Whether you are a Quality Manager reading a Microbial COA or a homeowner reading the results of your in-home mold test, you may find yourself interpreting quantitative data, qualitative data, or perhaps both. You may not realize you’re even looking at these kinds of data, but that’s why we’re here. Understanding the differences between qualitative and quantitative data can provide the end-user of that data (you!) with context and guidance on how the data should be interpreted.
Microbiologists utilize quantitative and qualitative tests for different organisms for different reasons. This can be tedious to explain without some foundation, so for now let’s use pregnancy tests as an example to compare and contrast qualitative and quantitative testing:
Typically, the first pregnancy test a woman would take is an at-home urine test. The result is either Positive or Negative. Pregnant or Not Pregnant. This is a qualitative test. It describes a quality of the woman via urinalysis. It is an excellent screening tool that provides a very basic amount of information. Next, the woman may visit a healthcare practitioner and have her hCG (pregnancy hormone) levels checked to confirm pregnancy and get an exact measurement of her hCG. This is a quantitative test because her hCG level is quantified.
|Test:||At-Home Urinalysis||Blood Draw for hCG|
|Hypothetical Result:||Positive||425 mIU/ mL|
|Test/ Result Type:||Qualitative||Quantitative|
We would expect this hypothetical pregnant woman to use these pieces of data differently, right? The Positive urinalysis might mean she stops drinking alcohol, begins taking prenatal vitamins, and exchanges salads for fast food. And since hCG levels increase at a known rate during the early stages of pregnancy, her hCG levels may be interpreted to help provide a due date. She didn’t need to know her hCG levels to decide to stop drinking alcohol. Vice versa, a Positive pregnancy test does not provide a due date. It was all important information for her to make time-sensitive, but different decisions.
Ya still with us? I hope so because we’re just about to get into the microbiology side of things.
Microbiologists typically use qualitative test methods when testing for microorganisms that cause disease, referred to as pathogens. This is common practice because the goal is always to have zero pathogens. One is too many. And why bother counting if one is too many? That is an oversimplification, but it fits. A peanut butter manufacturer never, ever, ever wants E. coli O157 in their product. Not one cell, not one million cells. It is a nasty bug that will make lots of people very sick, and so they would likely choose a qualitative testing approach. If even one cell is present, the test will be Positive for E. coli O157 and the manufacturer would have to destroy/ dispose of the tainted product. There is a lot of tedium in exactly how pathogens are tested for qualitatively and why such methods are chosen, but we’ll save that for another blog post.
Quantitative tests, on the other hand, are typically used to test for organisms which do not often cause disease. While it is industry dependent, many consumer products have an expected and accepted level of microbiological activity. Unless a product or area is sterile, there are bound to be microorganisms present. Quantifying what is present provides the data end-user with more precise information that can be compared to expected or previous results. Consider the following examples.
It would not be very helpful if your in-home mold test result simply said “Living Room – Positive” and “Outside – Positive”. Mold grows outside, you open a door or window, and mold comes inside. It is expected to be found inside and outside, so simply knowing that the mold is there doesn’t do much for you. What is important to know is how much mold is in your Living Room compared to how much mold is Outside. Quantitative testing is critical for this reason. Similarly, a certain level of microbiological activity would be expected in a cold-pressed raw juice product. Knowing whether there are 100 CFU/mL or 100,000,000 CFU/mL is a more useful set of data than simply knowing there are microorganisms present. Simply stated, quantification allows for a baseline against which data can be compared. This may be in the form of product specifications, the Healthy Home Standard, or other pre-set guidelines on acceptable microbiological activity in a product or environment.
We hope this blog post was informative and helpful for our readers, as we hope for all of our blog posts so far. We welcome any feedback or topics you would like covered. After all, this is a blog for you. Don’t forget to check back next month for another blog post!