Evidence map›Paper›PMID 42270707›Full record

ArticleScientific reports2026

How stakeholder requirements constrain drone-based medical delivery: probabilistic sizing of eVTOL aircraft at high altitude.

Victor Alulema, Gloria Acosta-Vargas, Cesar Guevara, Patricia Acosta-Vargas

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 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

4 authors.

Victor AlulemaDepartment of Mechanical Engineering, Laboratory of Unmanned Aerial Systems (LUAS-EPN), ATA Research Group, Escuela Politécnica Nacional, Quito, 170143, Ecuador.
Gloria Acosta-VargasMedicine Faculty, Pontificia Universidad Católica del Ecuador, Quito, 170143, Ecuador.
Cesar GuevaraQuantitative Methods Department, CUNEF University, Madrid, 28040, Spain.
Patricia Acosta-VargasIntelligent and Interactive Systems Laboratory, Ingeniería Industrial, FICA, Universidad de Las Américas, Quito, 170125, Ecuador. patricia.acosta@udla.edu.ec.

Funding

Universidad de Las Américas Ecuador 489.A.XIV.24
6 · The paper itself

Abstract

Drone-based medical delivery can overcome geographic barriers to healthcare in highland regions, but designing aircraft for this mission requires navigating uncertainty that originates outside engineering: physicians define cold-chain requirements, regulators mandate safety systems, and health planners set delivery speed targets, each imposing design penalties whose magnitudes are uncertain. No existing aircraft sizing framework propagates this requirement-origin uncertainty alongside classical technological uncertainty. Here we introduce Requirement Impact Kits (RIKs)-composable modules with uncertain engineering coefficients-within a three-level probabilistic framework that distinguishes requirement-scenario, engineering-translation, and parameter-level uncertainty. Applied to eVTOL medical delivery at 2,800 m altitude in the Quito Metropolitan District, comparing Lift+Cruise, Tilt-Rotor, and Multirotor architectures, the framework reveals that stakeholder decisions dominate the design space: demanding urgent delivery reduces aircraft feasibility by 24 percentage points-four times the impact of adding cold-chain thermal management. Sobol sensitivity decomposition shows that 98% of parameter-level variance is epistemic and reducible through rotor testing, while battery energy density contributes less than 2%. The Lift+Cruise architecture achieves the highest robustness, and an altitude-cruise speed feasibility map provides health system planners with a quantitative tool for negotiating delivery time requirements against operational reliability.

Indexed as

AircraftAltitudeDelivery of Health CareHumansUncertaintyEVTOL sizingMedical delivery UAVProbabilistic designRequirement analysisSobol sensitivity analysisUncertainty quantification

Identifiers

PMID42270707
PMCPMC13500619

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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.