Heart and skeletal muscle inflammation (HSMI) is an emerging disease of marine-farmed Atlantic Salmon (Salmo salar), first recognized in 1999 in Norway, and later also reported in Scotland and Chile. We undertook a longitudinal study involving health evaluation over an entire marine production cycle on one salmon farm in British Columbia (Canada). In previous production cycles at this farm site and others in the vicinity, cardiac lesions not linked to a specific infectious agent or disease were identified. Histologic assessments of both live and moribund fish samples collected at the farm during the longitudinal study documented at the population level the development, peak, and recovery phases of HSMI. The fish underwent histopathological evaluation of all tissues, Twort’s Gram staining, immunohistochemistry, and molecular quantification in heart tissue of 44 agents known or suspected to cause disease in salmon. Our analysis showed evidence of HSMI histopathological lesions over an 11-month timespan, with the prevalence of lesions peaking at 80–100% in sampled fish, despite mild clinical signs with no associated elevation in mortalities reported at the farm level. Diffuse mononuclear inflammation and myodegeneration, consistent with HSMI, was the predominant histologic observation in affected heart and skeletal muscle. Infective agent monitoring identified three agents at high prevalence in salmon heart tissue, including Piscine orthoreovirus (PRV), and parasites Paranucleospora theridion and Kudoa thyrsites. However, PRV alone was statistically correlated with the occurrence and severity of histopathological lesions in the heart. Immunohistochemical staining further localized PRV throughout HSMI development, with the virus found mainly within red blood cells in early cases, moving into the cardiomyocytes within or, more often, on the periphery of the inflammatory reaction during the peak disease, and reducing to low or undetectable levels later in the production cycle. This study represents the first longitudinal assessment of HSMI in a salmon farm in British Columbia, providing new insights on the pathogenesis of the disease.

Infectious marine diseases can decimate populations and are increasing among some taxa due to global change and our increasing reliance on marine environments. Marine diseases become emergencies when significant ecological, economic or social impacts occur. We can prepare for and manage these emergencies through improved surveillance, and the development and iterative refinement of approaches to mitigate disease and its impacts. Improving surveillance requires fast, accurate diagnoses, forecasting disease risk and real-time monitoring of disease-promoting environmental conditions. Diversifying impact mitigation involves increasing host resilience to disease, reducing pathogen abundance and managing environmental factors that facilitate disease. Disease surveillance and mitigation can be adaptive if informed by research advances and catalysed by communication among observers, researchers and decision-makers using information-sharing platforms. Recent increases in the awareness of the threats posed by marine diseases may lead to policy frameworks that facilitate the responses and management that marine disease emergencies require.

In 1975, Fagan published a nomogram to help practitioners determine, without the use of a calculator or computer, the probability of a patient truly having a condition of interest given a particular test result. Nomograms are very useful for bedside interpretations of test results, as no test is perfect. However, the practicality of Fagan's nomogram is limited by its use of the likelihood ratio (LR), a parameter not commonly reported in the evaluation studies of diagnostic tests. The LR reflects the direction and strength of evidence provided by a test result and can be computed from the conventional diagnostic sensitivity (DSe) and specificity (DSp) of the test. This initial computation is absent in Fagan's nomogram, making it impractical for routine use. We have seamlessly integrated the initial step to compute the LR and the resulting two-step nomogram allows the user to quickly interpret the outcome of a test. With the addition of the DSe and DSp, the nomogram, for the purposes of interpreting a dichotomous test result, is now complete. This tool is more accessible and flexible than the original, which will facilitate its use in routine evidence-based practice. The nomogram can be downloaded at: www.adelaide.edu.au/vetsci/research/pub_pop/2step-nomogram/.

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