Schools as potential vaccination venue for vaccines outside regular EPI schedule: results from a school census in Pakistan
Bibliographic record
Abstract
BACKGROUND: Vaccines are the most effective public health intervention. Expanded Program on Immunization (EPI) provides routine vaccination in developing countries. However, vaccines that cannot be given in EPI schedule such as typhoid fever vaccine need alternative venues. In areas where school enrolment is high, schools provide a cost effective opportunity for vaccination. Prior to start of a school-based typhoid vaccination program, interviews were conducted with staff of educational institutions in two townships of Karachi, Pakistan to collect baseline information about the school system and to plan a typhoid vaccination program. Data collection teams administered a structured questionnaire to all schools in the two townships. The administrative staff was requested information on school fee, class enrolment, past history of involvement and willingness of parents to participate in a vaccination campaign. RESULTS: A total of 304,836 students were enrolled in 1,096 public, private, and religious schools (Madrasahs) of the two towns. Five percent of schools refused to participate in the school census. Twenty-five percent of schools had a total enrolment of less than 100 students whereas 3% had more than 1,000 students. Health education programs were available in less than 8% of public schools, 17% of private schools, and 14% of Madrasahs. One-quarter of public schools, 41% of private schools, and 43% of Madrasahs had previously participated in a school-based vaccination campaign. The most common vaccination campaign in which schools participated was Polio eradication program. Cost of the vaccine, side effects, and parents' lack of information were highlighted as important limiting factors by school administration for school-based immunization programs. Permission from parents, appropriateness of vaccine-related information, and involvement of teachers were considered as important factors to improve participation. CONCLUSIONS: Health education programs are not part of the regular school curriculum in developing countries including Pakistan. Many schools in the targeted townships participated in immunization activities but they were not carried out regularly. In the wake of low immunization coverage in Pakistan, schools can be used as a potential venue not only for non-EPI vaccines, but for a catch up vaccination of routine vaccines.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".