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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Faverjon 2019 - Systeme de surveillance syndromique multivariee_AEEMA_.pdf - Published Version Restricted to registered users only Available under License Publisher holds Copyright. Download (685kB) |
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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