVID-19 pandemic and other recent global epidemics, epidemic simulation frameworks are gaining rapid significance. In this work, we present a workflow that will allow researchers to simulate the spread of an infectious disease under different intervention schemes. Our workflow is built using the Covasim simulator for COVID-19 alongside a network-based PREEMPT tool for vaccination. The Covasim simulator is a stochastic agent-based simulator with the capacity to test the efficacy of different intervention schemes. PREEMPT is a graph-theoretic approach that models epidemic intervention on a network using submodular optimization. By integrating the PREEMPT tool with the Covasim simulator, users will be able to test network diffusion based interventions for vaccination. The paper presents a description of this integrated workflow alongside preliminary results of our empirical evaluation for COVID-19.
format Preprint
id arxiv_https___arxiv_org_abs_2411_05243
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An Integrated Epidemic Simulation Workflow for Submodular Intervention Strategies
Barik, Reet
Minutoli, Marco
Halappanavar, Mahantesh
Kalyanaraman, Ananth
Social and Information Networks
Owing to the ongoing COVID-19 pandemic and other recent global epidemics, epidemic simulation frameworks are gaining rapid significance. In this work, we present a workflow that will allow researchers to simulate the spread of an infectious disease under different intervention schemes. Our workflow is built using the Covasim simulator for COVID-19 alongside a network-based PREEMPT tool for vaccination. The Covasim simulator is a stochastic agent-based simulator with the capacity to test the efficacy of different intervention schemes. PREEMPT is a graph-theoretic approach that models epidemic intervention on a network using submodular optimization. By integrating the PREEMPT tool with the Covasim simulator, users will be able to test network diffusion based interventions for vaccination. The paper presents a description of this integrated workflow alongside preliminary results of our empirical evaluation for COVID-19.
title An Integrated Epidemic Simulation Workflow for Submodular Intervention Strategies
topic Social and Information Networks
url https://arxiv.org/abs/2411.05243