Seroprevalence of anti-tetanus antibodies in mothers and cord blood and associated factors in health-care settings in Lao People’s Democratic Republic
Bibliographic record
Abstract
BACKGROUND: Maternal neonatal tetanus (MNT) was eliminated from Lao People's Democratic Republic (PDR) in 2014. WHO recommends 80% coverage of 2 or more tetanus vaccinations (TT2+) in pregnancy to maintain MNT control. Vaccination coverage in Lao PDR varies among regions although the reasons are not clear. METHODS: 185 pregnant women giving birth in three district hospitals in Savannakhet province, Lao PDR were recruited. A questionnaire was administered to determine factors associated with seroprotection and blood was taken from mother and cord blood to be tested for anti-tetanus antibodies by ELISA. RESULTS: 77% of mothers and 79% of newborns had sufficiently protective antibody titres (>0.5 IU/ml) against tetanus. Only 70% of the mothers received one dose of TT vaccination during antenatal care (ANC) consultation and 45% received the recommended two injections. Although most of the vaccination took place during ANC 1 and 2, many were missed at these time-points. Anti-tetanus seroprotection in the mothers was associated with maternal age, number of ANC visits, number of TT vaccinations during and before pregnancy and gestational age. CONCLUSION: Seroprevalence of anti-tetanus antibodies in mothers and newborns was intermediate but TT2+ coverage was low in healthcare settings in Lao PDR. TT2+ coverage during ANC is likely to be significantly lower in settings with less robust ANC practices. Missed opportunities to vaccinate in ANC 1 and 2 suggest a need to promote vaccine awareness and vaccination at first ANC visit. A booster dose of TT containing vaccine should be considered for children aged between 4 and 7 years old.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".