The Impact of War in Yemen on Immunization Coverage of Children Under One Year of Age: Descriptive Study
Bibliographic record
Abstract
BACKGROUND: After 2 years of war that crippled the capacity of the Yemeni National Health System and left only 45% of health facilities functioning, Yemen faced increasing vaccine-preventable disease (VPD) outbreaks and may be at high risk of polio importation. OBJECTIVE: The aim of this study was to determine the impact of the 2015 war on the immunization coverage of children under 1 year. METHODS: Data on vaccination coverage for 2012-2015 were obtained from the national Expanded Program on Immunization (EPI). The vaccination coverage was calculated at the national and governorate levels by dividing the number of actually vaccinated children by the estimated population of children under 1 year. RESULTS: Although there was an increase from 2012 to 2014 in the national coverage for penta-3 vaccine (82% in 2012 vs 88% in 2014) and measles vaccine (70% in 2012 vs 75% in 2014), the coverage was still below the national target (≥95%). Furthermore, the year 2015 witnessed a marked drop in the national coverage compared with 2014 for the measles vaccine (66% in 2015 vs 75% in 2014), but a slight drop in penta-3 vaccine coverage (84% in 2015 vs 88% in 2014). Bacillus Calmette-Guérin vaccine also showed a marked drop from 73% in 2014 to 49% in 2015. These reductions were more marked in governorates that witnessed armed confrontations (eg, Taiz, Lahj, and Sa'dah governorates). On the other hand, governorates that did not witness armed confrontations showed an increase in coverage (eg, Raymah and Ibb), owing to an increase in their population because of displacement from less secure and confrontation-prone governorates. CONCLUSIONS: This analysis demonstrated the marked negative impact of the 2015 war on immunization coverage, especially in the governorates that witnessed armed confrontations. This could put Yemen at more risk of VPD outbreaks and polio importation. Besides the ongoing efforts to stop the Yemeni war, strategies for more innovative vaccine delivery or provision and fulfilling the increasing demands are needed, especially in governorates with confrontations. Enhancing EPI performance through supportable investments in infrastructure that was destroyed by the war and providing decentralized funds are a prerequisite.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".