Evidence map›Paper›PMID 36292549›Full record

ArticleHealthcare (Basel, Switzerland)2022

Unmanned Aerial Vehicle in the Logistics of Pandemic Vaccination: An Exact Analytical Approach for Any Number of Vaccination Centres.

Adnan Benayad, Olaf Malasse, Hicham Belhadaoui, Noureddine Benayad

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Adnan BenayadLaboratory of Computer Networks, Telecommunications and Multimedia, ESTC, Hassan II University, B.P. 8012 Oasis, Casablanca 20000, Morocco.
Olaf MalasseLaboratoire LCFC, National School of Arts and Crafts, ParisTech, 57070 Metz, France.
Hicham BelhadaouiLaboratory of Computer Networks, Telecommunications and Multimedia, ESTC, Hassan II University, B.P. 8012 Oasis, Casablanca 20000, Morocco.
Noureddine BenayadLaboratory of PHEMaC, Faculty of Sciences-Ain Chock, Hassan II University, B.P. 5366 Maarif, Casablanca 20000, Morocco.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the development and manufacture of pandemic vaccines is a daunting task, the greatest challenge lies in how to deliver these vaccines to billions of people around the world. This requires an efficient strategy of deliveries, at constrained costs and deadlines. This paper proposes an exact analytical approach and operational strategy to the logistics of any pandemic vaccination efforts, applicable both to sparsely populated areas or deficient infrastructure, and to very dense urban fabrics where mobility is highly constrained. Our strategy consists in dividing the territory concerned into zones and districts in a concentric way. We opt for the use of unmanned aerial vehicles to free ourselves from land constraints. This involves serving, from a logistics centre (central depot), any number n of vaccination centres, while optimizing costs and deadlines. We have determined all equivalent and optimal flight path plans for a fixed and optimal number of drones, which depend on domain D(d); d being the demand of vaccination centers. The analysis of the results led us to define what we will call the "degeneracy of domain D". All our results are expressed as a function of the parameter n.

Indexed as

degeneracydrone deliveryequivalent graphsexact analytical approachoptimal flight pathpandemic vaccinationroute planning problemunmanned aerial vehicle (UAV)

Identifiers

PMID36292549
PMCPMC9602990

What OpenQuestion holds

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Registered trials

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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.