Understanding pathogen risk is the foundation of creating mitigation activities that lead to a consistently safe food product. Proper data analysis will inform the level of pathogen risk to your processing systems. The key is to use the proper analysis to accurately determine how well your risk avoidance strategies are performing.

When evaluating the true pathogen risk it is important to know the distinction between two core analysis protocols—prevalence or enumeration. Knowing when to use each analysis method will help you better understand how your intervention programs are performing.

Understanding the protocols.

By definition, prevalence is the degree to which something exists in a given environment. For example, prevalence could cover the percentage of lymph nodes that have Salmonella at or during a defined time period. However, this does not provide information on quantity of pathogen presence.

On the other hand, enumeration is a specific count of something in a population. This could include the amount of Salmonella in a lymph node in a specific unit of measurement. Where prevalence can tell if something is present or not, enumeration can provide insights on how much pathogen load is present.

Prevalence is more of a systems approach to determining if processes are working. It could be used to determine how interventions are performing. Prevalence could tell you that the existence of pathogens was 30% at the beginning of the study but 3% afterward. Performance standards are based on established prevalence baselines and therefore can affect regulations that impact public health.

Enumeration data can also impact public health, but more from a basis of risk. It can tell you how much of a pathogen exists and if intervention activities will be able to overcome that level. Enumeration analysis can also be more targeted to focus on specific areas of the processing system to determine pathogen load levels in relation to intervention capacity.

Real-world scenarios.

Here’re a couple of scenarios to consider that demonstrate the difference between prevalence and enumeration. Let’s say, in the first scenario, eight out of 24 samples are Salmonella positive for a 33% prevalence rate. Of the positive samples, seven are at 10 CFU/g and 1 is at 10,000 CFU/g. In the second scenario, six out of 30 samples are Salmonella positive for a 20% prevalence. However, just one of the positive samples is at 10 CFU/g while five are at 10,000 CFU/g. Even though the pathogen loads in the positive samples were low, they still pose a public health risk because the percentage of positive tests is above our performance standard requirements.

The prevalence information in the first scenario indicates that our intervention process is probably working. There are more positive samples than the second scenario, however the pathogen load is low in all but one of the samples. Yet if our performance standard is set at 30%, our process would be above those standards in the first scenario.

In the second scenario, even though our prevalence percentage is below our performance standards, the pathogen load in all but one of the positive samples is significantly higher than the samples in the first scenario.  

This could potentially pose a more significant public health risk because the amount of pathogen in each positive sample is higher even though the prevalence percentage is below performance standard guidelines. The second scenario reflects the need to take a more targeted approach to managing pathogen loads in specific areas of the processing system.

Choose the proper analysis.

Both prevalence and enumeration studies give valuable information. It’s critical to understand what the incoming pathogen load might be and if interventions can handle that load. It’s important to remember that prevalence is not correlated to load. There could be a high prevalence in samples but a low pathogen load and, conversely, there could be a low prevalence but high pathogen load.

When deciding between prevalence or enumeration studies, start with the end in mind. What is your objective? Do you want to know what your prevalence data indicates relative to your performance standards? Or do you want to know the pathogen load in your facility so you can target intervention activities?

A comprehensive literature review can help you understand where in your system you need to start an analysis and help guide your decision-making on where to start an intervention. Use a statistician to help set up the analysis and evaluate results. And as always, continually review and improve analysis systems. Be sure to reach out to your Arm & Hammer Animal and Food Production representative for insights and tools to help reduce pathogen risk.

Get additional insights from the rest of our Combating Salmonella series: