Evidence map›Paper›PMID 41663505›Full record

ArticleScientific reports2026

A multi-phase, multi-method assessment of national COVID-19 vaccination performance with equity analysis.

Mohammadreza Rasouli, Amirreza Salehi, Majid Rafiee, Omid Fatahi Valilai

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mohammadreza RasouliDepartment of Industrial Engineering, Sharif University of Technology, Tehran, Iran.
Amirreza SalehiDepartment of Industrial Engineering, Sharif University of Technology, Tehran, Iran.
Majid RafieeDepartment of Industrial Engineering, Sharif University of Technology, Tehran, Iran. rafiee@sharif.edu.
Omid Fatahi ValilaiEmerging Technologies in Industrial Engineering (EITIE) Research Group, School of Business, Social & Decision Sciences, Constructor University Bremen, Campus Ring 1, 28759, Bremen, Germany. OFatahiValilai@Constructor.University.ORCID http://orcid.org/0000-0001-7087-6946

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic, originating in Wuhan, China, rapidly escalated into a global crisis, straining public health systems and economies. This study proposes a data-driven framework to evaluate the response performance of 143 countries across three phases: pre-vaccination, vaccination, and post-vaccination. Countries are clustered using K-means clustering based on pandemic-related indicators, and indicator importance is derived using an objective weighting method that accounts for variability and interdependence. Three Multi-Criteria Decision-Making (MCDM) methods (MACONT, COCOSO, and EDAS) are then applied to rank countries within clusters. The framework integrates diverse measures, including healthcare capacity, economic resilience, and the Risk INFORM COVID-19 index, enabling a holistic evaluation. Results reveal notable differences in country performance over time, with early vaccination rollout and strict public health policies associated with more stable rankings. Key determinants include the strength of the healthcare system, economic adaptability, and equitable vaccine distribution. An equity analysis using the Gini coefficient highlights significant disparities in global vaccine access, emphasizing the urgency of coordinated policy action. Finally, by tracking country movements across clusters, the study provides insights into evolving national responses. It concludes with recommendations for improving global preparedness and building more resilient, equitable systems for future health emergencies.

Indexed as

COVID-19COVID-19 VaccinesVaccinationHumansPandemicsSARS-CoV-2COVID-19 VaccinesCOVID-19Decision-support systemMachine learningMulti-criteria decision-making (MCDM)Vaccination strategies

Identifiers

PMID41663505
PMCPMC12960841

What OpenQuestion holds

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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.