The Science of Social Distancing Never Said It Could Slow This Pandemic

By David Burns

A review of the scientific literature leading up the SARS-CoV-2 outbreak casts doubt on the wisdom of universally engaging in social distancing without consideration of costs.  Data accumulated on social distancing since its onset has only served to reinforce the ineffectiveness as a strategy to slow the pandemic.  However, it has been very effective at disrupting social cohesion.

It seems that overnight, sometime around March 15th, America was introduced to the term “social distancing.”  Rapidly, social distancing became nearly universally accepted, such that in just two weeks, by March 29th, the movement of Americans had been dramatically reduced.  Google Analytics data confirms this reduction in social contact, and those two weeks as a radical change in human behavior.  Humans are by and large social creatures, and yet everywhere they changed the way they lived nearly overnight, and cheered it.

Very few voices sounded opposition to this trend, and social distancing seems to maintain widespread support, rooted in a belief that it helped reduce a pandemic, and continues to do so. Questioning social distancing effectiveness can lose relationships, both of friend and family.  It can cost you your employment, should you vocally speak against it.  Finally, in some countries, as social distancing measures have been implemented by force, it can cost you your life.  Meanwhile, the costs of social distancing have been extraordinary.  Beyond the obvious economic destruction that it has brought to our planet, social distancing has had a tremendously negative health effect for many portions of the population.  Delayed medical treatments mean earlier death for some, and the effects of social isolation has exacerbated mental health issues.  We all see that the costs of social distancing are incredibly high.

So we must assume that the science on social distancing is airtight.  Any idea that produces such a trade off must be grounded in science and that science must say in advance what the trade offs actually are.

However, the science of social distancing does not say any of that.  For this article, I reviewed the four largest meta-studies I could find on social distancing.

Two of them focused on the available science on shutting down schools to stop an influenza pandemic (one from the NIH and one from a Community Preparedness Task Force.)
Jackson C, Mangtani P, Hawker J, Olowokure B, Vynnycky E. The effects of school closures on influenza outbreaks and pandemics: systematic review of simulation studies. PLoS One. 2014;9(5):e97297. Published 2014 May 15. doi:10.1371/journal.pone.0097297
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4022492/
and
https://www.thecommunityguide.org/sites/default/files/assets/Emergency-Preparedness-School-Dismissals.pdf

Both school studies assumed children play a vital role in the pandemic, which is not the case with SARS-CoV-2.

Another review from NIH focused on the science of workplace social distance intervention.  Ahmed F, Zviedrite N, Uzicanin A. Effectiveness of workplace social distancing measures in reducing influenza transmission: a systematic review. BMC Public Health. 2018;18(1):518. Published 2018 Apr 18. doi:10.1186/s12889-018-5446-1
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907354/

Finally, I purchased a review of all the literature available in the Cochrane Library (The Cochrane Library is a collection of databases in medicine and other health care specialties) on interventions to stop a pandemic.
JeffersonT, Del MarCB, DooleyL, FerroniE, Al-AnsaryLA, BawazeerGA, van DrielML, NairNS, JonesMA, ThorningS, ConlyJM. Physical interventions to interrupt or reduce the spread of respiratory viruses. Cochrane Database of Systematic Reviews 2011, Issue 7. Art. No.: CD006207. DOI: 10.1002/14651858.CD006207.pub4.
https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD006207.pub4/full?fbclid=IwAR12EKWh6Y9lrNqFeZgZz7cG1UYjwyXkcWS2vk74aGKtS-Xg9tKtFlYyF-8

One would assume, again based on what we know about the enthusiastic implementation of social distancing globally, that the science said the following:

• Social distancing is effective no matter the transmission rate or time of implementation
• The economic costs of not implementing social distancing would be catastrophic
• Studies using actual settings prove social distancing’s effectiveness
• Data analysis of the effects of social distancing implemented in March 2020 would clearly show a link between social distancing and reduced deaths
• A dramatic reduction in deaths could be achieved by universal social distancing

Let’s go through these 5 assumptions, one-by-one and see if they have any truth to them.

Assumption #1: Social distancing is effective no matter the transmission rate or time of implementation 

Reality: Social distancing, if effective at all, is only so for R0 of 1.9 or less, and when implemented early.

“The modeling studies reported that percentage reduction in cumulative influenza attack rate in the general population declined with higher R0 values”  - Ahmed, et al

“The greatest reductions (especially for the peak attack rate) were usually predicted when R0 was relatively low” - Jackson, et al

The science on this is probably the most agreed upon of all the literature available.  Social distancing, if effective, is most effective when the rate of transmission is 1.9 or lower and most effective when implemented near peak.  The higher the rate of transmission and the later implemented, the less effective.  The R0 of SARS-CoV-2 is estimated to be between 2.0 and 3.9 (https://www.coronadisease.us/).  

I could not find a single scientific analysis showing that the rate of infection would be reduced by social distancing after the peak has passed. In America, we are now 5 weeks past the peak, and social distancing is still being promoted, with no end in sight.

Assumption #2: The economic costs of not implementing social distancing would be catastrophic

Reality: Where scientific literature references economic costs of the “next pandemic”, the economic cost is quite mild, particularly in comparison to what we have witnessed.

“The economic impact of the next influenza pandemic in the United States, in the absence of vaccination and other mitigation measures, has been estimated to be $71 to $166 billion” - Meltzer MI, Cox NJ, Fukuda K. The economic impact of pandemic influenza in the United States: priorities for intervention. Emerg Infect Dis. 1999;5(5):659‐671. doi:10.3201/eid0505.990507

https://pubmed.ncbi.nlm.nih.gov/10511522/

Even after adjusting for inflation, an expected cost of ~$150-200 billion seems like a small price to pay compared to the economic destruction wrought by US policy.  I don’t think anyone who supported the massive interventions would have done so had they been able to put the cost into context.  All the more amusing is watching economists now try to claim that trillions were saved by the intervention.  How could that be, if the cost we were trying to avoid was far less than that? (Lockdowns saved trillions! Say models… https://wmbriggs.com/post/31028/)

There’s even an understanding in the scientific literature that the economic burden is increased with certain policies:

“The average total cost of saving a person is highest when schools are closed. This is due to added preventive costs such as care-taking of (healthy) children.” Barrett C, Bisset K, Leidig J, Marathe A, Marathe M. Economic and social impact of influenza mitigation strategies by demographic class. Epidemics. 2011;3(1):19‐31. doi:10.1016/j.epidem.2010.11.002. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3039122/

Assumption #3: Studies using actual settings prove social distancing’s effectiveness

Reality: No such studies exist or could be included in the reviews cited.

"This systematic review has several potential limitations. First, most of the included studies were based on modeling and few were in actual settings." Of those in actual settings, “The epidemiological studies showed that social distancing was associated with a reduction in influenza-like illness and seroconversion to 2009 influenza A (H1N1). However, the overall risk of bias in the epidemiological studies was serious." - Ahmed, et al.  

I could find only one study that was performed on humans in an actual setting without a high bias rating, which the Cochrane review referred to as Broderick 2008:

“Prospective, cohort study carried out in a military recruit training centre during the first 4 weeks of recruit training. Data were collected between February 2004 and March 2005 (duration of recruit training is not reported) It is not clear how the recruits were assigned to 'experimental' (closed) or control (open). Recruits were assigned to units on the basis of arrival order with no particular allocation scheme The study assessed if social distancing would reduce the incidence of febrile respiratory illness (FRI). Data were collected over 4 weeks for each new group of recruits

The authors conclude that social distancing did not reduce FRI and that environmental contamination rather than person to person transmission is the culprit in the spread of FRI.” -  Cochrane

So that leaves us with modeling studies.

“The quality of modeling studies was not assessed.” - Ahmed

Oh, cmon!  

I can’t find a single review of the quality of computer modeling in predicting the outcome of social distancing. 

Assumption #4: Data analysis of the effects of social distancing implemented in March 2020 would clearly show a link between social distancing and reduced deaths

Reality: A huge amount of mobility data has been collected and the there is no correlation, and even a slight negative correlation, between reduced social interactions and Covid-19 death rate

Since the beginning of this pandemic, Google and Apple have been collecting tons of data on social distancing.  As a gesture to the research community perhaps, all of this data has been made available for download.  The findings so far suggest little to negative correlation between social distancing and death rate.

See the attached screen shot.

Furthermore, you can’t predict what amount of social distancing would be implemented based on deaths or cases or hospitalizations.  Unfortunately, you can only predict it by looking at political affiliation, see second screen shot.

In other words, social distancing reflects political affiliation and has no predictive ability using actual data in influencing rates of death.

It appears that social distancing accomplished nothing but to further divide the Left and Right.

Assumption #5: A dramatic reduction in deaths could be achieved by universal social distancing

Reality: Even under ideal conditions, scientific recommendation is limited to targeted intervention and modeling outcomes have a wide range of findings and quality. No scientific evidence exists in real world scenarios that show a reduction in deaths can be achieved through universal social distancing.

There is no clear scientific consensus on how effective social distancing can be in reducing deaths from a non-vaccinated influenza pandemic. When a broader range of respiratory illnesses is included, the effectiveness becomes even less clear.  But ranges I have found tend to be ~25-75% reduction from the peak for implementing social distancing in workplaces and schools.  And even these predicted reductions come with significant caveats, such as

• R0 being in a range which does not appear accurate for SARS-CoV-2.
• Children being as impacted, or more so, than adults. Again clearly not the case here.
• Models being of high quality, which is unknown, and not even considered.
• Environmental factors being less important than person-to-person transmission.
• Social distance is targeted in high risk areas.

Keep in mind that the Imperial College model which compelled all Western governments into some form of lockdown predicted as much as 2.2 million deaths in the United States alone.  There were many other fantastic models produced that predicted hospitals overrun, fantastic amounts of beds needed, and on and on.  For nearly all of these models, social distancing was already baked in, and assumed to successfully reduce infection, which again is based on modeling for which nothing is really known about their quality.

So what can we conclude based on the science?

Here’s what the Cochrane review determined:

“We scanned 3775 titles, excluded 3560 and retrieved full papers of 215 studies, to include 66 papers of 67 studies. We included physical interventions (screening at entry ports, isolation, quarantine, social distancing, barriers, personal protection, hand hygiene) to prevent respiratory virus transmission.

There was limited evidence that social distancing was effective, especially if related to the risk of exposure...

There is insufficient evidence to support screening at entry ports and social distancing (spatial separation of at least one metre between those infected and those non-infected) as a method to reduce spread during epidemics.”

I can’t say it any better than that. There is very little scientific evidence that social distancing is effective at containing the spread of a pandemic, particularly this pandemic. The data available from our experience since March indicates social distancing is unhelpful.  However, it is overwhelmingly clear that social distancing has had dramatically damaging impacts on our lives, both socially and economically.

Without clear scientific evidence that we should all be social distancing, that means we are the experiment.  The experiment needs to come to an immediate end before any further damage is done.

The science on that is clear.

David Burns is a cyber security engineer living in Virginia Beach. He can be reached at dvdburns@gmail.com.