Evidence map›Paper›PMID 34696289›Full record

ArticleVaccines2021

A Data-Driven Digital Application to Enhance the Capacity Planning of the COVID-19 Vaccination Process.

Berend Markhorst, Tara Zver, Nina Malbasic, Renze Dijkstra, Daan Otto, Rob van der Mei, Dennis Moeke

Abstract read
In one paragraph

Article in Vaccines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Berend MarkhorstDepartment of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Tara ZverDepartment of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.ORCID 0000-0002-1563-6373
Nina MalbasicDepartment of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Renze DijkstraDepartment of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Daan OttoDepartment of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Rob van der MeiDepartment of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Dennis MoekeResearch Group Logistics & Alliances, HAN University of Applied Sciences, 6826 CC Arnhem, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a decision support system (DSS) is presented that focuses on the capacity planning of the COVID-19 vaccination process in the Netherlands. With the Dutch national vaccination priority list as the starting point, the DSS aims to minimize the per-class waiting-time with respect to (1) the locations of the medical hubs (i.e., the vaccination locations) and (2) the distribution of the available vaccines and healthcare professionals (over time). As the user is given the freedom to experiment with different starting positions and strategies, the DSS is ideally suited for providing support in the dynamic environment of the COVID-19 vaccination process. In addition to the DSS, a mathematical model to support the assignment of inhabitants to medical hubs is presented. This model has been satisfactorily implemented in practice in close collaboration with the Dutch Municipal and Regional Health Service (GGD GHOR Nederland).

Indexed as

COVID-19decision support systemlast-milevaccination logisticsvaccination planning

Identifiers

PMID34696289
PMCPMC8540361

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.