Why Opening the Economy Before Mass Testing for COVID-19 is a Bad Idea

April 19, 2020 – I took a day off writing yesterday to do the annual right of passage, compiling all my tax information to send to my accountant. If that wasn’t enough to depress me, the persistent pest south of the border, President Donald Trump, was encouraging “activists” to protest against state governments that were not reopening their economies based on the man’s hunches, instincts, and his big “beautiful” brain.

Today, a new study presents a good reality check for Mr. Trump and those who want to open the economy quickly before mass testing.

In a COVID-19 antibodies study using serology and involving over 3,000 volunteers in Santa Clara County, California, it found that between 2.5% and 4% of those tested showed they had been infected by the virus.

If you are not familiar with serology, it is a method of determining whether someone has been infected by a bacteria, fungus, or virus. The technology has been around for a century and can detect infection where other forms of testing cannot. What it shows in an infected person is the production of antibodies. What it doesn’t show is if the immune system is producing a sufficient amount of these antibodies to ward off repeat exposures. It also may not show the presence of antibodies until weeks after a person is exposed to an infectious agent. Sometimes the presence of antibodies may not be from something recent, but rather from something that happened further back in time, making tracing back to the source of transmission difficult. As a result, serology tends to be used last in a testing regime.

But the Santa Clara results, at between 2.5% and 4%, suggest that the presence of COVID-19 in that county is 50 to 85 times greater than the number of cases reported so far. If that holds true for the general population of the United States, then the reported viral caseload as of this Sunday morning which stands at over 740,000 is underrepresenting the actual spread of the virus. At 50 times greater, it means 37 million Americans have been exposed, and at 85 times the number it means nearly 63 million have been infected by COVID-19 enough to produce antibodies.

Opening the Economy Means a Silent Spread of the Virus

Here’s where the opening of the economy becomes dicey.

The numbers quoted above are huge.

We don’t know how many would have had a relatively benign COVID-19 encounter. It is very much of concern that a vast majority may be asymptomatic or present symptoms not typically associated with the virus. Add to this that COVID-19 infections don’t necessarily produce the common symptoms we’ve read about, cough, persistent fever, shortness of breath, exhaustion, gastrointestinal problems, loss of sense of smell, and muscle aches and pains. And then there is the gestation period which can be anywhere from 5 to 14 days before symptoms present.

Infectious disease modelers earlier this month described COVID-19 as a silent spreader in three categories: asymptomatic, presymptomatic, and mildly symptomatic.  Chinese data (whether you believe it or not) clearly shows that positive test results without symptoms have been found in many of the infected with a quarter of those in follow-up continuing to show no symptoms.

The outbreak in the state of Washington in a nursing home showed that 56% of the 82 residents plus the support staff who tested COVID-19 positive in March were asymptomatic. Two weeks later many of them displayed a full-blown presentation of the disease. And in the period between first testing, these residents became silent spreaders increasing the infection rate. Similar results have been reported in other localities where there have been outbreaks of the virus.

And then there is this disturbing fact. A person who is asymptomatic or mildly symptomatic sheds the virus in normal daily activity. Anyone exposed to that person is likely to become infected but how the disease presents itself in them may result in little to no symptoms. And a silent spreader can infect large numbers of people who become far more ill than the initial host of COVID-19.

Mass Testing is the Priority

Before we can hope to go back to the near-normal, or a new normal, the Santa Clara results, along with others doing serology studies, need to be peer-reviewed and assessed for their validity. Only then can governments and the public begin to have confidence in relaxing the restrictions with which we are currently living.

We don’t know whether the Santa Clara study is providing wildly exaggerated results because of those who were tested, or if it is underreporting the real rate of infection. And Santa Clara’s demographics may not be representative of the rest of the country.

So what do those demographics look like? According to the Santa Clara county records the population distribution divides as follows:

• 53.8% White
• 25.6% Asian
• 24.0% Hispanic or Latino
• 12.1% other
• 4.7% mixed race
• 2.8% African American
• 0.7% Native American
• 0.3% Pacific Islander

Santa Clara County had 1,870 COVID-19 cases as of two days ago.

Compare those demographics to Bergen County, New Jersey, a current COVID-19 hotspot.

• 71.9% White
• 14.5% Asian
• 5.8% African American
• 5.0% other
• 2.5% mixed race
• 0.23% Native American
• 0.03% Pacific Islander

Bergen County had 11,863 COVID-19 cases as of 22 hours ago.

Do the demographics make a difference? Undoubtedly they can. For example, and this isn’t seen in the above demographic breakdown, if a population has a high percentage of people over age 60, or if it has a large number of those who are immune-compromised, or saddled with chronic illnesses like diabetes, heart and lung disease, obesity, kidney disease, and others, it is likely that COVID-19 infection rates will be as high or higher than the percentages coming from the Santa Clara study.

Do We Know the Current State of the Pandemic in the United States?

The answer is NO!

On March 1, 2020, the CDC reported 75 cases in total in America. Today just six weeks later the CDC data shows more than 740,000 cases.

There remain areas of the country with little reported exposure. For example, as of this morning, the Northern Mariana Islands reported 13 cases, Guam has 136, and Alaska 314.

If the 50 to 85-times estimate applies, even in these areas of limited exposure, COVID-19 is being underreported.

Instead of 13 cases, we are talking about 650 to 1,100 for the Northern Marianas.

Instead of 136 cases, we are talking about between 6,800 and 11,560 on Guam.

And instead of 314 in Alaska, we are talking about 15,700 to 26,690 cases, the vast majority of them silent spreaders.

Without mass testing including the ramping up of serology studies to determine COVID-19 antibody levels in the general population, the silent spreaders will remain unidentified and an ongoing threat as the United States and other countries wrestle with how and when to get back to near-normal in a post-pandemic future.