Evidence map›Paper›PMID 40348837›Full record

ArticleScientific reports2025

Developing an intuitive decision support system for equitable vaccine distribution during pandemics.

Lise Boey, Hossein Baharmand, Ross Owen Phillips, Nico Vandaele, Burcu Balcik, Jan Ove Kjøndal, Asle Birkeland, Håvard Fossli, Naima Saeed, Catherine Decouttere

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Lise BoeyAccess-To-Medicines Research Centre, KU Leuven, Leuven, Belgium.
Hossein BaharmandSchool of Business and Law, University of Agder, Grimstad, Norway. hossein.baharmand@uia.no.
Ross Owen PhillipsNorwegian Centre for Transport Research (TøI), Oslo, Norway.
Nico VandaeleAccess-To-Medicines Research Centre, KU Leuven, Leuven, Belgium.
Burcu BalcikDepartment of Industrial Engineering, Özyeğin University, Istanbul, Turkey.
Jan Ove KjøndalAgens, Oslo, Norway.
Asle BirkelandAgens, Oslo, Norway.
Håvard FossliAgens, Oslo, Norway.
Naima SaeedSchool of Business and Law, University of Agder, Grimstad, Norway.
Catherine DecouttereAccess-To-Medicines Research Centre, KU Leuven, Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective organization of the vaccine supply chain is vital to achieve high vaccination rates in pandemics. This paper presents a novel approach for developing a decision support system (DSS) to support health officials and policymakers who must make timely and impactful decisions with limited information for distributing vaccines. We combine a stakeholder-informed systems approach for problem definition with a user-centered design approach for DSS development. The methodology has been tested during the COVID-19 pandemic. We used system modeling to capture stakeholders' knowledge, experience, and learnings from the H1N1 pandemic, leading us to focus on the central vaccine allocation problem (CVAP), which involves determining the number of vaccines allocated to each municipality in an equitable way. We designed a dashboard that embedded a mathematical model as a DSS for in-country CVAP during a pandemic. A Lightning Decision Jam workshop was conducted to define the DSS's characteristics, with the visualization of scenarios and decision-making transparency being key features during the development process. We validated the DSS with policymakers and built it for the Norwegian context, with flexibility for adaptation to other regions, particularly those still grappling with high vaccine supply deficits. Our approach offers a novel and practical way to develop DSSs to support policymakers making critical decisions during pandemics.

Indexed as

COVID-19COVID-19 VaccinesDecision Support TechniquesPandemicsVaccinesHumansInfluenza A Virus, H1N1 SubtypeModels, TheoreticalNorwaySARS-CoV-2VaccinationCOVID-19 VaccinesVaccinesCOVID-19Decision-support systemSystem dynamicsUser-centered approachVaccine supply chain

Identifiers

PMID40348837
PMCPMC12065852

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.