Always Advocating Alan – Do You Believe in Science?

| Opinion | June 25, 2020

The reason I ask if you believe in science at the start of this column is because today, there are many individuals who say one thing, but when questioned, tell us it really means something else. Then there are others who believe they can disagree with anyone’s opinion and gain the high ground by simply saying, “You must not believe in science,” by name calling or throwing out insults.

So, what is science anyway? Science Made Simple tell us, “Science refers to a system of acquiring knowledge. This system uses observation and experimentation to describe and explain natural phenomena. Less formally, the word ‘science’ often describes any systematic field of study or the knowledge gained from it.”

Science Made Simple goes on to further reveal the purpose of science as “to produce useful models of reality. Most scientific investigations use some form of the scientific method.”

While some of you may think only scientists build useful models based on investigations, observations, and a complex scientific method, it is something we all do regularly. Let’s suppose you live in the Santa Clarita Valley and work in Los Angeles. You recognize the need to get to work on time every day in order to keep your job. On your first day of employment, you select a method of transportation to get you there, a route, and an estimate of the amount of time necessary to travel the distance using the route and method of transportation you selected. Plus, since it is your first day, you probably added a little extra time as a safety margin. To that I say, congratulations. You just built your first model.

When you arrived at work, you checked your watch and made your first scientific observation. You noted if you were early, late, or right on time, and unless you were completely satisfied with the time you arrive, you adjusted your model by changing one of the attributes. You could leave earlier or later, use a different method of transportation, or change your route. In scientific terminology, you are refining your model. As time goes by, you would continue to make additional observations and perhaps find it necessary to add some additional model criteria. You might account for traffic density changes when school is in session, or if you are working the day before a 3-day holiday weekend. You might need to add some additional time or consider the impact if you are traveling to work on a national holiday. Each of the new criteria adds a level of complexity to your model. You added them because they are necessary for you to make accurate future predictions as the situation changes.


Models are very rarely simple, and results change over time. Plus, as we learned, they do so for varying reasons. Even using the example of modeling your time to get to work, results will need to be validated and updated regularly as traffic density changes, road conditions may require you to alter a portion of your route, and the scheduling of other unrelated activities impacting your trip to work may become apparent over time. You would never consider asking an expert how long it was going to take to get to work, and then not validate if the information you received was accurate, or continue to use the information as is if you were ending up late, or way to early, every day. Your model’s accuracy is important if you are to be successful.

Figure 1

Well, there is not much difference if you were building a model to guide the public through the COVID-19 pandemic. At first, the so-called experts “guessed” what the impact would be, and they did so by reflecting on prior experience. They decided to use a “bell curve” to model the virus’ transmission, because most human endeavors follow such a pattern, and they all took a probability and statistics course in college. Their initial estimate indicated the number of patients who would be infected with the COVID-19 virus would be so large, the existing U.S. health care capability would be overwhelmed. To combat this potential issue, they came up with a home quarantine philosophy, which they said would “flatten the curve” (see Figure 1). They gave the impression their method would reduce the “area under the curve,” meaning there would be fewer U.S. citizens succumbing to this new pandemic.

But, that was never the objective. On March 19, 2020, Life Science published an article entitled, “What is ‘flattening the curve,’ and will it work?” The text went on to explain, “Many hundreds of thousands of infections will happen — but they don’t all have to happen at once. Flattening the curve refers to community isolation measures that keep the daily number of disease cases at a manageable level for medical providers.” (See Figure 2). Therefore, “Flatten the Curve” is a misnomer and it should have been called “Reshaping the Curve.” It was never intended to keep you from being infected. It simply attempted to delay when you would suffer an infection and stretch the amount of time the pandemic would be an issue. The medical experts were not trying to prevent the public from suffering; they wanted to ensure their facilities would not be overwhelmed. Plus, they did not consider problems associated with the increased length of time the public would be suffering in isolation.

Fortunately for us all, those same medical experts grossly overestimated, the number of people who would become infected, the number who would require hospitalization, and the number of resulting deaths over time. Emergency medical facilities provided by the federal government went mostly unused, and the availability of local facilities remained adequate to handle the outbreak. But sadly, they never updated the models which were presented to the public. Therefore, if you believe in science, you recognize you have not been given a true representation of what transpired, or enough data for you to base an informed opinion.

figure 2

Currently, the country is trying to reopen and regain a sense of normalcy. I would very much like to understand the results, the level of risk, and the consequences of today’s civic planning. Yet, all I hear and read about are counts representing the number of positive cases revealed by testing each day, and a cumulative count of the number of cases discovered in each area. Just yesterday, I read the headline, “Florida Continues to See Coronavirus Spike.” The author went on to identify 4,049 new positive cases were reported on Saturday, for a grand total of 94,000 cases. While the information does not sound good, what does it mean? Without knowing if the new cases were obtained from a representative sample of the Florida population, or if they were individuals tested for the first time, or how many of those included requested testing because they were experiencing symptoms, or even how large the sample size was, makes this daily reporting almost meaningless. This is because there is insufficient information to normalize the data per day, or to understand the potential Florida population percentage which will be effected. Therefore, there is insufficient data to generate an accurate model.

Lately, the best information on infection rates came from California’s Governor Newsom, when last week he reported on live TV. The Governor informed us 90,000 California COVID-19 tests had been performed the previous day, with 4.2% of the results showing positive, and 15% of the individuals testing positive requiring hospitalization. Calculate it yourself. If this sample is representative of the California population, our hospitalization rate is 0.6%. If the public was given that kind of information daily, we could build a superficial model and attempt to show how California was handling our rush to normalcy.

So, when I read articles where Dr. Fauci opines about the American public not accepting science, and then goes on without including any scientific data in the article, he needs to recognize he has lost the public’s trust by not providing information needed to make his assertions credible. Then, as the public remembers his inconsistency over time, it falls on him to explain why he now is espousing different suggestions. Plus, those of you who say “I believe in science,” but have not done the homework to back up your assertions, I say your credibility is right in line with Dr. Fauci.

Like most of our residents, I have had enough self-isolation to last a lifetime, and I am hoping we will be able to shortly return to normal. At the same time, I do believe in science, and understand we have not been provided enough information to have a scientific opinion on what the future will bring. So, if I am left with having to form an emotional opinion, I say let’s go for it and open our society as soon as possible.

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