AGENT-BASED SIMULATION FRAMEWORK FOR MULTI-VARIANT SURVEILLANCE

  • Sifat Afroj Moon
  • , Jiangzhuo Chen
  • , Baltazar Espinoza
  • , Bryan Lewis
  • , Madhav Marathe
  • , Joseph Outten
  • , Srinivasan Venkatramanan
  • , Anil Vullikanti
  • , Andrew Warren

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Early detection of an emerging VOC (Variant-Of-Concern) is essential for effective preparedness for a disease like COVID-19. The spreading of an emerging VOC not only depends on the disease dynamics of itself but also depends on the state of the circulating variants and the susceptibility of the population. Resources for testing are typically quite limited, and a number of strategies have been considered for deploying them. However, it has been difficult to evaluate the performance of such strategies, especially higher order effects, and inequities, while incorporating constraints on these resources. Here, we develop an agent-based surveillance framework, NETWORKDETECT, to understand the early warning system of an emerging VOC. Our framework allows us to incorporate various population heterogeneities and resource constraints.

Original languageEnglish
Title of host publication2024 Winter Simulation Conference, WSC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages276-287
Number of pages12
ISBN (Electronic)9798331534202
DOIs
StatePublished - 2024
Event2024 Winter Simulation Conference, WSC 2024 - Orlando, United States
Duration: Dec 15 2024Dec 18 2024

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Conference

Conference2024 Winter Simulation Conference, WSC 2024
Country/TerritoryUnited States
CityOrlando
Period12/15/2412/18/24

Funding

This research is supported by University of Virginia Strategic Investment Fund award number SIF160, Virginia Department of Health grant VDH-21-501-0135-1, CDC Pathogen Genomics Centers of Excellence network (PGCoE) grant 6NU50CK000555-03-01, NSF Grants OAC-1916805 (CINES), CCF-1918656 (Expeditions), IIS-1931628, IIS-1955797, and NIH grant R01GM109718. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable,world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

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