ASF Early Detection

Strengthening On-Farm Preparedness: The ASF Early Detection Surveillance Tool

Effective early detection is a critical component of disease preparedness and a requirement for the development of disease-free compartments. To support Canadian producers in this effort, EpiMundi was commissioned by the Canadian Pork Council to develop an early detection surveillance tool for African Swine Fever (ASF) on commercial swine farms.

The primary goal of this project was to create a system that balances two competing needs: effectiveness and efficiency. An effective system must have high sensitivity to detect a disease incursion rapidly, while an efficient system must achieve that detection at a reasonable cost.

Customized Farm Simulations

Recognizing that every operation is different, the work focused on developing an online tool that allows producers and policy makers to evaluate surveillance sensitivity based on their specific farm parameters. Rather than using generic averages, the tool allows users to input their own data to create a custom scenario, including:

  • Barn Layout: Users define the structure of their specific facilities, detailing the arrangement of pens within rooms and rooms within the barn. This allows the model to account for the specific “rows by columns” design of a producer’s operation.

  • Population Details: The tool accepts specific inputs regarding the total number of pigs and how they are distributed across the barn.

  • Baseline Mortality: A critical input is the unit-specific baseline mortality rate. This is the expected number of pigs dying of unknown causes in the absence of disease. This data helps the model distinguish between normal production losses and potential ASF-related mortalities.

Testing Your Strategy

The core function of the tool is to simulate ASF surveillance scenarios. Based on a published epidemiological model, the system runs a stochastic (randomized) simulation of an outbreak starting in a single pen.

Producers can test different surveillance protocols by adjusting:

  • The Mortality Threshold: The number of dead pigs that must be found before diagnostic testing is triggered.

  • Sample Size: The number of pigs to test once that threshold is reached.

  • Testing Costs: The specific costs associated with diagnostic testing in their region.

Actionable Insights

Once a producer defines their scenario and clicks “Email my report,” the system processes the simulation and delivers a PDF report via email . This report provides data to help producers optimize their surveillance strategy, including:

  • Estimated Time to Detection: How quickly the proposed protocol would catch an outbreak.

  • Detection Sensitivity: The likelihood of the protocol successfully identifying the disease.

  • Projected Costs: A breakdown of total costs, including the number of tests performed and the economic impact of the testing strategy.

  • False Positives: An estimation of how often the protocol might flag a concern when no disease is present.

By enabling the comparison of different thresholds and testing frequencies, the tool provides a recommended optimal testing strategy. This allows producers to make informed decisions that ensure high standards of safety while managing operational costs.