ArticleInternational journal of environmental research and public health2021
A Drone Logistic Model for Transporting the Complete Analytic Volume of a Large-Scale University Laboratory.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- The Use of Unmanned Aerial Vehicles (UAV) on Delivering Biological Samples for COVID-19 and Tuberculosis Diagnosis: A Scoping Review.Therapeutic innovation & regulatory science · 2026Article
- Drone-Assisted Organ Transport: A Scoping Review of Clinical, Regulatory, and System Readiness.Clinical transplantation · 2025Article
- Comparative modelling of drone interventions with traditional logistics modes for expedited and equitable deliveries.Npj sustainable mobility and transport · 2025Article
- Realities of Using Drones to Transport Laboratory Samples: Insights from Attended Routes in a Mixed-Methods Study.Journal of multidisciplinary healthcare · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a model for drone transport of the complete annual analytic volume of 6.5 million analyses-(routine and emergency) between two inner-city university laboratories at Oslo University Hospital located 1.8 km apart and with a time restriction for the analyses of no more than 60 min. The total laboratory activity was analyzed per min for the complete year of 2018. The time from the clinical ordering of tests to the loading of the drone, drone transport time, and analysis time after the sample arrived at the analyzing laboratory were assessed using the lead time of emergency analyses of C-reactive protein, troponin, and the international normalized ratio. The activity had characteristic diurnal patterns, with the most intensive traffic between 8 and 12 a.m. on weekdays and there being considerably less traffic for the rest of the day, at night and on weekends. Drone schedules with departures 15-60 min apart were simulated. A maximum of 15 min between flights was required to meet the emergency demand for the analyses being completed within 60 min. The required drone weight capacity was below 3.5 kg at all times. In multiple simulations, the drone times were appropriate, whereas variations in the clinic- and laboratory-related time intervals caused violations of the allowed time 50% of the time. Drone transport with regular schedules may potentially improve the transport time compared with traditional ground transport and allow the merging of large laboratories, even when the demand for emergency analyses restricts the maximum transport time. Comprehensive economic evaluations and robust drone technology are needed before such solutions can be ready for implementation.
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