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Record W4417311556 · doi:10.3389/fvets.2025.1635447

Assessment of peste des petits ruminant’s vaccine wastage along the vaccine supply chain in Mali

2025· article· en· W4417311556 on OpenAlexaboutno aff
Guy Sidwatta Ilboudo, Ahmadou Sow, Cheick Abou Kounta Sidibé, Théodore Knight-Jones, Cheick Oumar Fomba, Michel Dione

Bibliographic record

VenueFrontiers in Veterinary Science · 2025
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsCold chainVaccinationPrivate sectorQuarter (Canadian coin)Public sectorDistribution (mathematics)Upstream (networking)Supply chain

Abstract

fetched live from OpenAlex

This study was carried out in six regions of Mali to assess peste des petits ruminants (PPR) vaccine wastage along the vaccine supply chain during the vaccination campaign of 2023. Multi-stage stratified sampling was used to select 107 actors involved in the vaccine supply chain, including private veterinarians ( n = 75), public vaccinators ( n = 19), regional veterinary officers ( n = 12), and one senior veterinary officer at the central level. Vaccine actors operated across the dominant small ruminants (SR) production systems in Mali (pastoral, agropastoral, and peri-urban). The World Health Organization field guidelines for monitoring and reducing vaccine wastage was used as a basis for this study. Results show that a quarter of vaccine doses were wasted. The vaccine wastage rate was 24.3% in public sector and 25.4% in private sector with approximately 90% of wastage occurring at the final stage of delivery (veterinary posts, or private veterinarians). At upstream points in the vaccine supply chain, wastage was low in both private and public distribution channels (less than 1%). No statistically significant difference was observed between the public and private sectors in vaccine wastage rates across the different stages of the vaccine distribution chain. The biggest cause of wastage was vaccine being discarded due to denaturation (46.0 and 32.4%, respectively, for the private and public actors), as doses were not used within the short (1 h) time window between reconstitution in the field and use. Also wastage was high due to improper injection (33.8 and 45.6% in public and private sectors), vial breakage (11.2 and 11.1%), and reconstitution errors (7.4 and 8.8%). The massive loss due to denaturation highlights the need for building stronger cold chains along the vaccine supply chain. In hard to reach areas, where cold chain failure is more likely, a vaccine able to remain potent for a longer period before and after reconstitution such as thermotolerant vaccines would add value. Furthermore, capacity of field vaccinators should be enhanced through trainings on best practices regarding vaccination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.318
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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