The impact of the 21 November 2016 epidemic thunderstorm asthma event on general practice clinics in metropolitan Melbourne, Australia
Bibliographic record
Abstract
Background and objectiveOn 21 November 2016, parts of Victoria experienced a devastating epidemic thunderstorm asthma (ETSA) event.The aim of this study was to describe the epidemiology and burden of the 2016 ETSA event at MedicineInsight-registered general practices in the Melbourne metropolitan area in Victoria, Australia. MethodsA cross-sectional study was conducted using patient record data from 21-23 November 2016.Codes were developed to identify all patients presenting to MedicineInsight-registered general practices with asthma during the 2016 ETSA event. ResultsDuring the event, there were 787 more asthma-related encounters to MedicineInsight general practices than expected, which represented a 7.1-fold increase (605% increase).Estimates suggest that there were between approximately 8940 and 13,689 more asthma-related encounters than expected across metropolitan Melbourne. DiscussionGeneral practices were significantly affected by the 2016 ETSA event.This work highlights the important part that general practices play in responding to ETSA events and the need for these practices to be prepared to respond.EPIDEMIC THUNDERSTORM ASTHMA (ETSA) describes the sudden onset of asthma in a large number of people and is thought to be caused by a unique combination of high amounts of grass pollen in the air and a certain type of thunderstorm.Although ETSA events are uncommon, they can place considerable pressure on health systems, because they result in near-simultaneous asthma exacerbations in susceptible individuals.1 On 21 November 2016, parts of Victoria experienced a devastating ETSA event.This event resulted in widespread and significant strain on the health system, with unprecedented numbers of people calling triple zero, requiring ambulance services and presenting to hospital.1,2 The impact of the event has been described in a Victorian Chief Health Officer's report, which summarised that Melbourne and Geelong public hospitals experienced a 672% increase (3365 more presentations than expected) in respiratory-related emergency department presentations and a 992% increase in asthma-related admissions in the 30 hours from 6.00 pm on 21 November 2016. 1 There were 1626 more calls to the Emergency Services Telecommunications Authority (Triple Zero) than forecast.Furthermore, this event resulted in 10 deaths that have been investigated by the Victorian Coroner. 3 ETSA events have previously occurred in Melbourne, 4,5 but Victoria's health services, emergency services and the
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".