How the “precautionary principle” backfired during the pandemic

Every policymaker’s dial was turned to ten — and not much thought has been given to unintended consequences

Erring on the side of caution is generally sensible, both personally and in making public policy. But erring on the side of caution without considering the foreseeable side effects and consequences of public policy choices can lead to unintended consequences.

We can now identify a number of key policy “dials” that were, in the name of erring on the side of caution, effectively turned up to “ten” in each case. This seems to have backfired, we are now learning as we steadily obtain data showing that lockdowns not only didn’t work to reduce casualties from the virus, but may in many cases have led to significantly more harm than they prevented.

A peer-reviewed study published in early 2021 in the journal European Journal of Clinical Investigation (written by four Stanford professors) concludes, after looking at policy choices in ten different countries, that lockdown measures had “no clear, significant beneficial” impact on reducing the impact of the virus in any of the ten countries examined.

Why not? Because voluntary measures seem to achieve the impacts that lockdown measures are designed to achieve — but voluntary measures don’t come with the draconian social, economic or political costs that lockdown measures entail.

Now that we have good data showing that lockdowns don’t seem to work we need to go back and review the policy choices we’ve made in the US and elsewhere and figure out how we got here. Why were key policy choices made without significant public debate or good data? Why did we let panic become part of policymaking?

In the U.S., a number of key policy choices (“dials”) were made early in the pandemic that dramatically affected how later events unfolded. And as we’ve seen now, with new data showing that lockdowns and related policies probably don’t work, many of these policy choices seem to have backfired and may even have caused more harm than benefit.

Let’s review a few key examples that led to the imposition of lockdowns, all in the name of “erring on the side of caution.”

PCR test development

It is now widely acknowledged that development of the CDC’s PCR test early in 2020 entailed many major failures, and this has been reported by the Washington Post, NPR, ProPublica, and others in some depth. CDC’s team explained their “erring on the side of caution” approach in a peer-reviewed paper: “We designed … specimen screening to confirm virus detection when present at low concentrations and to reduce the possibility of false-negative results ….” (Lu et al. 2020.)

The public lab troubleshooting of the new PCR test in February of 2020 led to high rates of false positives (not false negatives), alarming the labs and CDC. Rather than determine why, specifically, these false positives were occurring, CDC instead omitted the specific test component it thought was yielding the false positives. We know now, based on simply searching the BLAST public database of genomes, that all of CDC’s PCR test primers and probes are commonly found in both human DNA and microbial DNA.

Why wasn’t this rather serious issue (what ProPublica called a “software bug” in a severe understatement) caught early on and corrected? What level of false positives is acceptable in order to minimize false negatives? How many of the test positives still being detected are false positives?

Case definition development

CDC develops a new “case definition” for every major illness as it arises, in order to have a standard for identifying and diagnosing cases of the illness. CDC produced its interim case definition in early April 2020 and for almost the first time in its history, with respect to respiratory ailments, it chose to define a “confirmed case” of Covid-19 based on a lab test only, regardless of symptoms.

CDC knew this was a major break from precedent but made this choice out of fear of asymptomatic spread of the illness, based on early reports out of China about the possibility of asymptomatic spread. This was another case of erring on the side of caution, but it led to an explosion of tabulated cases, based only on a positive test result, many of which should not have been considered positives.

We know now that asymptomatic spread seems to not be a substantial risk. A study of 10 million Chinese in post-lockdown Wuhan found zero cases of asymptomatic spread. (Cao et al. 2020.) Studies that find to the contrary are generally based on assumptions and models rather than actual data. (E.g. Johansson et al. 2021.) Why?

PCR test “cycle thresholds” were set way too high

We also know now that the PCR tests had a very high false positive rate because CDC and test manufacturers chose not only to err on the side of minimizing false negatives in creating the test itself, but also to err on the side of excessive amplification of the viral signal by using an overly-high “cycle threshold.” Scientists who work with PCR know that most anything over 30 cycles is amplifying noise and not a real signal.

Dr. Fauci highlighted this issue in July of 2020, stating publicly that for anything over a 35 cycle threshold “the chances of it being replication-competent [i.e. infectious] are minuscule… It’s just dead nucleotides. Period.” Unfortunately, to this day FDA’s instructions for use of CDC’s PCR test (p. 26) recommends a cycle threshold of 40, despite the abundant evidence that this is far too high for a meaningful test result. The widely-used Cepheid PCR test uses a cycle threshold of 45!

Many Asian nations, such as China, Taiwan, South Korea, Japan, and India, that had relatively low case counts and deaths have generally used 35–37 PCR cycle thresholds. This correlation is very likely not accidental.

Defining Covid-19 deaths

It is now well-known that many states have been counting almost any death associated with a positive PCR or antigen test, or even cases that didn’t involve testing, as Covid-19 deaths. Why?

Well-established death certificate guidelines were abandoned in favor of a new policy that every death that could conceivably have been related to Covid-19 should be recorded as a Covid-19 death. Similar to the CDC case definition relying solely on a positive PCR test for a “confirmed case,” CDC and state-level public health officials simply defined any death associated with the novel coronavirus as a “Covid death,” regardless of causation.

Dr. Deborah Birx stated this clearly in a June 2020 White House briefing: “if someone dies with Covid-19 we are counting that” as a Covid-19 death.

CDC yet again turned the dial to ten in issuing its official guidance for completing death certificates, in documents issued in March and April of 2020. CDC’s guidance didn’t even require a test result to conclude that a death was a Covid-19 death with respect to a death certificate. The linkage could be assumed and it was enough that Covid-19 contributed to death rather than causing death: “COVID-19 should be reported on the death certificate for all decedents where the disease caused or is assumed to have caused or contributed to death.”

Then, any inclusion of Covid-19 on a death certificate, whether it was listed as causing death or only a contributing factor, is tallied as a “Covid-19 death” by the states and CDC.

This is not by any means an exhaustive list of policy over-reaction. Essentially, every place we look for a dial that policymakers could turn to ten they did turn it to ten.

What resulted was a highly flawed testing system and highly flawed disease surveillance and data collection systems. I do not fault any particular person or persons for what happened. It seems to have been a result of a vicious circle of panic breeding panic at every level.

But we simply must learn from this experience and not repeat it.