Evidence map›Paper›PMID 34631358›Full record

ArticleHealth and technology2021

Optimizing planning and design of COVID-19 drive-through mass vaccination clinics by simulation.

Ali Asgary, Mahdi M Najafabadi, Sarah K Wendel, Daniel Resnick-Ault, Richard D Zane, Jianhong Wu

Abstract read
In one paragraph

Article in Health and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ali AsgaryDisaster & Emergency Management, York University, 4700 Keele Street, Toronto, ON M3J 1P3 Canada.ORCID 0000-0002-6253-1021
Mahdi M NajafabadiPostdoc Research Associate, City University of New York's Graduate School of Public Health, New York, NY USA.
Sarah K WendelDepartment of Emergency Medicine, University of Colorado School of Medicine, Denver, CO USA.
Daniel Resnick-AultDepartment of Emergency Medicine, University of Colorado School of Medicine, Denver, CO USA.
Richard D ZaneDepartment of Emergency Medicine, University of Colorado School of Medicine, Denver, CO USA.
Jianhong WuDepartment of Mathematics and Statistics, University Distinguished Research Professor, York University, Toronto, ON Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drive-through clinics have previously been utilized in vaccination efforts and are now being more widely adopted for COVID-19 vaccination in different parts of the world by offering many advantages including utilizing existing infrastructure, large daily throughput and enforcing social distancing by default. Successful, effective, and efficient drive-through facilities require a suitable site and keen focus on layout and process design. To demonstrate the role that high fidelity computer simulation can play in planning and design of drive-through mass vaccination clinics, we used multiple integrated discrete event simulation (DES) and agent-based modelling methods. This method using AnyLogic simulation software to aid in planning, design, and implementation of one of the largest and most successful early COVID-19 mass vaccination clinics operated by UCHealth in Denver, Colorado. Simulations proved to be helpful in aiding the optimization of UCHealth drive through mass vaccination clinic design and operations by exposing potential bottlenecks, overflows, and queueing, and clarifying the necessary number of supporting staff. Simulation results informed the target number of vaccinations and necessary processing times for different drive through station set ups and clinic formats. We found that modern simulation tools with advanced visual and analytical capabilities to be very useful for effective planning, design, and operations management of mass vaccination facilities.

Indexed as

Cabana LayoutCOVID-19Drive-throughMass VaccinationPit-Crew LayoutSimulation

Identifiers

PMID34631358
PMCPMC8492036

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.