Evaluation of Routine Immunization Coverage in 12- to 23-Month Children in Sarepol Province, 2018: Descriptive Cross-sectional Study
Bibliographic record
Abstract
Background Afghanistan has the lowest routine immunization coverage, according to the WHO-UNICEF reports. The coverage rate of Penta3 in Iran, India, Pakistan, and Afghanistan are estimated to be 99%, 89%, 75%, and 66%, respectively. Objective This study aimed to find the real immunization coverage in urban areas and factors related to vaccinated and unvaccinated 12- to 23-month children, in 2018, in Sarepol province. Methods A descriptive cross-sectional study with probability proportional to size (PPS) cluster sampling was conducted and modified for application to surveys of immunization coverage. We selected 30 clusters and randomly selected 7 households from each cluster in the urban setting of Sarepol province. The children’s age was calculated, in months, with respect to the 1st day of the survey. We designed a comprehensive questionnaire, and 210 questionnaires were filled. The data were managed and analyzed in Epi Info v.7. Results This survey shows EPI routine coverage for 12- to 23-month children for BCG, Meales-1, Penta1, and Penta3, which were 97.14%, 77.14%, 93.81%, and 83.81%, respectively. A full immunization coverage by gender—80.18% for girls and 71.15% for boys—was reported. The dropout rate of vaccination among Penta1, Penta3, and BCG was 9.27%, and for Measles-1 was 18.90%. Moreover, 2.86% of 12- to 23-month children did not receive any vaccine in these urban areas. Children’s illness, emigration, distant health facilities, and the gaps between the doses were reported by the respondents as the main reasons for incomplete or no vaccination. The valid doses administered for BCG, measles, and Penta3 were calculated to be 93.80%, 71.43%, and 80%, respectively. Conclusions It is observed that access and use of immunization services in urban areas have improved because full immunization was 75% compared with the AHS-2018 survey’s 61%. However, there are still many children who have not received any vaccine. High immunization dropout rates could be overcome by creating awareness of the program and of the importance of second and third doses of penta, polio, and measles vaccines. Measles coverage is very low, and we are expecting more outbreaks in urban areas. We therefore suggest that the Ministry of Public Health better enhance awareness and implement measles campaigns.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".