Note: Averages have a *; Comparative Analysis and Pneumonia are highlighted in blue; COVID-19 is highlighted in Yellow
Weekly
Annual
Analysis, Benchmarks, and Factor Analysis
As of the end of Week 8:
- COVID is around 9.4 times more deadly than the High Flu peak weekly deaths benchmark
- COVID is the most prevalent form of death in the US based on averaged benchmarks
- COVID deaths have remained roughly even since last week (factor 1.02)
- COVID deaths exceed the number of average annual deaths for Firearms, Suicide, and Pneumonia.
Numbers which COVID does not exceed will be presented as X%. This denotes that the COVID mortality rate equals X% of the higher number.
Numbers that COVID does exceed will be presented as N. This denotes that the COVID mortality rate is N times higher than the benchmark number. A one (1) means that the numbers are equal, a two (2) that COVID is twice as deadly on an annual basis, etc.
All numbers are rounded to the nearest decimal.
Factor Analysis
Other info
Charts
I have received some feedback that visualization may help folks understand numbers better. I am testing a few chart ideas.
The first is a weekly death rate growth chart. I am trying to provide information not being presented in other locations and I have noticed almost all charts online are cumulative. The chart below shows rough week-to-week data.
The other chart below is a visualization of the Annual Table above without Cancer and Heart Attacks. This is due to the 'skew' those numbers present because they are so much higher than the others. They are mainly on the Annual Chart to show the two major causes of death in the US as comparison and to help give context to weekly numbers.
As always I welcome additional feedback to make the information presented here more relevant and easy to understand.
State Variability
State variability is becoming more of a factor in reporting totals. As reported in Week 6 there is a great deal of variability depending on what State you are in. As States open up at different rates I think it is important to show changes to this variability over time. I have had difficulty tracking this since WorldMeter does not break State data down over time, just a total for the day. However, I believe I have a way to track week to week now.
Starting this week I will be including a 'Top 10' list to show where deaths from COVID are most prevalent and to show changes over time.
There are still limitations in this data. In particular, New York/Jersey are really centered around the New York City (NYC) metro area. So while their numbers are separated, they can be seen as the same 'cluster.' Also, both counts can't really get the NYC cluster out from the rest of the State. If I can figure out how to do it, a better way of displaying this would be to show NYC, then everyone else. I will continue to work on that as I move forward.
Finally, it will be easy to make correlations from the data presented below. In particular, 'colder,' States are bearing the brunt of this as are higher population States. I would urge caution in both of those assessments. While there might be some relation in both cases, experience tells me there are a number of other factors that are at play.
Top 10 States by COVID Fatalities
Corrections
Note: Change in Rank for this week is from Week 6. Future Tables will be from the previous week. Red highlights mean the State has moved higher, Green highlights mean the State has moved lower.
Two major corrections to previous data for this week. One, I got 'off-cycle' a bit a couple of weeks back and added a extra day into Week 5. It didn't have a major impact on any factor numbers or placements; however, I wanted to be transparent. It has been corrected moving forward.
Second, WorldMeter was able to back-fill a lot of the data from New York into their daily reporting. As such I was able integrate about half the numbers into previous weeks data. You will see this reflected in the 4/25 reconcile. One side note, while I don't revise weekly placements, Week 6 saw COVID move from #3 to #2. Overall the Raw Annual number is much closer to the stated number without adjustments.
Finally, just a note that I am doing this as a side project in my free time. Errors and mistakes (particularly spelling and grammar mistakes) will occur but I will be as transparent as possible when I catch them or am alerted to them.
Also remember this is a on-going event. Changes should be expected, even large number adjustments. As I have said before, treat all numbers as preliminary and with an error range.
Next Update: May 2nd by 6 PM Pacific