Since I’m not working as much or as hard these days, I thought I’d apply some of the problem solving & decision making concepts we use where I work on the Coronavirus situation.
At work, a crisis would be when a customer has a serious complaint about a specific product or system we sell; and then a second complaint comes in for the same issue from another part of the country, and then a third, and then a fourth, and so on. Suddenly, we may be overwhelmed with complaints on a daily basis. It won’t take long for top management to turn to various people in the company with two very urgent and fundamental questions:
- Why did it happen?!?
- What should we do?!?
In terms of “Why did it happen?”, I think that ship has sailed for this pandemic, so-to-speak. We could blame certain people, or governments, or the devil all day long while the other question would continue to loom large…“What should we do?”
Without boring the reader with arcane details, the process we use involves:
- Gathering data
- Sorting relevant data from irrelevant data
- Organizing and prioritizing relevant data in a meaningful way
- Tracking assumptions
- Looking at all the data (not just the data we like best)
- Reaching a conclusion and/or making a decision
Death
I’d say death is a very relevant piece of data for this pandemic. The closest equivalent at our company would be when a customer is what we call “Hard-Down”. This is when a problem has gone beyond a manageable inconvenience and has brought production to a “dead” stop.
For the virus, let’s stick with the U.S. only and using only recent history. This lowers variability caused by disparity in health care systems around the world and over the years.
Based on 7 recent flu seasons (2010-2016) in the U.S. from this source…
- Average number of flu cases per year = 25,300,000
- Average deaths = 34,571
- That’s 0.14%.
This also assumes flu vaccines were available to the general public which should keep numbers lower.
But I think it’s even more relevant to compare with the last pandemic in recent U.S. history.
Consider Swine Flu (H1N1) in 2009-2010 from this source…
- Number of cases = 60,800,000
- Deaths = 12,469
- That’s 0.02%.
Coronavirus (COVID-19) in the U.S. looks like this as of this morning…
- Number of cases = 69,197
- Deaths = 1046
- That’s 1.51%.
Hindsight will be 20/20 a year or two from now, but IF we act as with did with H1N1 in 2009 AND we end up 60,800,000 cases at 1.51% death rate, that’s 918,080 deaths!
Key assumptions:
- H1N1 from 2009 is just as contagious as the current strain of Coronavirus
- Mortality rate remains about 1.5% as more and more cases are confirmed
- Rate of unreported/unknown cases of H1N1 also about the same
Hospitalization
There’s talk of hospitals and hospital supplies being overwhelmed. On the job, this would be the equivalent of our Service Dept. being overwhelm with field service calls and part orders to the point where we could not service customers in a timely manner. This includes customers with the “crisis” problem as well as customers with other serious problems.
Based on 7 recent flu seasons (20101-2016) in the U.S. from this source…
- Average number of flu cases per year = 25,300,000
- Average hospitalizations = 388,571
- That’s 1.54%
Swine Flu (H1N1) in 2009-2010 in the U.S. from this source…
- Number of cases = 60,800,000
- Hospitalizations = 274,000
- That’s 0.45%
Clear COVID-19 hospitalization data seems difficult to find, but anywhere I look the rate seems huge. Even if we take one of the lowest numbers from this source…
- That’s 14.3%
Once again, hindsight will be 20/20 a year or two from now, but IF we act as with did with H1N1 in 2009 AND we ended up 60,800,000 cases with a 14.3% hospitalization rate, that’s 8,694,400 hospitalizations! Can our system handle that surplus? I doubt it, but that’s another study.
Once again, key assumptions:
- H1N1 from 2009 is just as contagious as current strain of Coronavirus
- Hospitalization rate is about 14.3% as more and more cases are confirmed
- Rate of unreported/unknown cases of H1N1 also about the same
Keep in mind that if absolute numbers for COVID-19 stay relatively low, one could easily say, “See, told you; it was because of all the preventive action.” If absolute numbers get relativity high one could easily say, “See, told you; imagine the numbers if we did not take the action we did.” But a percent is a percent, so you can compare more directly to seasonal flu or other pandemics.
I don’t deal with life and death where I work, but if one needed to make a decision on what to do based on the data & assumptions above, I think any lay person can conclude at least one thing. Action should be significantly greater than whatever is done during the normal flu season or whatever was done back in 2009 for H1N1.
Pray for those who make such decisions…it’s certainly above my paygrade.
For example, they breathlessly report that NYC has 30,000 COVID 19 positives. Alack and Alas! The Sky Is falling!! They are not screaming that 8,368,748 (2081 est. 8,398,748 – 30,000) NYers do not test positive for the Wuhan Flu. Big statistical fallacy: New York City is the most densely populated major city in the United States, plus it’s worse than the typical third world shithole.
Every time Gov. Cuomo (feverishly running to displace Biden as Dem nominee) opens his yap, my brain screams, “BOHICA!”
So, I think the precise numbers are not so precise. At best, the stats’ levels, directions and magnitudes may be utile. Otherwise, it’s all computer models based on some ‘Einstein’s’ assumptions, estimates, forecasts, political agendas, etc.
I always assume at play is the prime directive: “Get Trump.” Ergo,
We don’t calculate flu cases the same way we’re calculating Wuhan Flu cases, so your premises are flawed. My guess is the 1.4% death rate represents a worse than worst case scenario.
Ernst,
Main purpose was to compare to the last pandemic (H1N1), but can you explain how flu cases are calculated differently than Wuhan Flu?
Perhaps this impacts analysis:
https://www.dailywire.com/news/epidemiologist-behind-highly-cited-coronavirus-model-admits-he-was-wrong-drastically-revises-model?utm_source=facebook&utm_medium=social&utm_campaign=mattwalsh
They guesstimate total number of flu cases because the only ones that get reported are the ones who bother to seek out medical attention.
I had the flu in ’18. Stayed in bed for three days and then spent another four wandering about the house looking like Hawkeye Pierce after a hard night a Rosie’s. Never saw a doctor.
My understanding is they have a formula to account for mild cases like mine.
I do appreciate what your endeavoring to accomplish here.
We all want to understand what’s happening so we can make informed decisions for ourselves and our families.
Phillip & Ernst,
Agreed; a lot of unreported cases changes things a lot.
Note assumption #3 in the post:
3.Rate of unreported/unknown cases of H1N1 also about the same
There are also a lot of cases of Pneumonia that result in death that the CDC counts as flu. It may or may not be the flu.
Ben: Thanks for the analysis. Much has been also said about Prof Ferguson’s recent comment that the UK death count will now likely not rise above 20,000. In fact, he noted they found the virus lethality was about what they expected and it was slightly more transmissible than they predicted. Quote: “…Ferguson, appearing via videolink, explained: “We assessed in that report on the 16th of March that fatalities would be probably not likely to exceed 20,000 with effectively a lockdown and intense social distancing strategy”. The key to his comment seemed to hinge on the effectiveness of the lockdown and social distancing strategy. If the UK had not implemented those actions, the earlier studies still accurately predict there would have been a much higher death count. Those proactive measures had a positive impact. But his testimony counts more than my comments. His video to Parliament is here: https://thenationalpulse.com/commentary/revision-coronavirus-model-imperial/
“Coronavirus (COVID-19) in the U.S. looks like this as of this morning…Number of cases = 69,197…Deaths = 1046…That’s 1.51%.”
You have made an error. All cases will resolve with either a recovery or a death. To get the true death rate, you need to use the sum of recoveries and deaths, not the number of cases. The unresolved cases are still developing, and will develop into either deaths or recoveries. As of this morning the true death rate in the US was 3.5% when using deaths and recoveries to determine the mortality rate.
Good point Alphatron. 3.5% is much worse.
This site, however, seems to be calculating about the same as I did at about 1.5% with case fatality rate.
https://www.cebm.net/covid-19/global-covid-19-case-fatality-rates/