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Tuesday, June 23, 2020

What Do The Latest Coronavirus (COVID) Data Reveal About Testing, Positive Cases & Deaths

Every morning we wake up to cable news channels like MSNBC, Fox, CNN or our local affiliates to reporters exclaiming "spiking" Coronavirus cases based on yesterday's test numbers.  They give us nothing to compare our numbers to or to baseline with.  As a result we are making decisions based on incomplete data.  As a statistician, I find this very frustrating.

I simply want all the data presented to me about the trends so I can make my own informed decision.  As any statistician will agree, more data points are always better than less.  So, Rhonda and I decided to do our own research as we did back in March at the start of this horrible pandemic.  Data we searched for to include in this report is comprised of :
  • COVID testing numbers by date
  • Positive COVID cases by date
  • Hospitalizations due to COVID by date
  • Emergency room admissions for flu like symptoms by date
  • Deaths due to COVID by date
  • Deaths due to cars accidents and the flu/pneumonia annually
So, lets look at the facts.

COVID Testing Trends
We will begin with a look at the COVID testing numbers which have been a hot issue as of late on the various news channels.  The data below is from John Hopkins University and The COVID Tracking Project. 



This chart is showing incremental and NOT cumulative testing occurring on a daily basis.  So yes, testing is way up!  And, we also see the percent of positive cases per day has decreased significantly since late March and early April (the line chart).

Does this make sense?  Yes of course.  Initially, only those tested were those that were highly likely ill.  As a matter of fact, they were the only ones allowed to be tested.  Today, testing is open to anyone and testing centers are finally, thank goodness, everywhere including less affluent and predominately black communities (don't get me started on this).  As a result, many being tested today show no symptoms because they were either not sick or were asymptomatic.

But one concern we have based on this data is the recent uptick in the percent of positives -- since the opening up of America (around June 1).  This is something we do need to keep a close eye on and hope we get this to flatten quickly.  But all in all, good news with some caution.

Tracking Hospital Outpatient Visits for Mild COVID Symptoms

The U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet) provides data on visits for influenza-like illness (ILI).  Mild COVID-19 illness presents with symptoms similar to ILI.  So, ILINet is being used to track trends of mild to moderate COVID-19 illness and allows for comparison with prior influenza seasons.

The graph below shows the trend of this data.  The time line is reported as "year + week."  So, "202003" represents the third week of 2020, for example.




As we can see, the height of hospital visits for these Mild COVID symptoms occurred during the last week of December, 2019 through the 12th week of 2020 (end of March).  This is represented by the overall solid black line.

Today our percent of emergency room visits for such symptoms is well below the national baseline of 2.4% for the flu.  So again another good sign that we are at least moving in the right direction... assuming we continue to observe social distancing, hand washing, etc.

Tracking Emergency Room Visits for COVID Like Illnesses
NSSP is a collaboration among CDC, federal partners, local and state health departments and academic and private sector partners to collect, analyze and share electronic patient encounter data received from multiple healthcare settings. To track trends of potential COVID-19 visits, visits for COVID-19-like illness (CLI) and ILI to a subset of emergency departments in 47 states are being monitored.



Similar to the chart produced by ILINet (in the prior section), trends began on a downward slope around April of 2020.   And, currently for all emergency room visits, we are at a rate of around 1.9% for COVID and .8% for the flu.  Once again, we are heading in a good direction.

COVID Hospitalizations Over Time
Again, using data from the CDC we can track the number of hospitalizations for COVID patients.  To date we have over 23,000 such occurrences in the U.S.



As this graph shows we are currently on a downward trend regarding hospitalizations.  Again this assumes we maintain good social distancing and hygiene practices.  But all in all, good news.

One caution with respect to statistics on hospitalizations:  the data lags in reporting and is subject to review by many doctors prior to release to the CDC.  Thus, any patients with missing data are not reported until data is obtained so the absolute numbers understate the hospitalizations, but the trend is still meaningful.

Deaths Due to COVID
So, what do the real COVID mortality numbers look like?  What is the trend?  Again, a chart that the media outlets are just not showing us whether FOX, CNN, MSNBC or your local news...  which I personally find very frustrating and upsetting! 

Below is a chart showing the number of deaths by day for the US, Italy, Germany and the United Kingdom.  Please remember that the US population is anywhere from 4 to 5 times that of these other countries when comparing charts below.



To date we are still at around 500-800 deaths per day.  This is still much higher than the number of deaths due to the flu and pneumonia combined which stands at about 200-300 per day.  Flu deaths per year range from 30,000 to 60,000 while pneumonia deaths per year average around 49,000.  

Yes, believe it or not, each year we lose about 100,000 citizen due to the flu and phenomena.  A horrible figure.  Not that any loss is good, but the COVID figures above do appear to be moving in line with these other illnesses that we cope with yearly.

Weighing the Risks:  Car Accidents vs. COVID
Believe it or not, for most under the age of 45, your odds of dying in a car accident are significantly higher than contracting and dying of COVID.  Bloomberg New Media, recently did an in-depth analysis of this data.



So, for example, if you are 35-44 years old, you are 35% less likely to die of COVID than to die in a transport accident (0.008626% vs 0.0137%).   However, if you are 65-74, you are 9-10 times more likely to die of COVID than die of a transport accident (0.135047% vs. 0.01398%).  

NOTE:  0.135047% is not "13.5 percent" but rather ".135 percent" -- slightly more than one-tenth of one percent.

Please note that this complete analysis is only showing and analyzing national data.  We do realize that for various states or cities, other things might be going on due to lack of social distancing or lack of wearing face masks in public.  But on a national, bigger picture level, we do appear to be showing some light at the end of this very long tunnel.

Rhonda and I both hope this helps you put this terrible virus and pandemic in perspective.  We are just stating the facts and do apologize in advance for the lack of empathy that might appear in this report.  That was not our intent at all.  We are simply stating the numbers.

And as always, those at risk like the elderly or those with preexisting conditions, caution must always be exercised as the data also shows. 

Warm regards and stay healthy!
Perry & Rhonda Drake

Sources:
https://www.health.com/condition/cold-flu-sinus/how-many-people-die-of-the-flu-every-year
https://www.cdc.gov/flu/vaccines-work/burden-averted.htm
https://www.cdc.gov/nchs/fastats/pneumonia.htm
https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html
https://covidtracking.com/
https://coronavirus.jhu.edu/
https://ourworldindata.org/grapher/daily-covid-deaths-3-day-average?country=DEU~ITA~KOR~USA
https://www.bloomberg.com/opinion/articles/2020-05-07/comparing-coronavirus-deaths-by-age-with-flu-driving-fatalities
https://ourworldindata.org/coronavirus
https://ourworldindata.org/grapher/daily-covid-deaths-3-day-average
https://gis.cdc.gov/grasp/COVIDNet/COVID19_5.html



Tuesday, March 31, 2020

Understanding and Making Sense of the Coronavirus Pandemic Data in the US, Italy, and Worldwide. (3/31/20 update)

As a follow up to the analysis issued on March 24, which compared the United States to other countries, and reviewed the data on the basis of cases and deaths on a per 100,000 basis, the analysis that follows is an update of last week’s charts as well as an exploration of new questions raised in the past week.

The United States is approximately 30 days into the pandemic, and one can scarcely escape news and cautions about the coronavirus. As a nation is admonished to practice social distancing, wash their hands, and not touch their face, it is still possible to find individuals who do not heed these warnings. The entire country is learning about data, exponential growth of cases, and wondering if the shut down of businesses, home schooling and work from home initiatives are effective and how long they will last.

Meanwhile, some wonder if all of these efforts are worth it. Some wonder, how the coronavirus compares to the flu or other pandemics such as H1N1, and why the measures taken now have not been taken in the past for other flus, or outbreaks.

In the midst of all of these questions, while useful to aid understanding, it is critical for each of us to recognize, that the data sanitizes the reality that each death represents a person. Each person has a connection to a family, and each family grieves the loss of a loved one (maybe multiple loved ones) who fell victim of the virus. The data is merely a useful tool to address the problem. It can hopefully aid in understanding to bring about solutions, or change public behavior to save lives.

Updated curves—what do they show us?

Most people, those compliant citizens, or those considered essential workers, are keenly interested in knowing where we are on the curve. The question is, what is it we are looking for on the curves? The answer is simple. We are looking for a sustained slow down of the number of deaths (mortality rate). You may have discerned that this is a huge challenge for a country like the United States, since our country is a republic, with states each given the right to designate rules within their borders. We have seen Rhode Island, requesting incoming visitors from New York to quarantine, in addition, in Florida, visitors from New York are requested to self quarantine. This ultimately resulted in the Center for Disease control issuing a travel advisory for individuals from New York.

In the past week, New York City has become recognized as the epicenter for the coronavirus, the question is, where is New York on the curve, as the “canary in the coal mine” for the entire country?

What is happening at a national level?

The updated curves from our initial post last week for the United States versus selected other countries are shown below. As you will see on a national level, the curves have not changed much since last week. Following the updated linear curves, scaled to population, you will see logarithmically scaled curves.



The chart below plots the same curves on a logarithmic scale.




A logarithmic curve will show more clearly where the death rate begins to slow. Note here that the curve for South Korea stops climbing so steeply at day 15. Other countries such as Italy and Iran appear to also be slowing. However that is not the case for the United States, France or Spain.

What can we see at a more granular level within our country?

The chart below shows the difference in how the states of New York and Washington have been impacted versus the United States as a whole. New York City, and Seattle, were the first cities to have cases of coronavirus. The very high population density of New York City has fueled the spread of the virus. The situation in Washington, was one of the virus taking hold in a nursing home and being spread by workers from one nursing home to another.



Is the curve flattening? Is the mortality rate slowing down?

In the initial post of this series we discussed the use of a logarithmic scale. A logarithmic scale is one that scales on multiples of 10, with each increment 10 times higher than the one before. Such scales are helpful in some respects for epidemiologic functions since each individual infected can pass along the infection to a multiple of others. Thus, the function is not linear, it is exponential. That being said, our previous charts were normalized on a per 100,000 basis and presented linearly. This was done because we felt that the logarithmic scale was overstating what was happening relative to the infection rate. The New York Times did a good job of explaining this relationship. As previously mentioned, a logarithmic relationship will emphasize the point in which the growth rate slows by showing a flattening of the curve (more horizontal) rather than the steep (nearly vertical) slope of the line.

Much discussion online focused on where the inflection point was happening which would show us where we were turning the corner of the cases decreasing. In viewing the data in this way, it appears that New York is nearly at the point of the curve bending horizontally which would indicate the death rate is decreasing incrementally. Washington State, seems to already be past the point of the curve bending horizontally.



The United States is still seeing a climbing death rate as hot spots continue to emerge around the country.

What is it that the United States is trying to achieve? How will we know when we are there?

The United States is striving to see a decrease in the incremental daily mortality rate. The incremental mortality rate is the number of daily deaths, and to see for example fewer deaths occurring today than yesterday. In addition, the United States Coronavirus taskforce team would like to see this relationship (fewer deaths than the previous day) occurring several days in succession so we can be sure it is a legitimate trend and not just a random blip in the data.

The United States took note of the handling of the virus by South Korea. South Korea, really ramped up testing and became informed about patterns, who were the infectors, and how to handle the localized containment of the virus. Of course, even though there are positive lessons to learn about the handling of the virus by South Korea, it is important to remember that South Korea is a country with a smaller landmass, and smaller population.



Below is a side by side comparison of the United States mortality curve compared to South Korea both in linear and logarithmic scales based on cases per 100,000 population.

Linear Scale:



Logarithmic Scale:


Note that the curve for South Korea is flattening, but the United States curve is still increasing.

What are the challenges for the United States to drive the mortality rates down? Can we hope to achieve what South Korea has achieved?

The United States recognized that more testing was a key factor to get a handle on the infections, and to be able to predict hot spots. New York has emerged as an epicenter, but other hot spots are also emerging, New Orleans, Florida, and Maryland to name a few. Why is this happening? Put bluntly, in the United States, the compliance with stay at home directives and social distancing are not being met with a high enough degree of compliance. 


Spring Break partiers in Florida were clogging the beaches and many of the young revelers left South Florida only to return to other parts of the country to spread the virus.
In New Orleans, Mardi Gras went on this year as it does every year. In retrospect, many think perhaps, it should have been cancelled. 


In Maryland, it appears to be a timeline similar to many places across the United States, but given the population density, slow walking public policy geared to closing down restaurants, and bars, and limiting the size of gatherings simply did not take place quickly enough, and now they are emerging as a hot spot. Maryland’s first cases were reported on February 28, but orders to restrict gathering sizes were not made until March 12. Also, the virus has hit one particular nursing home in Maryland very hard.


In contrast, South Korea has through electronic surveillance by the government, employed monitoring strategies to predict the movement of the virus, and compliance of quarantine rules and enforcement when quarantine rules are violated. Enforcement comes by way of a strict quarantine period of 14 days for those found to have the virus, as well as those re-entering the country. There is a zero-tolerance policy for infractions, those who do not comply could face deportation, if they are a foreign national, or if they are a citizen of South Korea, they could face arrest and financial penalties. It should be noted in the sited article, that there were 11 known people who violated the quarantine in South Korea between March 13 and March 24.

The last sentence was emphasized with good reason. Eleven people violating the rules seems like a very modest number and in our reality it may seem sort of silly regarding why such enforcement (arrest and penalties) would be enforced. After all, if it was only eleven people, what is the harm? Let’s look at the data.

If each of the 11 original violators interacted with only two people, and then each of the subsequent infected people, who would not show symptoms initially, interacted with only two people (second generation) and this pattern carried out for seven generations, ultimately 1,397 people would be infected with the virus. See the snapshot of our excel spreadsheet below.



The assumptions of this scenario are very conservative, and based on each individual who has been in contact only is in contact with two others. Think about other scenarios, family get togethers, weddings, concerts, church services, public places where the contact rates would be much higher. This is where countries who are willing to do things like surveille their citizens to manage this crisis, have a kind of advantage because they can get much closer to 100% compliance than the United States can. It is debatable whether our culture in the United States would tolerate electronic monitoring and data gathering of its citizenry, even for a purpose as noble as the defeat of a pandemic. Or would we?

Are we seeing mixed messages from various leaders in the United States coronavirus task force?

Maybe we are getting mixed messages. In confusing and frightening times, it is human nature to hear the message that is most pleasing or resonates the most with you. We have some leaders (such as Dr. Fauci and Dr. Birx) who are very cautious and have predicted 200,000 deaths from the virus. We have others (primarily the president and other politicians) giving us a much more optimistic forecast with respect to the future of the country and when we can get back to “normal”. What is going on here? Who is right? Where will we end up?

In assessing the current set of solutions and resources at the disposal of the United States, we have a fixed and known numbers of ventilators and ICU beds. We also have a fixed and known numbers of doctors, personally protective equipment (PPE), emergency medical staff, etc. Epidemiologists have studied the virus, they have reviewed data from all countries who have faced this foe before and they understand the nature of the spread, as well as the nature of the affliction to infected patients. In the United States we have an assembled task force, and an entire agency, the CDC ready to make predictions, and many are asking who do I believe? Do I believe there will be up to 200,000 deaths associated with this virus in our country? Is that a reasonable expectation? How did the scientists arrive at this number?

While we are not inside the minds of Doctors Fauci and Birx, to know precisely how they arrived at their recently publicized estimate of fatalities, we can assume that as scientists, these numbers were based on facts and epidemiological models. But as a data scientist, it is clear to me that every model will have limitations of variables that it cannot take into account, so no model is perfect. To provide a worst-case scenario, we took the fatality rate seen by Italy (the country who has lost the most souls) and applied it to the US population. Italy has a population of approximately 60.5 million, the United States has a population of about 331 million. This makes the United States population about 5.5 times larger than Italy. Our worst-case expectation is that approximately 55,000 citizens would succumb to the virus and not 200,000.

In other words,

  • Italy has a population of 60.46 million. As of March 29, there were 10,023 deaths for a rate of .00016577.
  • Applying this rate to the population of the United States of 331,000,000 we would realize an ultimate number of deaths of 54,871. While this number is wholly unacceptable and shockingly large, it is still only about 25% of what Dr. Birx and Dr. Fauci have been projecting in the last couple of days.
To counterpoint the view of the scientists who are dealing with the facts as we know them now, the fixed resources that are counted and in place, we have a president with aspirations. The president is being optimistic and looking ahead when some of the fixed resources have been supplemented. Perhaps our president is overly optimistic. He is looking at the problem from many angles, with an eye of breaking the problem down with more resources. The president hopes to bring down the deaths by:
  • Producing more ventilators so that lack of resources in this regard does not contribute to deaths,
  • Reduction of regulations to speed vaccines and other medicines thus curing more people who might die were these medicines not available
  • Imposing travel advisories and talking up the virtues of the citizens in the United States to appeal to our sense of right and wrong to stay home, thus limiting the spread of the disease by the non-compliant citizens.
We have no idea what kind of reduction of deaths we would see from increased production of ventilators, or the increased production of medicines. These are precisely the kind of variables not included in current models. The one thing the model can account for, however is how compliance would impact the spread of the disease. This is a purely mathematical relationship.

The central issue is, we need to, as a country see that EVERYONE comply with the stay at home order, or it just doesn’t work. Some people just don’t want to sacrifice a little to achieve a goal. This is the crux of the problem, and as a free country, we have difficulty in taking away another citizen’s freedoms.

When we hear the words from our leadership, we all have a role to play, it is true. For many the role is to simply stay home. Don’t connect with others no matter how inconsequential you think it is. Call on the phone or skype or Facetime. That is OK. But person to person contact is NOT OK.

Our next update will be on April 7th.

Perry D. Drake, PhD 

    and Rhonda Knehans-Drake