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Record W4383998624 · doi:10.1017/s0950268823001127

Poliovirus outbreak in New York State, August 2022: qualitative assessment of immediate public health responses and priorities for improving vaccine coverage

2023· article· en· W4383998624 on OpenAlexaboutno aff
Ben Kasstan, Sandra Mounier‐Jack, Tracey Chantler, Nina B. Masters, Stephen A. Flores, Shannon Stokley, Haillie Meek, Delia Easton, Tatiana De Luna-Evans, Maria Júlia Silveira Souto, Chitra Punjabi, Patricia Schnabel Ruppert, Eli S. Rosenberg, Janell Routh

Bibliographic record

VenueEpidemiology and Infection · 2023
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsnot available
FundersNational Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionUniversity of Bristol
KeywordsOutbreakVaccinationInactivated Poliovirus VaccinePublic healthPoliomyelitisMisinformationMedicineVaccination scheduleImmunizationPoliovirusEnvironmental healthPolitical scienceVirologyNursingImmunologyVirus

Abstract

fetched live from OpenAlex

In 2022, a case of paralysis was reported in an unvaccinated adult in Rockland County (RC), New York. Genetically linked detections of vaccine-derived poliovirus type 2 (VDPV2) were reported in multiple New York counties, England, Israel, and Canada. The aims of this qualitative study were to: i) review immediate public health responses in New York to assess the challenges in addressing gaps in vaccination coverage; ii) inform a longer-term strategy to improving vaccination coverage in under-vaccinated communities, and iii) collect data to support comparative evaluations of transnational poliovirus outbreaks. Twenty-three semi-structured interviews were conducted with public health professionals, healthcare professionals, and community partners. Results indicate that i) addressing suboptimal vaccination coverage in RC remains a significant challenge after recent disease outbreaks; ii) the poliovirus outbreak was not unexpected and effort should be invested to engage mothers, the key decision-makers on childhood vaccination; iii) healthcare providers (especially paediatricians) received technical support during the outbreak, and may require resources and guidance to effectively contribute to longer-term vaccine engagement strategies; vi) data systems strengthening is required to help track under-vaccinated children. Public health departments should prioritize long-term investments in appropriate communication strategies, countering misinformation, and promoting the importance of the routine immunization schedule.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.047
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.166
GPT teacher head0.471
Teacher spread0.305 · 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 teacher head, 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

Citations10
Published2023
Admission routes1
Has abstractyes

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