Simulation-enabled Evaluation of Operational Strategies at Shield Illinois Depot for Efficient Disease Testing
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| Vydáno v: | IISE Annual Conference. Proceedings (2025), p. 1-4 |
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Institute of Industrial and Systems Engineers (IISE)
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| On-line přístup: | Citation/Abstract Full Text Full Text - PDF |
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MARC
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| 001 | 3243713107 | ||
| 003 | UK-CbPIL | ||
| 024 | 7 | |a 10.21872/2025IISE_6412 |2 doi | |
| 035 | |a 3243713107 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 102209 |2 nlm | ||
| 100 | 1 | |a Khan, Md Abu Naeem |u Department of Industrial and Systems Engineering, Northern Illinois University, USA | |
| 245 | 1 | |a Simulation-enabled Evaluation of Operational Strategies at Shield Illinois Depot for Efficient Disease Testing | |
| 260 | |b Institute of Industrial and Systems Engineers (IISE) |c 2025 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a SHIELD Illinois launched a statewide, saliva-based COVID-19 testing network that reaches 1,700 schools, colleges and universities in Illinois. The depot was essential to this operation; it served as the central distribution hub daily routing thousands of samples to testing laboratories across the state. Depot operations were heavily impacted at the peak of their pandemic, owing to an extremely erratic arrival pattern of samples and a manual dispatching system, thus often leading to inefficiencies and longer cycle times. This case study simulates routing strategics, assessing their impact on travel times, resource requirements and cycle times from collection to results. Through simulations tests, this study aims to obtain optimal dispatch strategies that will make operation more efficient and consistent thereby minimizing delays. The findings of this research will provide valuable insights into future logistics for large-scale public health responses to epidemics. | |
| 651 | 4 | |a United States--US | |
| 651 | 4 | |a Illinois | |
| 653 | |a Simulation | ||
| 653 | |a Testing laboratories | ||
| 653 | |a Public health | ||
| 653 | |a Decision making | ||
| 653 | |a Pandemics | ||
| 653 | |a Epidemics | ||
| 653 | |a Travel time | ||
| 653 | |a Cycle time | ||
| 653 | |a Distribution centers | ||
| 653 | |a Inventory control | ||
| 653 | |a COVID-19 diagnostic tests | ||
| 653 | |a Logistics | ||
| 653 | |a Workloads | ||
| 653 | |a Efficiency | ||
| 653 | |a COVID-19 | ||
| 653 | |a Case studies | ||
| 700 | 1 | |a Wang, Ziteng |u Department of Industrial and Systems Engineering, Northern Illinois University, USA | |
| 773 | 0 | |t IISE Annual Conference. Proceedings |g (2025), p. 1-4 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243713107/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3243713107/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243713107/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |