MétaCan
Menu
← Back to cohort
Record W4407388429 · doi:10.48327/mtsi.v4i3.2024.431

Freins et réticences à la vaccination pédiatrique (PEV) et contre la Covid-19 : résultats d’une enquête au Niger

2023· article· en· W4407388429 on OpenAlexaff
Bernard Seytre, Sanoussi Chaibou, Elise Chabot, Bernard Simon

Bibliographic record

VenuePubMed · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsVaccinationCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineVirologyPandemicEnvironmental healthInternal medicineOutbreak

Abstract

fetched live from OpenAlex

Background: Vaccination adherence among populations is a complex process involving, on the one hand, the expected benefit of a vaccine, and on the other, the perceived risk. To develop an evidence-based communication strategy aimed at improving vaccination coverage in Niger, we conducted a mixed socio-anthropological study of the perceptions among the population on the benefit and the risk of the childhood (Expanded Program on Immunization, EPI) and the Covid-19 vaccines. While the vaccine coverage for some of the EPI vaccines is above 80%, only 33% of the children are fully vaccinated, according to the national vaccination schedule. The first objective of our study was to understand the perceptions that might explain this drop off.The second objective was to identify the drivers of the low adherence to the Covid-19 vaccination, 22% of the illegible population being vaccinated. Materials and methods: In March 2023, we interviewed 509 people for the quantitative study and 40 people through focus groups and individual interviews for the qualitative one, in Niamey (80% of the interviewees) and two villages. Results: 96.9% of the interviewees think that childhood vaccines are "a good thing," even though 30.6% know that they might have negative side effects. While 87.8% think that it is "easy" or "very easy" to get children vaccinated, 21.4% point out as "annoying" the lack of amiability by the health care workers and 16.9% the waiting time. The qualitative study showed that these two complaints drive some women not to complete the vaccination schedule. We might also hypothesize that, given the perceived lack of amiability, some women don't get enough information on the side effects and their management. Surprisingly, 73.3% of the interviewees think that vaccines against the disease are a good thing, and 83% of those who have heard messages promoting the vaccination approve them. This apparent contradiction with the low vaccine uptake is explained by a very low perception of the Covid-19 risks. More than half of the population surveyed believe that the disease is not present in the country, a very large majority believe that only ill people can transmit the disease, while only 12.8% think they know anybody who has ever been sick with Covid-19. According to our results, the circulating rumors on the vaccines don't play a significant role in the low adherence to Covid-19 uptake, nor in the insufficient completeness of the EPI vaccination schedule. Conclusion: The communication efforts on EPI vaccination should focus on the explanation of the side effects and their management, as well as improving the organization of the vaccination sessions. The communication on Covid-19 vaccination should focus on the reality of the disease in the country and the groups at risk for severe forms.

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)0.011
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 score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.319
Teacher spread0.286 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicVaccine Coverage and Hesitancy→French-language works237,207→