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Record W4401210875 · doi:10.1371/journal.pone.0308088

Effectiveness of a community-centered Newcastle disease vaccine delivery model under paid and free vaccination frameworks in southeastern Kenya

2024· article· en· W4401210875 on OpenAlexfundno aff
Kennedy O. Ogolla, Douglas N. Anyona, Judith K. Chemuliti, Winnie W. Kimani, Francisca M. King’oo, Kennedy Munyua Waweru, Dalmas Omia, Isaac K. Nyamongo, Salome A. Bukachi

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsnot available
FundersInternational Development Research CentreGlobal Affairs CanadaBill and Melinda Gates Foundation
KeywordsVaccinationMedicineNewcastle diseaseBiosecurityEnvironmental healthImmunologyVirus

Abstract

fetched live from OpenAlex

In the absence of effective drugs, vaccines constitute the cornerstone for the prevention of Newcastle disease (ND). Different strategies have been implemented to increase vaccination, but uptake remains low, underscoring the need for novel vaccine delivery methods. We designed and assessed the effectiveness of a community-centered ND vaccine delivery model in southeastern Kenya. Under the model, we sensitized smallholder chicken farmers (SCFs) through structured training on chicken husbandry, biosecurity, ND, and its vaccination, among other aspects. We subsequently engaged trained community vaccinators (CVs) to deliver vaccines and/or provide vaccination services to SCFs at a cost on one hand and, at no cost on the other, in selected sites to address challenges of inadequate service providers, vaccine unavailability, and inaccessibility. We tested this model under paid and free vaccination frameworks over one year and assessed the model's effect on vaccine uptake, ND-related deaths, and vaccine accessibility, among other aspects. Overall, we vaccinated more chickens at free sites compared to paid sites. However, we vaccinated a significantly higher mean number of chickens per household at paid (49.4±38.5) compared to free (28.4±25.9) sites (t = 8.4, p<0.0001). We recorded a significant increase in the proportion of SCFs who vaccinated their chickens from 31.3% to 68.4% (χ2(1, N = 399) = 58.3, p<0.0001) in paid and from 19.9% to 74.9% (χ2(1, N = 403) = 115.7, p<0.0001) in free sites pre- and post-intervention, respectively. The mean number of ND-related deaths reported per household decreased from 18.1±31.6 pre-intervention to 7.5±22.3 post-intervention (t = 5.4, p = 0.000), with higher reductions recorded in paid sites (20.9±37.7 to 4.5±11.2) compared to free sites (15.0±22.6 to 10.7±29.7) pre- and post-intervention, respectively. Farmers with access to vaccines increased significantly from 61.1% to 85.4% (χ2(1, N = 399) = 31.7, p<0.0001) in paid and 43.6% to 74.9% (χ2(1, N = 403) = 38.4, p = 0.0001) in free sites pre- and post-intervention, respectively. We established that type of intervention framework, gender of household head, if the household head attended training on chicken production in the last 12 months, access to information on ND vaccination, and the number of chickens lost to the previous ND outbreak were significant predictors of ND vaccine uptake. Our findings indicate the model has a broader reach and benefits for SCFs. However, policies should be enacted to regulate the integration of CVs into the formal animal health sector.

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)0.006
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.237
Teacher spread0.182 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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