**Glossary**

**Virus**– a type of germ that consists solely of a bit of genetic material (DNA or RNA) wrapped in a protein coat. The coat gets the genes into the target cell where the genes force the cell to make zillions of new viruses, and on it goes.**Coronavirus**– a species name of a number of different viruses. Called corona because its protein coat is studded with spike shapes that form a crown, halo, or corona of spikes**SARS-CoV-2**– the specific name of the new coronavirus**COVID-19-**the name of the illness that the new coronavirus is causing**Endemic**– an illness always present in a region. One could say strep throat is endemic in the US**Epidemic**– a sudden burst of an illness that comes and goes over a limited time**Pandemic**– an epidemic that bursts across the world not just one region**Spreadability**– how contagious is the disease, how many people will end up infected**Symptoms-**the experience of being ill, for example- fever, cough, headaches, loss of smell etc.**Asymptomatic**– literally means “without symptoms”. For COVID-19 it refers a person infected with the virus but has no and will have not symptoms**Presymptomatic**– This is a person who was infected with SARS-CoV-2, and will feel sick, but hasn’t yet

**Severity**– what harm does the disease cause, in terms of how sick you get and how many it will kill**Mask-**a mask is a loose-fitting cloth or textile that covers the mouth and nose loosely. A surgical mask is a mask used in surgery**Respirator-**for the purposes of the COVID-19 pandemic and other respiratory illnesses, a respirator is a mask that fits very snugly or tightly to the user’s face. An N95 mask is a respirator.**Personal Protective Equipment (PPE)-**PPE are any item that covers any part of the body with the design and intent of keeping viruses in the environment from infecting the wearer of the PPE. PPE’s include all masks (which includes respirators), face shields, eye shields, gloves, gowns.**Ventilator-**a ventilator is a machine that can force a person unable to breathe to inhale and exhale and control both effectively. They are sometimes called respirators, but during this pandemic the word respirator is now reserved for reference to a tightly fit mask.**Live Virus Swab**– this is the swab which attempts to swipe live virus from one’s nose or throat**to****see if you are currently infected.****Antibody Test-**(aka serology test) this is the blood test which looks for antibody to the SARS-CoV-2 virus**to****see if you have been infected in the past.**

**In this special COVID-19 update, we take on clarifying the bewilderment of pandemic statistics, and the question, how to avoid numbness.**

**A Basic Primer on Basic Numbers of the Pandemic**

Although the world is awash with a huge array of numbers that try to describe the pandemic, most of us really are interested in just three questions:

- How bad is this pandemic?
- How close am I and those I love to danger from this virus?
- Is the danger growing or shrinking?

Of course, related to these core questions are a number of more specific questions:

- What are the chances of my family and those I care for getting sick or even dying from this pandemic?
- How contagious is this virus?
- Is this virus spreading in my neighborhood now?
- Will this virus be spreading in my neighborhood in the future?
- What can I do to protect my family and those I care for from danger?
- What are the chances a treatment will stop the danger?

And there are many more.

The problem is that this virus and the disease it causes moves in complex ways. If we knew for a fact that a specific neighborhood would only be infected from March to July of 2020, we could take steps to be protected for 5 months knowing that before and after that time all are safe. But that is of course, not how viruses work.

So in the reality that it is complex, patterns shift, outbreaks happen in bursts not smoothly, we rely on learning from *patterns of information, *also known as statistics.

Before diving into the particular patterns of information that we are observing with this virus, a quick review of some basic patterns might prove helpful.

## Basic Patterns of Information (Statistics) Used in Describing Infections

One bit of information we would all like to know is- how many people in our neighborhood, or state, or country, or world, are infected right now?

If the infection we want to know about creates some obvious signal in everyone infected, that is a bit of information we could learn fairly easily. Take the example of chickenpox, a great majority of people who get that develop a very visible rash. Count the number of people with the rash and you know how many people have chickenpox.

But COVID-19 is not like that. We now know that at least half of everyone with this infection, and who are clearly contagious, have no such markers, and even don’t have *any *symptoms.

The only way to know how many people have COVID-19 is to do a test that swabs the nose or throat for the virus. That test is not perfect, but it helps.

So, our numbers primer for the pandemic start with statistics, or patterns of information, relating to how we figure out how many are infected, and where the virus is spreading.

**Truth in Testing- Basic Measures of Knowing how a Test Performs**

Very, very few tests are perfect, and some are very far from perfect.

Here we take a quick look at 6 ways one can describe how likely a test result can be believed. By the way, for any one person, for any one test, the result is either correct or incorrect. What follows is how we can describe patterns of tests being correct or incorrect.

An easy example is the rapid strep test. It can only tell us it is positive or negative. If I do that test on myself, and it comes back negative, that could be true (I don’t have strep) or false (I do have strep). For just me, it should be easy to find out which is the case, but if I look at a million rapid strep tests I could find out, is this rapid strep brand I use usually correct or incorrect, and how often for each. That information tells me how well the test performs

**False Results**

These are the famous trends we have all heard about- the false positive and the false negative.

- False positive. This is the chance that if you do a COVID-19 swab and the test says you have COVID-19, that you actually do not. It is usually reported as a percent, meaning, if you took 100 people with a positive swab, how many in fact, really do not have the infection? For COVID-19 swabs that number is quite low, it doesn’t happen very much.
- False negative. This is the chance that if you do a COVID-19 swab and the test says you
*do not*have COVID-19, that you actually do. It is also reported as a percent, meaning, if you took 100 people with a negative swab, how many in fact, really do have the infection? For COVID-19 that number is about 20% across all brands and times of test, but varies by brand of test and when you swab during your infection, with this number climbing the earlier you test.

**Predictive Results**

These are not widely discussed, but I like these numbers. They are closely related to false result rates, but not quite the same.

- Positive predictive value. This number is the chance if you have a positive COVID-19 swab test, you are actually infected.
- Negative predictive value. This number is the chance if you have a negative COVID-19 swab test, you are actually not infected.

Of all the test performance numbers, these talk about the question we all have when we get a test result, if it’s positive what’s the chance I have that problem, and if it is negative, what’s the chance I don’t have that problem. Simply stated, easy to understand. No twists.

**Sensitivity and Specificity**

These numbers are very widely used and cited across all medical literature, but I find them the least useful, hardest to understand, and furthest away a direct sense if your test result is known, how well you know if you have the problem. These numbers ask a different question entirely, namely, how well does a test pick up on people with and without the problem from a *group of people*.

There are very good purposes to knowing how a test performs across a group of people, but that sort of description of how a test performs can be very misleading when it comes to one person, which is how each of us of course experience all of our tests.

- This number asks, if you have a group of people, some with COVID-19, some not, what percentage of those with COVID-19 in the group will be found by the test whose sensitivity is being measured.
- This number asks, if you have a group of people, some with COVID-19, some not, what percentage of those
*without*COVID-19 in the group will be found to be negative by the test whose specificity is being measured.

Hopefully, you can see these patterns of information, sensitivity and specificity talk about a very specific type of performance a test has, which relates to groups, and not individuals. It reminds me of averages. Averages are about patterns of information defined by the group and speaking about a group. A group can have an average height, a person can only have one height.

**Case Counts**

- What the number counts: This statistic counts how many people have been
*diagnosed*with COVID-19 - How the number is created: Count all the people who have been swabbed whose test came back positive
- Issues with the number
- This number does NOT count anyone with the infection who has not been tested. Imagine if we tried to count how many babies would be born in Ohio by only counting the number of women who did a pregnancy test. There would always be more babies than pregnancy tests.
- Positive test results are reliable, but negative results can be misleading. Say you have the infection, but you test the first day of your infection, your test will almost certainly be negative. Even four days into the infection, about 66% of the tests are negative.
- Case counts vary wildly if the number tested varies wildly. Simply put, imagine testing for COVID-19 stopped entirely, the case count would go to zero, even though the number of people with COVID-19 would remain the same, in that moment.

- How this number helps
- We will never be able to know the total number of who has COVID-19, but the case number can give us some indication of if the number is large or small, going up or going down.

**Death Counts**

- What the number counts: This statistic counts how many people have died from COVID-19
- How the number is created: Count all the people who doctors have determined have died from COVID-19
- Issues with this number:
- The passing of life is often due to a number of causes, and more often that one might imagine, hard to know if COVID-19 played a role. Imagine a situation in which someone has long-standing heart disease whose heart stops. Was this death due to heart disease, or maybe an infection with SARS-CoV-2 fatally damaged the ailing heart, in which case COVID-19 was the actual cause.
- A number of people tragically die suddenly at home, and without an autopsy, the actual cause is never found.
- A number of deaths from COVID-19 happen in people whose test for COVID-19 is negative, which we know is wrong 20% of the time. Many reports document specific findings of COVID-19 in people whose course can only by explained by this infection, clearly dying from COVID-19, but the false negative swab test keeps that death from being counted as a COVID-19 death, and not included in the COVID-19 death count.

- How this number helps
- Sad to say, death is a visible event. Essentially every death is recorded. For an illness in which half of those infected have not symptoms, counting deaths is far more accurate approach to getting a sense if the pandemic is stable, fading, or surging.
- Patterns of death can be helpful in estimating how many unknown causes of death are due to COVID-19. Imagine that a city suffers 100 sudden, unexplained deaths at home a week, and that number has been steady for many years. Now COVID-19 appears, and that city now suffers 120 such losses a week. It is clear that some of those extra 20 deaths a week are due to the proven ability of COVID-19 to lead to sudden dying at home.

**Seven Day Rolling Averages**

- What the number counts: This statistic takes whatever number counted daily and adds that daily number across 7 days, and takes the average of that number. If that average is tallied and reported every day, one can graph that number daily, even though it is reporting the average counts of 7 days past. That is why it is called a rolling average, it rolls forward day to day. It is applied mostly to Case Counts and Death Counts
- How this number helps: Daily counts can vary wildly even if the progress of the pandemic is steady. By taking the counts across a 7 day period, the unavoidable sharp jags up and down are smoothed and trends in the pandemic become more accurately, and easily, observed.
- There are few if any downsides to this approach to finding patterns in information

**The R numbers**

The R numbers go by various names, such as R_{0} or R nought. The R always stands for Reproduction. The question these numbers try to answer is how contagious is the germ that is being measured. Some germs are very contagious, some not so much.

Perhaps the most contagious common illness is measles. The R_{0} for measles ranges from 12-18, which means if I have measles, go about my usual activities, in a place where no one has had measles, I will make about 12-18 people sick with measles by the time I get better.

Notice how this estimate for measles assumed I was out and about surrounded by only people who had never had measles. The R_{t }number, also written as Re, refers to the chance of spreading the virus by one person in a group that has already experienced the disease. This is called the *effective *Reproduction number, the t stands for time, since this measure takes into account how many people in a community have already had the infection, over time.

- What the number counts: All the various forms of the R, or Reproduction number, try to calculate just how many people with COVID-19 have infected how many other people with COVID-19, in a neighborhood, county, state, or nation. Take that number for that community, at that time, and you can estimate, on average, how many people one person tends to give COVID-19 to.
- Issues with this number
- There is no direct way to actually count this number. It is, by definition, an estimate, an attempt to observe
*patterns*of numbers. - The R number varies tremendously by how much people are in contact with each other. All the various R numbers go to zero if someone with COVID-19 is totally isolated for all other people, since that person cannot then transmit the virus to anyone. That makes all the R numbers a moving number, which can easily cause confusion.

- There is no direct way to actually count this number. It is, by definition, an estimate, an attempt to observe
- How this number helps
- If we really did know the R number for COVID-19 at any moment, in any place, we could know if the pandemic was truly going to fade away, stay constant, or surge in that place, in that moment. This is easy to understand if we simply consider that if the virus fails to spread to more than one person from anyone with the infection, the numbers of people infected cannot grow. It is just like a community where two parents always have two children, the population of the community will stay steady, not growing or shrinking much. That steady state where one person with COVID-19, on average transmits the illness to one other person is the well-known R
_{0}of 1. - If the R
_{0 }is over 1, then the number of people with COVID-19, in that place, at that time, will go up. - If the R
_{0 }is under 1, then the number of people with COVID-19, in that place, at that time, will go down. - The effect of a higher R
_{0 }is dramatic. Say that number reaches 2. That would mean each infected person would typically cause 2 new infections. After ten rounds one infection becomes 1000 infected, and another ten rounds leads to 1 million infected. If that number reaches 3, then the number after 10 rounds becomes 60,000 and after another 10 rounds,**5 billion.** **The R numbers define how we all will experience the pandemic- a wild explosion or a withering disappearance and do track how well our efforts to bring the spread down to zero are doing.**

- If we really did know the R number for COVID-19 at any moment, in any place, we could know if the pandemic was truly going to fade away, stay constant, or surge in that place, in that moment. This is easy to understand if we simply consider that if the virus fails to spread to more than one person from anyone with the infection, the numbers of people infected cannot grow. It is just like a community where two parents always have two children, the population of the community will stay steady, not growing or shrinking much. That steady state where one person with COVID-19, on average transmits the illness to one other person is the well-known R

**Last Pattern of Information to Discuss: Prevalence and Incidence**

These words do not come up much with COVID-19, so I’ll make this one brief.

Both prevalence and incidence are patterns of information that try to describe how many people have a problem, such as COVID-19.

One can talk about how many people **have **COVID-19 right now or during a particular period of time- that would be **prevalence.**

Or, one can talk about how many people **will come down with** COVID-19 will during a particular period of time- that would be **incidence.**

Again, this particular confusion does not come up much, but just in case the words cross your eyes, now you now what they mean.

**Numb Yet? What We Feel**

We close this tour of the patterns of information swirling around us with a moment of reflection on how we feel about this pandemic.

Even writing up each of these patterns of information, or statistics, challenged my sense of the humanity of this tragedy.

But keep in mind, whether it is the case count, or the rolling average, or the number reported dying from COVID-19, all these confusing numbers really are our very limited human attempts at figuring out some very, very basic questions. The questions we all have, and are so desperate to know, and manage:

- What are the chances of my family and those I care for getting sick or even dying from this pandemic?
- How contagious is this virus?
- Is this virus spreading in my neighborhood now?
- Will this virus be spreading in my neighborhood in the future?
- What can I do to protect my family and those I care for from danger?
- What are the chances a treatment will stop the danger?

As imperfect as all the numbers are, they do tell us a lot about these very simple but devastating concerns.

And what we know from our numbers and numbers from other nations, is that we in America have indeed suffered, suffered grievously, and suffered more than we had to.

The official number of Americans who will be counted as killed by this virus will reach 200,000 soon. As noted above, the imperfections of the tests, the imperfections of case counts and death counts means we have almost certainly already passed this number.

But all that means is that when the official count hits 200,000, we can be *very confident *at least this many of us have died from COVID-19. All in a matter of 9 months.

And given current trends, that number will absolutely rise, we don’t know how much, that depends on how well we act to stop its spread.

I remember looking on with horror when we saw the spread of COVID-19 in the US explode so dramatically that we learned that 5,000 Americans had died from it, more than in China!

Somehow, as the number dead climbed beyond 5,000, it seems the outrage of the loss has numbed.

I believe this has to do with the two essential faces of the disease- COVID can be harmless, and COVID can be deadly. Most of us only see the harmless face, so the loss of 200,000 seems distant, only affecting people not like us- people who are very old, or very ill. It feels good to feel, we are safe.

**But the main reason we present this tour of the numbers is to sharpen their meaning, in order to diminish confusion, so that we can take a moment each day, and ponder how mammoth our loss has really been. At a certain level, I fear the temptation to not really get upset that 200,000 of us died for no very good reason.**

**BOTTOM LINES**

- COVID-19 continues to spread across the United States causing illness and much death in its path.
- It will remain very hard to know exactly who has COVID and who does not, the tests are imperfect.
- Further counting cases and loss of life is inexact.
- These challenges to describing how this disease spreads can create confusion, but at its heart, the numbers are not confusing, the point remains crystal clear: COVID-19 continues to spread across our nation, with many, many people getting sick and dying, even today.

What makes the whole story so tragic here at home, is that dozens of nations have figured out how to use their patterns of information to essentially stop the spread of COVID-19. By any measure death from COVID-19 in these nations has essentially stopped, or been reduced to tiny numbers. People in these nations live, they go to school, they go to work, they play, without fear, but with eyes open and good actions.

Let us hope as we continue to monitor our numbers, we do not go numb, but remain feeling for the thousands and thousands of us hurt and killed by this threat, so that we all can take action to move our nation to stop the spread, stop the harm, stop the dying.

To your health,

Dr. Arthur Lavin

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