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Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory
Disease surveillance in animals remains inadequate to detect outbreaks resulting from novel pathogens and potential bioweapons. Mostly relying on confirmed diagnoses, another shortcoming of these systems is their ability to detect outbreaks in a timely manner. We investigated the feasibility of usin...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120669/ http://dx.doi.org/10.1007/978-3-540-72608-1_1 |
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author | Shaffer, Loren Funk, Julie Rajala-Schultz, Päivi Wallstrom, Garrick Wittum, Thomas Wagner, Michael Saville, William |
author_facet | Shaffer, Loren Funk, Julie Rajala-Schultz, Päivi Wallstrom, Garrick Wittum, Thomas Wagner, Michael Saville, William |
author_sort | Shaffer, Loren |
collection | PubMed |
description | Disease surveillance in animals remains inadequate to detect outbreaks resulting from novel pathogens and potential bioweapons. Mostly relying on confirmed diagnoses, another shortcoming of these systems is their ability to detect outbreaks in a timely manner. We investigated the feasibility of using veterinary laboratory test orders in a prospective system to detect outbreaks of disease earlier compared to traditional reporting methods. IDEXX Laboratories, Inc. automatically transferred daily records of laboratory test orders submitted from veterinary providers in Ohio via a secure file transfer protocol. Test products were classified to appropriate syndromic category using their unique identifying number. Counts of each category by county were analyzed to identify unexpected increases using a cumulative sums method. The results indicated that disease events can be detected through the prospective analysis of laboratory test orders and may provide indications of similar disease events in humans before traditional disease reporting. |
format | Online Article Text |
id | pubmed-7120669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71206692020-04-06 Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory Shaffer, Loren Funk, Julie Rajala-Schultz, Päivi Wallstrom, Garrick Wittum, Thomas Wagner, Michael Saville, William Intelligence and Security Informatics: Biosurveillance Article Disease surveillance in animals remains inadequate to detect outbreaks resulting from novel pathogens and potential bioweapons. Mostly relying on confirmed diagnoses, another shortcoming of these systems is their ability to detect outbreaks in a timely manner. We investigated the feasibility of using veterinary laboratory test orders in a prospective system to detect outbreaks of disease earlier compared to traditional reporting methods. IDEXX Laboratories, Inc. automatically transferred daily records of laboratory test orders submitted from veterinary providers in Ohio via a secure file transfer protocol. Test products were classified to appropriate syndromic category using their unique identifying number. Counts of each category by county were analyzed to identify unexpected increases using a cumulative sums method. The results indicated that disease events can be detected through the prospective analysis of laboratory test orders and may provide indications of similar disease events in humans before traditional disease reporting. 2007 /pmc/articles/PMC7120669/ http://dx.doi.org/10.1007/978-3-540-72608-1_1 Text en © Springer Berlin Heidelberg 2007 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Shaffer, Loren Funk, Julie Rajala-Schultz, Päivi Wallstrom, Garrick Wittum, Thomas Wagner, Michael Saville, William Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory |
title | Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory |
title_full | Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory |
title_fullStr | Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory |
title_full_unstemmed | Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory |
title_short | Early Outbreak Detection Using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory |
title_sort | early outbreak detection using an automated data feed of test orders from a veterinary diagnostic laboratory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120669/ http://dx.doi.org/10.1007/978-3-540-72608-1_1 |
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