TY - JOUR
T1 - A Discrete Event Simulation-Based Model to Optimally Design and Dimension Mobile COVID-19 Saliva-Based Testing Stations
AU - Saidani, Michael
AU - Kim, Harrison Hyung Min
N1 - Funding Information:
This work is supported by Humanities and Social Science Project of Hubei Education Department (No.17G079) and Youth Foudation Wuhan Donghu University (No.2017dhsk004).
Funding Information:
Affiliation: 1. (D. LI) Economics Department, Wuhan Donghu University; 301 Wenhua Ave, Jiangxia District, Wuhan City, Hubei, China 430212; 2. (X. HE) Business Department, Wuchang Technology University, 16 Jiangxia Ave, Wuchang, Wuhan, Hubei, China 430223 Email Address: (X. HE) [email protected]; Or Email: [email protected] First Published by: 15 April 2018 Peer Reviewer: Prof. Hu Xueping, teaching in Zhongnan University of Economics and Law. His main research area covers at logistics and supply chain management, green development, problems of migrant workers. Funding Resources: Humanities and Social Science Project of Hubei Education Department (No.17G079) and Youth Foundation Wuhan Donghu University (No.2017dhsk004). Keywords: Agricultural Informatization; Restriction Factors; Countermeasures; Hubei Province
Publisher Copyright:
Copyright © 2021 Society for Simulation in Healthcare.
PY - 2021/4/1
Y1 - 2021/4/1
N2 - 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.
AB - 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.
KW - Discrete event simulation
KW - resource allocation
KW - resource efficiency
KW - optimization
KW - testing stations
KW - COVID-19
UR - http://www.scopus.com/inward/record.url?scp=85103682064&partnerID=8YFLogxK
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U2 - 10.1097/SIH.0000000000000565
DO - 10.1097/SIH.0000000000000565
M3 - Article
C2 - 33600140
SN - 1559-2332
VL - 16
SP - 151
EP - 152
JO - Simulation in Healthcare
JF - Simulation in Healthcare
IS - 2
ER -