Context-specific definitions of epidemiological units

The Challenge: The Definition Gap

In the regulation of animal health — whether for surveillance standards or the licensing of autogenous vaccines — the concept of the “Epidemiological Unit” is the cornerstone of compliance. Standard definitions (such as those by WOAH or national competent authorities) often default to a spatial interpretation: one shed, one farm.

However, in modern integrated production, this spatial definition rarely reflects biological reality. Highly connected production flows, shared genetics, and common logistics create networks where pathogens move freely across physical boundaries.

For pharmaceutical companies, a restrictive interpretation of an epidemiological unit creates a commercial bottleneck. It limits the population eligible for an autogenous vaccine (making production economically unviable) or mandates excessive, redundant sampling for surveillance.

EpiMundi’s Approach: From Spatial to Functional Definitions

EpiMundi has used a risk-Assessment framework to develop a practical, applied approach to defining an epidemiological unit from a static geographic concept to a dynamic functional one.

We do not simply ask “where are the animals located?” Instead, we ask “how are these populations connected, and what is the likelihood of disease spread?”

Our framework evaluates three critical dimensions to determine the true scope of a unit:

1. Level of Connectedness: We utilise network analysis to map the flow of animals (e.g., hatchery to grow-out, sow farm to nursery), personnel, and fomites. If two geographically distinct sites share high traffic and identical sourcing, they may functionally operate as a single biological unit.
2. Transmission Mechanisms: A unit defined for a highly contagious airborne virus (like Influenza) differs from one defined for a feco-oral pathogen (like Salmonella). Our models adjust the “borders” of the unit based on the specific transmission physics of the target pathogen.
3. Acceptable Risk Thresholds: We quantify the probability of pathogen heterogeneity. If the risk that the strain circulating on Farm A differs from Farm B is statistically negligible, we provide the evidence to classify them as a single unit.

Application 1: Unlocking the Economics of Autogenous Vaccines

The viability of autogenous (herd-specific) vaccines hinges on scale. Producing a custom batch for a single farm is less cost-effective.

By applying our framework, pharmaceutical clients and veterinarians can provide evidence to demonstrate to regulators what the appropriate epidemiological unit is in a specific situation. This evidence-based expansion of the “unit” may allow a single autogenous isolate to be legally and safely applied across a much larger population (e.g., an entire integrator’s flow), significantly improving the cost-benefit ratio of the product and making the intervention nore commercially attractive.

Application 2: Optimising Surveillance Efficiency

When an integrator operates 50 sites that function biologically as one, sampling every site is a waste of resources.

We use our framework to calculate the degree of homogeneity within the production system. This allows for the design of representative sampling protocols where a subset of the population provides statistical confidence for the whole network. This reduces laboratory and labour costs for surveillance and routine monitoring, without compromising the sensitivity of the surveillance system.

The Result: Regulatory Confidence

Regulators act on caution; they require evidence to deviate from standard definitions. EpiMundi provides the rigorous, independent technical methodology required to justify a more nuanced interpretation of the epidemiological unit. We bridge the gap between a strict yet arbitrary interpretation of the law and the complex reality of modern production, ensuring compliance while securing commercial efficiency.