If we adopt the vector model of disease when addressing addiction for any valuable medicinal, whether it’s opioids, benzodiazepines or any other controlled medicine, what’s at stake is our ability to ease and cure human suffering, not prevent addiction.
The vector model for disease was demonstrated in 1897 by Dr. R.A. Ross in his research on malaria. The vector was the Anopheles mosquito and Dr. Ross’s research won a Nobel Prize in Medicine for it. It may be best to view health officials who promote such simplistic yet dramatic ideas, as you would theoretical astrophysicists who are all pumped up talking about Albert Einstein; especially when such content is published for public consumption. Each official dazzling his readers with big words which have obscure meanings, as we all just sit there and nod our heads as if we know what they’re talking about.
What the public and media lap up without fact checking, not unlike a dog returning to its vomit, is that this model was constructed for diseases, either viral as in malaria, or bacterial. Applying this model to opioid addiction, as if addiction was something which can be communicated through another biological entity or having some kind of communicable properties which can be spread from person to person, is utter bunk.
That doesn’t mean the mathematical model on which it’s built, doesn’t have benefits for researchers in forecasting trends for healthcare. In that context it does have limited benefits, but drawing a 1:1 relationship for opioid addiction and proposing such a simplistic prevention plan, is just hog wash. Even the NIH say the connection between over prescribing and the opioid crisis is just a theory.
Reductionism vs Emergent Properties
Why do I say this? Because it’s a tool you can plug into a computer algorithm and run a simulation with, but beyond that it has no value with a condition which has a strong behavioral component. There’s a good scientific reason for this and it’s called human behavior. Computers are great at crunching numbers down several lines of probabilities, but computers can’t simulate emergent properties. A single emergent property is a property which a collection or complex system has, but which the individual members do not have. A failure to realize a property is emergent, leads to a fallacy and division.
Most forms of modern science are based on a principle called reductionism, reducing something down to it’s smallest constituent components so that when reassembled you can explain how each piece produces a results. But emergent properties in complex systems defy this principle; the sum of the parts can’t explain the whole.
A computer can do wonders simulating how billions of water molecules become a drop of water, but it can’t simulate enough drops of water, built on individual molecules, to explain a hurricane. And this is what we’re talking about when we think of modeling a simple disease such as a bacterium or virus verses a brain scaled up from billions of neurons with a billions times that, of neural connections which is where human behavior becomes emergent.
If this were possible, we’d have walking talking robots now waiting on us hand and foot. And no doubt, some would become addicted to that, just like they do other processes addictions such as gambling, sex and shopping. And by the way, there are 35 known types of 12 step self-help groups currently used to treat the different types of addiction we know of, and the list keeps growing.
The Genetic Basis for Addiction
For most, addiction and recovery from it, is not so much about a substance or a process, but about correcting a behavioral deficit, learning something about yourself you didn’t know that has been tripping you up and I say this with good reason.
First is what’s called cross addictions, that ability to stop abusing one substance or process and switch to another. Or having two addictions, a substance addiction combined with a process addiction. Such conditions don’t have genetic markers that we know of yet. We’ve identified a genetic marker associated with high rates of opioid addiction and another for alcohol, but we can’t put our finger on these and say, if you got the genetic marker, you’re going to get the disease. Lots of women have the genetic marker for breast cancer, but don’t get breast cancer. Genetics is about probability, so it’s no foregone conclusion that anything will happen.
Those with genetic markers for opioid addiction have about a 0.62% chance of being addicted, that’s a forecasted rate of 620 people out of every 10,000 but in the real world, the actual number is around 62 people in every 10,000. For those with the genetic marker for alcohol addiction the forecasted rate is around 0.65% or 650 out of every 10,000. And what see in the real world numbers is, 670 people out of every 10,000. These are extremely small risk numbers when you compare them to other medical risks.
What is striking about these two numbers is how closely related they are in forecasting addiction but in real world numbers, how far apart they are. You’re first thought would be that with alcohol being freely available, there would be more addicted to alcohol than what is forecasted, but there’s not.
This is where the Vector Model approach for treating addiction, by removing access to opioids, breaks down and why I call it total bunk when used in addressing the opioid crisis.
Early prohibition in the 1920’s adopted the vector model when addressing alcoholism. Prohibition was based on the same idea, that if you outlaw alcohol, we can prevent alcoholism. As every knows that failed, but here we are again, 100 years later going back to our vomit and eating it.
What’s at Risk with the Vector Model
So if we adopt the vector model of disease when addressing addiction for any valuable medicinal, whether it’s opioids, benzodiazepines or any other controlled substance, what’s at stake is our ability to ease and cure human suffering, not prevent addiction.
There are risks in many medicinals and other things we use every day, some more so than others, which is why we have 35 types of 12 step self-help programs, but we’re not placing extreme restrictions on using them. Why should opioid be any different? There are things used every day in medical care which have risks for a bad outcome, most carry a far greater risk than opioid addiction, but we’re not restricting access to these nor are we telling doctors when they can use them and when they can’t. And why, because the benefits out weigh the risks.
Opioids are the single best medicinal we have for moderate to severe pain both inside and outside a hospital. Yet because of the use of the vector model, we want to severely restrict their use both in and out of hospitals. The rule of thumb in our society for medications is, when the benefits outweigh the risks and the risks are manageable, we use the best of what we have and right now opioids are the best we have for moderate to severe pain. We train our physicians to recognize these differences and respond appropriately. We don’t relegate medical decision making to politicians so they can use it as spring boards in their next election campaign. If we allow some in healthcare to substitute ideology for science, by dazzling us with big words which have obscure meaning, allowing them to pan their ideological values off as science, then we will have bought into a lie and the price in this case, will become our pain and suffering.