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Record W2238432109

Examining measles, mumps, and rubella (MMR) immunization uptake in Saskatoon: Can neighbourhood characteristics predict coverage rates?

2004· dissertation· en· W2238432109 on OpenAlexaboutno aff
Kyla Avis

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2004
Typedissertation
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsMeaslesRubellaNeighbourhood (mathematics)VirologyImmunizationMMR vaccineMeasles-Mumps-Rubella VaccineMedicineEnvironmental healthPediatricsVaccinationImmunologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

Immunization programs have proven to be one of the most successful public health initiatives in Canada yet continuous monitoring of coverage rates is essential to ensure high uptake and the continued success of these programs. Prior to this study, Saskatoon Public Health Services (PHS) were limited to manual calculation of coverage rates and trends and were unable to examine immunization uptake by neighbourhood. The purpose of this study was to utilize newly available data from the Saskatchewan Immunization Management System (SIMS) to examine city and neighbourhood uptake of the Measles, Mumps, and Rubella (MMR) vaccine. Once neighbourhood coverage rates were calculated, the project centred on using quantitative neighbourhood level data to determine if the neighbourhood variables of interest could significantly contribute to the explanation in variation of up-todate immunization coverage in Saskatoon. The study looked at 10, 287 two year-olds in Saskatoon between 1999 and 2002. The findings revealed immunization rates were relatively stable during this period. Of the approximately 90% of children who were immunized each year about 70% were considered up-to-date while approximately 20% were considered delayed or incomplete. However, significant disparities were found to exist at the neighbourhood level with areas of social and economic disadvantage having lower rates of total, complete, and up-to-date immunization uptake compared to areas of greater social and economic wealth. A slight downward trend in total immunization uptake was also noted in both the city of Saskatoon and high uptake neighbourhoods. Interestingly, high uptake neighbourhoods were also found to have the highest levels of social and economic advantage. Multivariate linear regression, used in the second phase of the analysis, revealed 80.6% of variation in up-to-date immunization uptake in Saskatoon could be explained by the proportion of single mothers and the proportion of vehicles registered in ,the neighbourhood. These findings are supported by the literature and may indicate the presence of real or perceived barriers to immunization for some families in Saskatoon. Limitations of the study include: the quality of the SIMS data, general limitations of ecologic designs, and problems with child mobility within and outside of the city. The issue of mobility likely resulted in the overestimation of coverage rates in some neighbourhoods and underestimation in others even though measures were taken to mitigate the effects of potential misclassification. Six recommendations were devised in an attempt to identify possible directions for future research and to improve the provision of immunization services for all areas of the city with particular attention focussed on high-risk neighbourhoods. It is hoped the findings of this study and recommendations provided will assist PHS in their continued efforts to improve immunization uptake in Saskatoon and throughout the entire region.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.128
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0010.000
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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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

Citations0
Published2004
Admission routes1
Has abstractno

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