Early Outbreak Detection using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory
Shaffer L, Funk J, Rajala-Schultz P, Wallstrom G, Wagner MM, Saville W. Early Outbreak Detection using an Automated Data Feed of Test Orders from a Veterinary Diagnostic Laboratory. Lecture Notes in Computer Science: Intelligence and Security Informatics: Biosurveillance, 2007; 4506: 1-10. ISSN 0302-9743 (Print); 1611-3349 (Online).
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.