South Africa’s farmed abalone (Haliotis midae) sector plays a critical role in the national aquaculture economy and relies heavily on continued access to high-value international markets. To support international trade and provide scientifically credible assurance of disease freedom, the Department of Forestry, Fisheries and the Environment (DFFE) coordinates a national surveillance programme for aquatic animal diseases. The programme targets both World Organisation for Animal Health (WOAH)-listed diseases and other endemic diseases of national significance. Although Haliotis midae has not been identified by WOAH as susceptible to any listed diseases, other Haliotis species have been assessed as susceptible to infections with Abalone herpesvirus, Perkinsus olseni, and Xenohaliotis californiensis.
The surveillance programme includes components of passive surveillance, targeted surveillance, and a risk-based, active non-targeted surveillance component or stock inspections. These elements are integrated to enhance early detection, provide evidence for disease freedom, and inform national risk management strategies. Together, they support the sustainable health management of Haliotis spp. and underpin continued market access for South African abalone products.
The stock inspections are not triggered by clinical suspicion, but instead proactively monitor apparently health populations to detect disease should it be present. This component is risk based, with surveillance frequency being informed by a disease risk model that estimates the likelihood that a farm would express detectable clinical signs if a pathogen were present. At each farm, a statistically sufficient number of abalone baskets are inspected to achieve a 95% confidence of detecting disease at a 2% design prevalence. Inspectors inspect the selected baskets for mortalities and clinical signs such as tissue necrosis, shell abnormalities and behavioural changes. Suspect samples are sampled and tested using sufficiently validated diagnostic methods.
This presentation outlines the development and ongoing refinement of the risk estimation model, drawing on field inspection data from 2017 to 2023. The integration of longitudinal surveillance data over time has enabled improved risk stratification, better resource allocation, and enhanced confidence in surveillance outcomes. Findings contribute to the demonstration and maintenance of national disease freedom status and support the issuance of export health certificates. Ultimately, this work demonstrates how the absence of disease, when backed by a robust, risk-informed system, can serve as powerful evidence for maintaining access to internation markets.