Evidence map›Paper›PMID 39309669›Full record

ArticleNaval research logistics2024

Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.

Shibshankar Dey, Ali Kaan Kurbanzade, Esma S Gel, Joseph Mihaljevic, Sanjay Mehrotra

Abstract read
In one paragraph

Article in Naval research logistics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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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

5 authors.

Shibshankar DeyDepartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.
Ali Kaan KurbanzadeDepartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.
Esma S GelDepartment of Supply Chain Management and Analytics, University of Nebraska-Lincoln, Lincoln, NB, USA.
Joseph MihaljevicSchool of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA.
Sanjay MehrotraDepartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.

Funding

EpiMoRPH: A simulation environment for generating spatially-refined intervention strategies for the control of infectious diseaseR01AI168144 · NIAID · NORTHERN ARIZONA UNIVERSITY · PI Joseph Mihaljevic · 2022 to 2026
$3.5M
NIAID NIH HHS R01 AI168144
6 · The paper itself

Abstract

During various stages of the COVID-19 pandemic, countries implemented diverse vaccine management approaches, influenced by variations in infrastructure and socio-economic conditions. This article provides a comprehensive overview of optimization models developed by the research community throughout the COVID-19 era, aimed at enhancing vaccine distribution and establishing a standardized framework for future pandemic preparedness. These models address critical issues such as site selection, inventory management, allocation strategies, distribution logistics, and route optimization encountered during the COVID-19 crisis. A unified framework is employed to describe the models, emphasizing their integration with epidemiological models to facilitate a holistic understanding. This article also summarizes evolving nature of literature, relevant research gaps, and authors' perspectives for model selection. Finally, future research scopes are detailed both in the context of modeling and solutions approaches.

Indexed as

COVID-19 vaccine managementepidemiological modelingmathematical modelingreview

Identifiers

PMID39309669
PMCPMC11412613

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.