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The Ontario Animal Health Network: enhancing disease surveillance and information sharing through integrative data sharing and management
Author(s) -
Cynthia Miltenburg,
Tim Pasma,
Kathleen Todd,
Melanie Barham,
Alison Moore
Publication year - 2021
Publication title -
journal of veterinary diagnostic investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.529
H-Index - 78
eISSN - 1943-4936
pISSN - 1040-6387
DOI - 10.1177/10406387211003910
Subject(s) - preparedness , context (archaeology) , disease surveillance , variety (cybernetics) , disease , government (linguistics) , data sharing , one health , information sharing , medicine , data science , environmental health , computer science , public health , pathology , geography , alternative medicine , political science , linguistics , philosophy , archaeology , artificial intelligence , world wide web , law
The Ontario Animal Health Network (OAHN) is an innovative disease surveillance program created to enhance preparedness, early detection, and response to animal disease in Ontario. Laboratory data and, where available, abattoir condemnation data and clinical observations submitted by practicing veterinarians form the core of regular discussions of the species-sector networks. Each network is comprised of government veterinarians or specialists, epidemiologists, pathologists, university species specialists, industry stakeholders, and practicing veterinarians, as appropriate. Laboratorians provide data for diseases of interest as determined by the individual network, and network members provide analysis and context for the large volume of information. Networks assess data for disease trends and the emergence of new clinical syndromes, as well as generate information on the health and disease status for each sector in the province. Members assess data validity and quality, which may be limited by multiple factors. Interpretation of laboratory tests and antimicrobial resistance trends without available clinical histories can be challenging. Extrapolation of disease incidence or risk from laboratory submissions to broader species populations must be done with caution. Disease information is communicated in a variety of media to inform veterinary and agricultural sectors of regional disease risks. Through network engagement, information gaps have been addressed, such as educational initiatives to improve sample submissions and enhance diagnostic outcomes, and the development of applied network-driven research. These diverse network initiatives, developed after careful assessment of laboratory and other data, demonstrate that novel approaches to analysis and interpretation can result in a variety of disease risk mitigation actions.

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