A proposal to leverage high-quality veterinary diagnostic laboratory large data streams for animal health, public health, and One Health

• Published in: Journal of veterinary diagnostic investigation Vol. 33; no. 3; pp. 399 - 409
• Main Authors: Carter, Craig N., Smith, Jacqueline L.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.05.2021
• Subjects: Animals; COVID-19 - epidemiology; Humans; Laboratories - organization & administration; One Health; Public Health; SARS-CoV-2; Special Issue; United States - epidemiology; Veterinary Medicine; Zoonoses - epidemiology; United States; animal health monitoring; laboratory information management system; standard veterinary nomenclature system; veterinary diagnostic laboratory
• ISSN: 1040-6387; 1943-4936
• DOI: 10.1177/10406387211003088

Test data generated by ~60 accredited member laboratories of the American Association of Veterinary Laboratory Diagnosticians (AAVLD) is of exceptional quality. These data are captured by 1 of 13 laboratory information management systems (LIMSs) developed specifically for veterinary diagnostic laboratories (VDLs). Beginning ~2000, the National Animal Health Laboratory Network (NAHLN) developed an electronic messaging system for LIMS to automatically send standardized data streams for 14 select agents to a national repository. This messaging enables the U.S. Department of Agriculture to track and respond to high-consequence animal disease outbreaks such as highly pathogenic avian influenza. Because of the lack of standardized data collection in the LIMSs used at VDLs, there is, to date, no means of summarizing VDL large data streams for multi-state and national animal health studies or for providing near-real-time tracking for hundreds of other important animal diseases in the United States that are detected routinely by VDLs. Further, VDLs are the only state and federal resources that can provide early detection and identification of endemic and emerging zoonotic diseases. Zoonotic diseases are estimated to be responsible for 2.5 billion cases of human illness and 2.7 million deaths worldwide every year. The economic and health impact of the SARS-CoV-2 pandemic is self-evident. We review here the history and progress of data management in VDLs and discuss ways of seizing unexplored opportunities to advance data leveraging to better serve animal health, public health, and One Health.