Science and Pseudoscience in Coronavirus Epidemics

There are many topics in science to study conronavirus in the fields of biology and epidemiology, from vaccine development to methods to help critically ill patients survive, from control of virus spread to prevention of infection. These are highly specialized fields, and the domain of biologists, medical researchers, and epidemiologists.  As a layman to these two fields, and a mechanical engineer, in this post I summarize my critical review of two specific topics - 1) understanding published statistics on covid-19 and prediction of infections, 2) the distance in social distancing.

Understanding numbers for the Pandemic statistics

CDC and state governments have issued orders and guidelines to contain the spread of the coronavirus.  After a few weeks we saw the obvious exponential increase of total confirmed infections and with about 1 week shift in time, the exponential growth in coronavirus death - see linear scale histograms below.

Near the end of March, the administration announced  that data showed the measures taken were working, and last week the administration/CDC proclaimed to see the light at end of the tunnel.  CDC claims are based on epidemiology science that logarithmic scaled histogram better reveals future trend, and the logarithmic curves for both total cases and death clear showed the slowdown of growth rates in both numbers.

Liner scaled data histogram

Logarithmic data histogram

Those announcements were ridiculed by some news media outlets  - one went as far as claiming "we are not in the tunnel yet". In front of the epidemiology science and real data last week, those outlets and pundits turned out to be the parties that should be ridiculed and disregarded.

There are more sophisticated models to predict the curves of  infections and deaths. Those models, e.g.  IHME model, are phenomenological, statistical in nature. The model predictions tend to have large scatter, high uncertainty (tip - think about weather forecasting models as an analogy). Remember that on March 29th, both CDC and Harvard school of public health announced that the covid-19 death would be at 200K! On April 9th, CDC announced that total death number should be closer to 60K!!

The models seem to predict trends well but not the numbers.

An interesting side story related to understand the statistics. A friend sent an urgent email on Saturday April 11, telling us that worst were yet to come for Texas. I was incredulous - I have been looking at the data daily, Texas has been obviously on a good trajectory. Most recent data April 10th new death, 26, April 11th, new death 19. Both real numbers were lower than previously projected numbers from the IHME model.

IHME projection for Texas

We checked the source of that "worst are yet to come to Texas", it was from CNN, the statement was actually true per the model projection, but what they did not mention in the report was what the worst was for Texas. We checked IHME website, and in fact Texas state government also announced the projection on Friday, peak death rate was to come on April 28th, 66 death per day - see chart above. This compares to what happened at New York, which was discussed in the same CNN report. NY has real peak death rate at 800 so far.  Considering Texas's population is about 1.5 times of New York state's. Texas will be 18 times better than New York on peak death rate per person count. Per current data trend, the real peak death rate should be lower than 66. CNN's sensationalized title and the content of the report gave only partial truth omitting critical information - it distorted the truth, so it was fake news!

Projections are based on rigorous epidemiology models, but there are a lot of assumptions in the models, and the uncertainty in the prediction is very large, as shown in the shaded area in above chart, it is at order of magnitude level. If one is really interested, an in-depth understanding of model predictions as well as raw data are needed so we are not misled by media or any other entities.

What is the proper distance for social distancing?

CDC recommended 6 feet apart for social distancing in order to reduce the spread of conronavirus.  This is mainly based on the understanding that virus is mainly spread through droplets that come out of one's mouth and nose. When an virus carrier speaks, exhales, coughs or sneezes, the droplets travel about three to six feet before gravity pulls them to the ground.

As mentioned in the previous section, in the real world the recommended social distancing and other measures - most significantly "shelter-in-place", has been working its magic.

On March 31, US Today reported a publication by a MIT associate professor, Lydia Bourouiba, in Department of Civil Engineering, in The Journal of the American Medical Association, stating "droplets carrying coronavirus can travel up to 27 feet", and discussed about its potential implications.

USA Today wrote "Her research could have implications for the global COVID-19 pandemic, though measures called for by the Centers for Disease Control and Prevention and the World Health Organization call for six and three feet of space, respectively." A few other outlets reported the JMMA publication, and wondering aloud if 6 feet is enough.

I reviewed the JMMA  publication, and checked  the professor's research background.

First the publication is not a peer reviewed technical paper, it was an opinion piece - JMMA insight.

Second, upon checking the professor's MIT webpage, it indicates that her group has been working on the droplets' fluid dynamics for a few years.

Based on her past publications in technical journals, such as journal of fluid mechanics, a top journal in fluid mechanics, I assumed that the fluid dynamics part of her comments in JMMA insight to be technically correct.

The question is if the work has implications to CDC 6 feet distancing guideline. In the following I show that the JMMA insight has no practical value for social distancing guideline.

A general guideline related to cough and sneeze is "cover your cough". This has been a guideline for many years and is emphasized for covid-19 prevention. When people do cover their cough then the projection of virus carrying droplets are very limited, smaller than 3 feet for most case.

covering your cough prevents virus carrying droplets from traveling far 

For flu and covid-19, people with symptom are requested to stay home before symptoms go away. The 6 feet social distancing is more for prevention of virus spread from asymptomatic people. In this case virus being coughed out is a small probability event. If everyone, or most people (95% +) do their job to cover their cough or sneeze, then increasing social distance becomes a moot point!

The social distancing is to prevent spread of the virus from normal conversation, breathing - in this case 6 feet is more than enough.

So for prevention of virus spread from asymptomatic persons. the most important guidelines are, 1) wash hands frequently after each potential exposure, e.g. touching door knobs, using other's keyboard or mouse ....2) cover one's cough and sneeze.

The projection of droplets carrying virus to 27ft is a small probability event in real world. It is good to know that it can happen under certain conditions*, it is bad to be the base to change social distancing guideline.

It is pseudoscience to claim a single factor experimental results under "ideal condition" to be general enough for policy change. To the least, changing the social distancing guideline based on the MIT work would be misguided.


* how tall the person is, vital capacity, how hard the cough is,wind/air flow direction  ....