Système de surveillance syndromique multivarié des maladies bovines en Suisse : simulation d'épidémies et évaluation d'algorithmes de détection

Faverjon, Céline; Carmo, Luis Pedro; Berezowski, John (2019). Système de surveillance syndromique multivarié des maladies bovines en Suisse : simulation d'épidémies et évaluation d'algorithmes de détection. Épidémiologie et santé animimale, 2019(75) AEEMA

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Multivariate syndromic surveillance systems offer interesting opportunities to strengthen early detection of epidemics. However, the number of operational multivariate SSy systems in animal health is low because it remains difficult to assess the performance of these systems. The objective of this study was to evaluate a multivariate SSy system for bovine diseases in Switzerland using a standardized method to simulate realistic multivariate epidemics of different diseases and comparing the detection performance of two algorithms: the Multivariate Exponentially Weighted Moving Average (MEWMA), and the Multivariate Cumulative Sum (MCUSUM).

Item Type:

Journal Article (Original Article)

Division/Institute:

05 Veterinary Medicine > Research Foci > Veterinary Public Health / Herd Health Management
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Veterinary Public Health Institute
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)

UniBE Contributor:

Faverjon, Céline Odette, Carmo, Luís Pedro, Berezowski, John Andrew

Subjects:

600 Technology > 630 Agriculture

Publisher:

AEEMA

Language:

French

Submitter:

Susanne Agnes Lerch

Date Deposited:

14 Feb 2020 11:13

Last Modified:

05 Dec 2022 15:36

BORIS DOI:

10.7892/boris.140389

URI:

https://boris.unibe.ch/id/eprint/140389

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