Paediatric Active Enhanced Disease Surveillance (PAEDS) annual report 2015: Prospective hospital-based surveillance for serious paediatric conditions
Bibliographic record
Abstract
INTRODUCTION: The Paediatric Active Enhanced Disease Surveillance (PAEDS) network is a hospital-based active surveillance system employing prospective case ascertainment for selected serious childhood conditions, particularly vaccine preventable diseases and potential adverse events following immunisation (AEFI). PAEDS data is used to better understand these conditions, inform policy and practice under the National Immunisation Program, and enable rapid public health responses for certain conditions of public health importance. PAEDS enhances data available from other Australian surveillance systems by providing prospective, detailed clinical and laboratory information on children with selected conditions. This is the second of the planned annual PAEDS reporting series, and presents surveillance data for 2015. METHODS: Specialist surveillance nurses screened hospital admissions, emergency department records, laboratory and other data, on a daily basis in 5 paediatric tertiary referral hospitals in New South Wales, Victoria, South Australia, Western Australia and Queensland to identify children with the selected conditions. Standardised protocols and case definitions were used across all sites. Conditions under surveillance in 2015 included acute flaccid paralysis (a syndrome associated with poliovirus infection), acute childhood encephalitis (ACE), influenza, intussusception (IS; a potential AEFI with rotavirus vaccines), pertussis and varicella-zoster virus infection (varicella and herpes zoster). Most protocols restrict eligibility to hospitalisations, ED only presentations are also included for some conditions. METHODS: : In 2015, there were 674 cases identified across all conditions under surveillance. Key outcomes of PAEDS included: contribution to national AFP surveillance to reach WHO reporting targets; identification of signals for Mycoplasma pneumoniae and parechovirus-related outbreaks (ACE surveillance); and demonstration of high influenza activity with vaccine effectiveness (VE) analysis supportive of vaccination. Surveillance for IS remains ongoing with any identified AEFIs reported to the relevant State Health Department; varicella and herpes zoster case numbers decreased slightly from previous years in older children not eligible for catch-up. Pertussis case numbers increased in early 2015 and analysis of cases in children aged <1 year demonstrated the importance of timely childhood and maternal immunisation. CONCLUSIONS: PAEDS continues to provide unique policy-relevant data on serious paediatric conditions using hospital-based sentinel surveillance.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".