By Hugh Mitchell, MS.*
Sales and marketing people (and politicians from all sides!) have known our psychological make-up for years (if not for centuries). Although we like to fancy ourselves as informed shoppers, we tend to not make the best choices in what we buy, or in many of the day-to-day decisions that we make. Instead, marketers know that we are prone to making the LEAST RISKY CHOICE (Fig. 1), and often we do so without any notion of the true magnitude of this risk. A product brand that we trust - is a least risk choice. A company that we have dealt with for years - is a least risk choice. If the competition can be portrayed as a risky prospect (again by exaggerating an uncertain magnitude), then we have an excessively strong tendency to stick with the status quo and give that least risky prospect the benefit of the doubt.
This sales and marketing technique is not only used by commercial merchandizers, but also by activists trying to convince the public to rally to their cause: the evils of vaccines, gluten, GMO’s, antibiotics, political points of view, and sometimes: fish farming. In many cases, the seeds of doubt that are planted are enough to cause people to second guess issues and areas without any in-depth follow-up. Searching out supportive information from “Dr. Google” further fans the flames of these preliminary paranoiac notions while opposing factual presentations are ignored or dismissed. Before long, dogma is formed and a certain “truth” settles into a segment of society. Even when the facts are presented by impartial experts that give proper magnitude to the level of risk, the fear is so strong that this dogma becomes extremely hard to shake and put in its proper quantifiable context. We are more apt to think: “But what if...” and “Better be safe than sorry” - tenets that are used to justify a confirmation bias. Solid metrics are summarily dismissed even when they are available.
Risks to Fish Health in Aquaculture
What does all this have to do with fish health in aquaculture? Aquaculture is technical, and is a business, or as with stock enhancement facilities, has tight budget constraints. This means that its practitioners are used to metrics. Unfortunately, in the past, these have not been extensively applied to fish disease. The preponderance of fish disease research has often been too “pathogenocentric” (the problem is the bacteria, virus or parasite), when in actuality fish population health (as well as terrestrial animal health AND human health) should more usefully be about risks, risk practices, and risk avoidances. Many seasoned fish culturists have developed an ingrained sense of this and manage it on an instinctual level. For example, they have developed a feel for what densities they need to keep their fish at with their particular water and containers in order to stave off persistent or episodic endemic diseases at their particular facility. However, when margins are thin and/or budgets are tight, risk reducing practices have to be prioritized. How does a farmer ensure that their risk hunches are indeed correct and prioritized? What if there are some hidden, unaccounted for risks that are being missed or under-appreciated?
What is not always well studied or utilized in aquaculture are the quantitative tools that have been developed to help aquaculturists decide what really is risky and what isn’t, as well as providing fish culturists ways of prioritizing and dedicating time and resources to what really is important (versus being subjectively risk averse to something that may actually not matter significantly).
So, the fundamental question is, and should be, for every fish farmer, given a specific disease: Why is there a variation in impact and mortality between farms? Why do some sites and fish culture facilities get impacted to a greater extent than others when they all have the “bug”? In other words, why do some facilities seem to be more at risk to the disease and its impact than others?
Mention “statistics” and most people’s eyes glaze over or you get comments like: “There are three types of lies - lies, damn lies, and statistics.” This is because most don’t appreciate the incredible tool that statistics is in helping us sort out a probabilistic world. In fact, there is no magic in statistics, it is simply a formal method of presenting data in order to help you decide whether something is probable or not. In medicine, there are many statistical tools that can help an aquaculturist or fish health specialist more accurately gauge the risk of a product or a practice. Instead of guessing on what might be contributing the most to a given disease situation, statistics can be generated in order to help a farmer or industry put the proper attention where it should be going (i.e.: reduce the guesswork), and/or reaffirming risk notions from experience.
It is beyond the scope of this column to be exhaustive on all statistical procedures, but in the next issue examples will be provided in order to show the value of this underutilized tool in fish health research and practice.
Hugh Mitchell, MS, DVM is an aquaculture veterinarian with more than 25 years of experience, who provides services and fish health tools to fish farmers across the US and Canada. His practice is AquaTactics Fish Health, out of Kirkland, Washington, specializing in bringing a comprehensive professional service/product package to aquaculture, including: vaccine solutions, immune stimulants, sedatives, antimicrobials and parasiticides.