Application of an automated surveillance-data-analysis system in a laboratory-based early-warning system for detection of an abortion outbreak in mares.
Abstract: To develop an early-warning automated surveillance-data-analysis system for early outbreak detection and reporting and to assess its performance on an abortion outbreak in mares in Kentucky. Methods: 426 data sets of abortions in mares in Kentucky during December 2000 to July 2001. Methods: A custom software system was developed to automatically extract and analyze data from a Laboratory Information Management System database. The software system was tested on data on abortions in mares in Kentucky reported between December 1, 2000, and July 31, 2001. The prospective space-time permutations scan statistic, proposed by Kulldorff, was used to detect and identify abortion outbreak signals. Results: Results indicated that use of the system would have detected the abortion outbreak approximately 1 week earlier than traditional surveillance systems. However, the geographic scale of analysis was critical for highest sensitivity in outbreak detection. Use of the lower geographic scale of analysis (ie, postal [zip code]) enhanced earlier detection of significant clusters, compared with use of the higher geographic scale (ie, county). Conclusions: The automated surveillance-data-analysis system would be useful in early detection of endemic, emerging, and foreign animal disease outbreaks and might help in detection of a bioterrorist attack. Manual analyses of such a large number of data sets (ie, 426) with a computationally intensive algorithm would be impractical toward the goal of achieving near real-time surveillance. Use of this early-warning system would facilitate early interventions that should result in more positive health outcomes.
Publication Date: 2009-02-24 PubMed ID: 19231958DOI: 10.2460/ajvr.70.2.247Google Scholar: Lookup
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- Journal Article
- Research Support
- U.S. Gov't
- Non-P.H.S.
- Disease control
- Disease Diagnosis
- Disease Etiology
- Disease Management
- Disease Outbreaks
- Disease Prevalence
- Disease Surveillance
- Disease Transmission
- Disease Treatment
- Epidemiology
- Equine Health
- Infectious Disease
- Laboratory Methods
- Mares
- Public Health
- Vascular
- Veterinary Medicine
- Veterinary Procedure
- Veterinary Research
- Veterinary Science
Summary
This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.
The research is focused on the development and application of an automated system meant to detect and report early signs of disease outbreaks in animals. This particular study tested the system’s efficacy on a reported case of an outbreak of abortion in mares in Kentucky, using data collected over several months.
Development of the Surveillance System
- The researchers developed a custom automated software system aimed to provide early warning of disease outbreaks.
- They implemented the system to extract and analyze data from a laboratory-based information management system database.
- This innovative system allows almost real-time surveillance of potential outbreaks and eliminates the need for labor-intensive manual analysis.
- The system is intended to quickly detect disease outbreak patterns, thereby allowing for swift intervention which could result in more positive health outcomes for the animals involved.
Methods and Data Used
- The data sets used for this study consisted of 426 cases of abortions in mares in Kentucky reported from December 2000 to July 2001.
- To detect and identify abortion outbreak patterns, the researchers used a prospective space-time permutations scan statistic, proposed by Kulldorff.
Performance of the Surveillance System
- The results of the study showed that the automated surveillance system could have detected the abortion outbreak in mares approximately one week earlier than traditional surveillance methods.
- However, the geographic scale of the data’s analysis crucially influenced the system’s sensitivity in detecting outbreaks.
- For instance, an analysis operating on a smaller geographic scale (i.e., postal codes) heightened the system’s ability for earlier detection of significant clusters, in comparison to analyses using a broader geographic scale (i.e., county).
Conclusions Drawn
- The researchers concluded that the automated surveillance-data-analysis system could be greatly beneficial in the early detection of endemic, emerging, and foreign animal diseases, and possibly even in the detection of a bioterrorist attack.
- This system could potentially be a game-changer in the field of veterinary surveillance and biosecurity, with its capability for near real-time data analysis and outbreak detection.
Cite This Article
APA
Odoi A, Carter CN, Riley JW, Smith JL, Dwyer RM.
(2009).
Application of an automated surveillance-data-analysis system in a laboratory-based early-warning system for detection of an abortion outbreak in mares.
Am J Vet Res, 70(2), 247-256.
https://doi.org/10.2460/ajvr.70.2.247 Publication
Researcher Affiliations
- Department of Comparative Medicine, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA.
MeSH Terms
- Animals
- Disease Outbreaks / prevention & control
- Disease Outbreaks / veterinary
- Female
- Fetal Death / epidemiology
- Fetal Death / veterinary
- Horse Diseases / epidemiology
- Horses
- Internet
- Kentucky / epidemiology
- Medical Records Systems, Computerized
- Models, Theoretical
- Public Health Informatics / instrumentation
- Sentinel Surveillance / veterinary
Citations
This article has been cited 5 times.- Carter CN, Smith JL. A proposal to leverage high-quality veterinary diagnostic laboratory large data streams for animal health, public health, and One Health. J Vet Diagn Invest 2021 May;33(3):399-409.
- Arjkumpa O, Sansamur C, Sutthipankul P, Inchaisri C, Na Lampang K, Charoenpanyanet A, Punyapornwithaya V. Spatiotemporal analyses of foot and mouth disease outbreaks in cattle farms in Chiang Mai and Lamphun, Thailand. BMC Vet Res 2020 Jun 1;16(1):170.
- Amat JP, Hendrikx P, Tapprest J, Leblond A, Dufour B. Comparative evaluation of three surveillance systems for infectious equine diseases in France and implications for future synergies. Epidemiol Infect 2015 Oct;143(14):3122-33.
- Rodríguez-Prieto V, Vicente-Rubiano M, Sánchez-Matamoros A, Rubio-Guerri C, Melero M, Martínez-López B, Martínez-Avilés M, Hoinville L, Vergne T, Comin A, Schauer B, Dórea F, Pfeiffer DU, Sánchez-Vizcaíno JM. Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations. Epidemiol Infect 2015 Jul;143(10):2018-42.
- O'Sullivan TL, Friendship RM, Pearl DL, McEwen B, Dewey CE. Identifying an outbreak of a novel swine disease using test requests for porcine reproductive and respiratory syndrome as a syndromic surveillance tool. BMC Vet Res 2012 Oct 16;8:192.
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