Development and Validation of an Automated Emergency Department-Based Syndromic Surveillance System for Use at a Mass Gathering Event (2020 Arctic Winter Games, Yukon Canada) During a Global Pandemic: Implications for Lower Resourced and Remote Settings
Notice bibliographique
Résumé
Abstract Background: Automated syndromic surveillance systems are useful tools for rapidly identifying health risks during times when routine surveillance and follow-up cannot meet the demands of the population. In Yukon, Canada, the Arctic Winter Games were scheduled in March 2020, and were expected to increase the local population beyond the capacity of local public health surveillance. An emergency department-based automated syndromic surveillance system was therefore developed and validated using local hospitalization records for use during the event. Methods: Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written to detect syndromic cases from three different fields (triage notes; chief complaint; discharge diagnosis) using Yukon emergency department case data containing information from 19,082 visits over the period of October 1, 2018 to April 30, 2019. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms. Results: A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8%-89.5% to 62.5%-94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset. However, the system was rapidly adapted into an additional surveillance tool for use in the COVID-19 pandemic. Conclusions: Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. Ultimately, the 2020 Arctic Winter Games were cancelled due to the risks associated with mass gatherings during the global pandemic of COVID-19 and could not therefore be tested under a mass gathering scenario. However, the results from our validation study suggest that our surveillance system may be useful for future mass gathering events and proved a timely development for integration into Yukon’s COVID-19 surveillance infrastructure.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».