Surveillance of congenital Zika syndrome in England and Wales: methods and results of laboratory, obstetric and paediatric surveillance
Bibliographic record
Abstract
The spread of the Zika virus (ZIKV) in the Americas led to large outbreaks across the region and most of the Southern hemisphere. Of greatest concern were complications following acute infection during pregnancy. At the beginning of the outbreak, the risk to unborn babies and their clinical presentation was unclear. This report describes the methods and results of the UK surveillance response to assess the risk of ZIKV to children born to returning travellers. Established surveillance systems operating within the UK - the paediatric and obstetric surveillance units for rare diseases, and national laboratory monitoring - enabled rapid assessment of this emerging public health threat. A combined total of 11 women experiencing adverse pregnancy outcomes after possible ZIKV exposure were reported by the three surveillance systems; five miscarriages, two intrauterine deaths and four children with clinical presentations potentially associated with ZIKV infection. Sixteen women were diagnosed with ZIKV during pregnancy in the UK. Amongst the offspring of these women, there was unequivocal laboratory evidence of infection in only one child. In the UK, the number and risk of congenital ZIKV infection for travellers returning from ZIKV-affected countries is very small.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".