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Data, Models & Misinformation on the Coronavirus

· Coronavirus,Data,Big Data

Data, Models & Misinformation on the Coronavirus

With the world gripped in a panicked state of fear, everyone is looking to learn more about the novel Coronavirus and its lethal capabilities.

The virus has spread to more than 200 countries in a few short months and has been responsible for more than 30,000 deaths globally.

Now models are appearing that forecast millions of people perishing from this virus throughout the United States. Mortality rates are being thrown around and the anxiety of the nation is at a very high state.

But, simple models can be applied to the United States to disprove the potential doomsday outcomes.

The current number of registered infections, as of March 28th, is at 120,000 patients in the US with nearly 2,000 deaths.

However, as we reported in a previous article, the Director of Ohio’s Public Health estimated over 100,000 novel Coronavirus cases in Ohio alone. Ohio’s population accounts for about 4% of the overall US population, so extrapolated from the Public Health Director’s statement, there could have been as many as 2.5 million infected patients throughout the country several weeks ago.


In fact drive-thru testing was only available in all 50 states in the last 24 hours. Most people report a very hard time acquiring a test. So who is being tested? The sick -- those with symptoms that a doctor approves for testing. This will skew the data in the wrong direction.

How can we only test those who are sick and divide the number of deaths? The fatality rate will be horribly high.

Consider the Diamond Princess cruise ship. Back in early February the ship was stopping in Hong Kong, when one of its passengers disembarked and acquired the virus from a local host. When the ship made it back to Japan it was denied entry at first due to its Coronavirus outbreak and then anchored for several weeks in a quarantine zone.


What you end up with is a perfect controlled experiment, albeit for the skewed older age. The Diamond Princess had an average age of 62 among its passengers, much higher than the 38.2 average age in the United States. And as we have seen from all of the data, the novel Coronavirus has a deadlier outcome with older patients -- something Italy has witnessed with their elderly population in their north.

The 3,400 passengers of the Coronavirus were essentially locked in a large metal testing mechanism with a rampant virus on board. Yet, the fatality rate among those on board was .3% and the infection rate was a staggering 20.5%, 700 passengers.

This is a highly infectious disease, but these were closed confines and an elderly population base. The United States is a highly spread out country that is not using the same water and air systems. Think about how many methods the virus had to spread onboard the Diamond Princess; the boat was practically a petri dish.

The upper bound of potential deaths from the novel Coronavirus are almost impossible to predict, as many have died already that were not tested. And at the same time others are dying from bronchitis and being labeled as a Coronavirus death, simply because the virus was found in their system. Frankly, a hospital, as healthcare workers are finding out, is an awfully good breeding ground for a virus.

But, assuming that 20% of the US population contracts the disease with a 1.4% fatality rate, we could be looking at 900,000 deaths. However, the idea that every person in the United States will have some contact with another and that social distancing will not slow the spread is absurd.

A typical cruise ship around the size of the Diamond Princess will have around 1 million square feet, which with 3,400 on board yields about 300 square feet of space per passenger. Of course, this is meaningless, since the crew was constantly on the move spreading germs. But, staying with this logic, the US has 3.8 million square miles, when divided by a population of 300 million we get 1 person per 1.26 miles. Not quite the size of a cabin on a luxury cruise ship.

Playing devil’s advocate we must create a separate model for dense cities such as New York, Chicago and Los Angeles. Furthermore, 84% of the US population lives in urban areas now. So considering the nation’s entire size is also faulty logic.

So really two models should be created, one of urban centers and another of those Americans who live in rural areas. But, creating such a model is engaging in mathematics and data science with slippery slopes everywhere you turn. So really the only conclusion one can make is to ignore models and predictions and use their own logic.

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Written by Alexander Fleiss, Edited by Michael Ding & Bryan Xiao

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