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Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems, including: (1) the identity of wildlife hosts, their distributions, and movement patterns; (2) the pathogen transmission pathways between wildlife and domestic animals; (3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations; and (4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.

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The local laboratory with a local client-base, that never needs to exchange information with any outside entity, is a dying breed. As marketing channels, animal movement, and reporting requirements become increasingly national and international, the need to communicate about laboratory tests and results grows. Local and proprietary names of laboratory tests often fail to communicate enough detail to distinguish between similar tests. To avoid a lengthy description of each test, laboratories need the ability to assign codes that, although not sufficiently user-friendly for day-to-day use, contain enough information to translate between laboratories and even languages. The Logical Observation Identifiers Names and Codes (LOINC) standard provides such a universal coding system. Each test—each atomic observation—is evaluated on 6 attributes that establish its uniqueness at the level of clinical—or epidemiologic—significance. The analyte detected, analyte property, specimen, and result scale combine with the method of analysis and timing (for challenge and metabolic type tests) to define a unique LOINC code. Equipping laboratory results with such universal identifiers creates a world of opportunity for cross-institutional data exchange, aggregation, and analysis, and presents possibilities for data mining and artificial intelligence on a national and international scale. A few challenges, relatively unique to regulatory veterinary test protocols, require special handling.