Abstract
OBJECTIVES: Building on previous research noting variations in the operation and perceived utility of syndromic surveillance systems in Ontario, the timeliness of these different syndromic systems for detecting the onset of both 2009 H1N1 pandemic (A(H1N1)pdm09) waves relative to laboratory testing data was assessed using a standardized analytic algorithm.
METHODS: Syndromic data, specifically local emergency department (ED) visit and school absenteeism data, as well as provincial Telehealth (telephone helpline) and antiviral prescription data, were analyzed retrospectively for the period April 1, 2009 to January 31, 2010. The C2-MEDIUM aberration detection method from the US Centers for Disease Control and Prevention’s EARS software was used to detect increases above expected in syndromic data, and compared to laboratory alerts, defined as notice of confirmed A(H1N1)pdm09 cases over two consecutive days, to assess relative timeliness.
RESULTS: In Wave 1, provincial-level alerts were detected for antiviral prescriptions and Telehealth respiratory calls before the laboratory alert. In Wave 2, Telehealth respiratory calls similarly alerted in advance of the laboratory, while local alerts from ED visit, antiviral prescription and school absenteeism data varied in timing relative to the laboratory alerts. Alerts from syndromic data were also observed to coincide with external factors such as media releases.
CONCLUSIONS: Alerts from syndromic surveillance systems may be influenced by external factors and variation in system operations. Further understanding of both the impact of external factors on surveillance data and standardizing protocols for defining alerts is needed before the use of syndromic surveillance systems can be optimized.
Key Words: Public health surveillance, algorithms, influenza A virus, H1N1 subtype, outbreaks
Résumé
OBJECTIFS: À partir des résultats de recherches antérieures sur les écarts dans le fonctionnement et l’utilité perçue des systèmes de surveillance syndromique en Ontario, nous avons évalué, à l’aide d’un algorithme analytique standardisé, la rapidité avec laquelle les différents systèmes syndromiques ont détecté l’apparition des deux vagues de la pandémie de grippe H1N1 de 2009 (A(H1N1)pdm09) par rapport aux données des épreuves de laboratoire.
MÉTHODE: Les données syndromiques, plus précisément les visites aux services d’urgence locaux et l’absentéisme dans les écoles, ainsi que les appels à Télésanté (une ligne d’assistance téléphonique provinciale) et les ordonnances d’antiviraux, ont été analysées rétrospectivement pour la période du 1er avril 2009 au 31 janvier 2010. Nous avons utilisé la méthode de détection des aberrations C2-MEDIUM du logiciel EARS des Centers for Disease Control and Prevention des États-Unis pour déceler les hausses supérieures aux prévisions dans les données syndromiques, et nous les avons comparées aux alertes des laboratoires, définies comme étant les avis de cas de grippe A(H1N1)pdm09 confirmés au cours de deux journées consécutives, pour évaluer la rapidité relative des systèmes de surveillance syndromique.
RÉSULTATS: Durant la 1e vague, des alertes de niveau provincial ont été détectées, dans les ordonnances d’antiviraux et les appels pour problèmes respiratoires à Télésanté, avant les alertes des laboratoires. Durant la 2e vague, les appels pour problèmes respiratoires à Télésanté ont aussi précédé les alertes des laboratoires, mais les alertes locales liées aux visites aux urgences, aux ordonnances d’antiviraux et aux taux d’absentéisme dans les écoles ont varié dans le temps par rapport aux alertes des laboratoires. Il a aussi été observé que les alertes déclenchées par les données syndromiques coïncidaient avec des facteurs externes, comme les communiqués.
CONCLUSIONS: Les alertes des systèmes de surveillance syndromique peuvent être influencées par des facteurs externes et des variations dans le fonctionnement des systèmes. Il faudrait pousser la recherche sur deux plans: l’impact exercé par les facteurs externes sur les données de surveillance et la normalisation des protocoles de déclenchement des alertes, avant de pouvoir optimiser l’utilisation des systèmes de surveillance syndromique.
Mots Clés: surveillance sanitaire, algorithme, virus A de la grippe soustype H1N1, flambées épidémiques
Footnotes
Acknowledgements: The authors thank Adriana Peci and Jonathan Gubbay for assistance in providing aggregate laboratory testing data and necessary interpretation; participating public health units, the Ministry of Health and Long-Term Care and the Public Health Agency of Canada for providing syndromic data; and the study’s Advisory Committee for their contributions to the study’s methodology and interpretation of results.
This work was supported by the Institute of Population and Public Health and the Knowledge Synthesis and Exchange Branch of the Canadian Institutes of Health Research [H1N-104055].
Conflict of Interest: None to declare.
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