A Discrete Event Simulation-Based Model to Optimally Design and Dimension Mobile COVID-19 Saliva-Based Testing Stations

Michael Saidani, Harrison Hyung Min Kim

Research output: Contribution to journalArticlepeer-review

Abstract

The present COVID-19 brief report addresses: (1) the problem of optimal design and resource allocation to mobile testing stations to ensure rapid results to the persons getting tested; (2) the proposed solution through a newly developed discrete event simulation model, experienced in on-campus saliva-based testing stations at the University of Illinois at Urbana-Champaign; and (3) the lessons learned on how 10,000 samples (from noninvasive polymerase chain reaction COVID-19 tests) can be processed per day on campus, as well as how the model could be reused or adapted to other contexts by site managers and decision makers.
Original languageEnglish (US)
Pages (from-to)151-152
Number of pages2
JournalSimulation in Healthcare
Volume16
Issue number2
DOIs
StatePublished - Apr 1 2021

Keywords

  • Discrete event simulation
  • resource allocation
  • resource efficiency
  • optimization
  • testing stations
  • COVID-19

ASJC Scopus subject areas

  • Education
  • Epidemiology
  • Medicine (miscellaneous)
  • Modeling and Simulation

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