ArticleJournal of thoracic disease2022
Using discrete event simulation to optimize nucleic acid testing process for coronavirus disease 2019 (COVID-19).
Article in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 5 citations in OpenAlex.
- Within-laboratory SARS-CoV-2 real time PCR testing operations in Nepal: a simulation-based analysis.The Lancet regional health. Southeast Asia · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus-2 (SARS-CoV-2) has placed enormous diagnostic burden on hospitals and testing laboratories. It is thus critical for such facilities to optimize the diagnostic process to enable maximum testing on minimum resources. The current standard of diagnosis is the detection of the viral nucleic acid in clinical specimens. Methods: In order to optimize the laboratory's nucleic acid testing system for COVID-19, we performed a Discrete-Event-Simulation using the Arena Simulation Software to model the detection process based on the data obtained from the First Affiliated Hospital of Guangzhou Medical University (FAHGMU). The maximum of total time that specimens spent and the equipment consumption was compared under different scenarios in the model. Results: Seven scenarios were performed to simulate actual situation and improved situations. We analyzed conditions that adding a new nucleic acid extraction system (NAES), shifting a member from night duty to morning duty, using specimen tubes containing guanidine isothiocyanate (GITC), then tested the maximum testing capacity in the current number of technicians. In addition, the costs including personal protective equipment (PPE) and testing kits was calculated. Conclusions: A work schedule based on specimen-load improves efficiency without incurring additional costs, while using the specimen tubes containing GITC could reduce testing time by 30 min. In contrast, adding new NAESs or polymerase chain reaction (PCR) instruments has minimal impact on testing efficiency.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.