Evidence map›Paper›PMID 40874132›Full record

ArticleNpj sustainable mobility and transport2025

Comparative modelling of drone interventions with traditional logistics modes for expedited and equitable deliveries.

Andy Oakey, Matt Grote, Aliaksei Pilko, Jakub Krol, Alexander Blakesley, Tom Cherrett, Antonio Martinez-Sykora, Bani Anvari

Abstract read
In one paragraph

Article in Npj sustainable mobility and transport, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Andy OakeyUniversity of Southampton, Southampton, UK.
Matt GroteUniversity of Southampton, Southampton, UK.
Aliaksei PilkoUniversity of Southampton, Southampton, UK.
Jakub KrolUniversity College London, London, UK.
Alexander BlakesleyUniversity College London, London, UK.
Tom CherrettUniversity of Southampton, Southampton, UK.
Antonio Martinez-SykoraUniversity of Southampton, Southampton, UK.
Bani AnvariUniversity College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uncrewed Aerial Vehicles (UAVs/drones) for deliveries have become a key consideration for logistics planners, particularly in the healthcare industry. Despite reported theoretical cost and speed benefits, few systems have realised long-term financially sustainable operations. This paper explores UAVs in a multi-mode logistics system (vans, UAVs, bicycles) using medical sample delivery case studies in the United Kingdom, and a computational model that accounts for routing, landing restrictions, costs, and payload constraint practicalities. Results identified potential transit time reductions of up to 90% using UAVs, though costs increased significantly (+133%). Achieving these time savings required UAV access to all sites and residents tolerating up to 40 flight movements per hour. Other time savings were possible with partial or no UAV uptake; however, all expedited solutions increased costs, raising the question of the value of such time savings, and whether any benefits would materialise, given onward supply chain limitations and changeable weather.

Indexed as

EngineeringGeographyOperational researchScience, technology and societySocial policy

Identifiers

PMID40874132
PMCPMC12378082

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.