Evidence map›Paper›PMID 34458722›Full record

ArticleTransportation research interdisciplinary perspectives2021

A simulation-based analysis for effective distribution of COVID-19 vaccines: A case study in Norway.

Xu Sun, Eugenia Ama Andoh, Hao Yu

Open access · goldAbstract read
In one paragraph

Article in Transportation research interdisciplinary perspectives, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
9.9field-weighted citation impact, top 2% of its field
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

16 citing papers in PubMed, 64 citations in OpenAlex.

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  5. Inequality in COVID-19 vaccination in Africa.Journal of public health in Africa · 2023
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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

3 authors at 1 institution in 1 country.

Xu SunDepartment of Industrial Engineering, UiT The Arctic University of Norway, Lodve Langesgate 2, Narvik 8514, Norway.
Eugenia Ama AndohDepartment of Industrial Engineering, UiT The Arctic University of Norway, Lodve Langesgate 2, Narvik 8514, Norway.
Hao YuDepartment of Industrial Engineering, UiT The Arctic University of Norway, Lodve Langesgate 2, Narvik 8514, Norway.
UiT The Arctic University of Norway · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since December 2020, the vaccines from several manufacturers, e.g., Pfizer/BioNTech, Moderna, etc., have been approved for mass vaccination to control the COVID-19 pandemic, which has caused more than 100 million infections and 2.4 million deaths. These vaccines are produced and transported in large quantities to suffice the needs of several countries. Before arriving at the end-users, the vaccines need to be stored at extremely low temperatures and distributed through reliable cold chain logistics networks. Thus, the timely and cost-effective distribution of COVID-19 vaccines via cold chain logistics has become a complex operational challenge. In this paper, we develop a simulation-based approach combining both route optimization and dynamic simulation to improve the logistics performance for COVID-19 vaccine distribution. A state-of-the-art simulation package called anyLogistix is used to perform a real-world case study in Norway. With the data of periodic vaccine demands, customer and warehouse locations, vehicle-related costs and emissions, and expected service levels, implications are obtained based on the analysis of several scenarios. Our experimental results reveal that the service level, cost-effectiveness, environmental performance, and equity of a cold chain vaccine logistics system can be significantly influenced by the fleet size, the fleet composition, the type of vehicle used, and the route optimization. Thus, these factors need to be holistically considered in the planning of an effective COVID-19 vaccine distribution system.

Indexed as

Cold chain logisticsCOVID-19 vaccinesSimulationVaccine distributionVaccine logisticsVaccine supply chain

Identifiers

PMID34458722
PMCPMC8382586
OpenAlexW3196238930

What OpenQuestion holds

Textmetadata
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.