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Approaching the 700K Milestone

During the flu pandemic of 1918, historians and scientists estimated that the deaths were around 675K in the US; a few weeks ago, we breached it. Based upon the 7 day moving average of the death rate, we are a few days away from breaching 700K if we use the John Hopkins University numbers (JHU), which I think everyone else is using.

[Note: I enlarged the graphic so that the cumulative deaths number is legible.]

Image 1: Cumulative Deaths (Wikipedia, CDC, JHU)

Lately, it has been kind of difficult to read the trends because the written materials weren’t really jibing with my charts. My charts were showing dramatic declines in cases, deaths and hospitalizations but the news stories were all about the over run of hospitals and the impeding crisis care approach in hospitals. The news stories were for specific areas of the US (like Idaho and maybe Wisconsin or Montana) whereas I’m looking at the overall US. Also, I’m noticing that more and more states are not reporting as consistently, especially over the weekend so I start to look askance at the charting results. Florida is the most egregious example: they report only once a week despite having a terrible surge in cases.

Image 2: US Cases 9.27.2021 CDC

Image 4: US Hospitalization 9.28.2021 CDC

Image 3: US Deaths 9.27.2021 CDC

Image 5: US Positivity 9.25.2021 CDC

In all categories, I see both the US and regions declining after peaking sometime in August or September. I drew some horizontal lines to check to see if the southern region broke the January/February peak of the winter.

So, I have been a bit uncertain as to how to regard the data. Should I trust them or should I look at them with skepticism? I don’t know. I’m especially confused with Florida as it was mentioned in the news that Florida had changed their reporting methodology for deaths: the state had begun reporting deaths as of when the person actually died and not the date of when deaths are reported. Backdating to when the person actually died (deaths reporting has a lag time) is very useful for historical research but can be deceptive (I don’t know if that is the right word) when trying to discern trends on a day to day basis. Since deaths are reported with a lag time, what ends up happening is that the line curve will curve downward, sometimes dramatically, suggesting that the deaths count are declining when the downward line is really the result of lag time reporting.

Image 6.1: South – Cases 9.27.2021 – CDC

Image 6.2: South – Deaths 9.27.2021 – CDC

Image 6.3: South – Hospitalizations 9.28.2021 – CDC

I don’t know if you can see but Florida’s death chart shows a really strong decline in deaths which is due to the lag time in reporting so I have to discount that drop in counts. When I look at other states with similar downward curves, I now ask is that the result of a lag time in reporting? I know that my county or state has a lag time in reporting so the death count is ALWAYS declining and has been since the beginning. I never look at the death chart because the downward curve may not be real.

By this time, Florida’s decline in death rate may be real but that doesn’t jive with the story of anti-mask mandates, anti-vaccine mandates that I keep reading. You would think that if everybody is out walking around without masks and are unvaccinated, the population should be facing surges in counts. The only thing I could think of is that maybe despite all of the noise surrounding masks and vaccination, the people are actually complying with masking, social distancing and vaccinating but quietly. In looking at the vaccination map from the New York Times, I see that Florida is on its way to being one of the states with higher vaccination rates (they are approaching the colors of the northeast). If that is true, then maybe those declines in cases and deaths are real.

Image 7: Top 10 over last 14 days (Wiki as of 9.28.2021)

Image 8: US cases tower over everyone else (Wiki as of 9.28.2021)

Image 9: US deaths tower over everyone else (Wiki as of 9.28.2021)

Wrapping up, I see that the US is still number one in number of cases and deaths. We just outshine the world in that due to our polarized state. I don’t know if other countries suffer from the same polarization or not but these polarization sure are costly. It is hard to see but in image 7 on the left hand side in the box above, US 14 cumulative count of cases is about 4 times the next country, UK and UK was already way above its peers in Europe. This inability to get together to do what needs to be done is really striking for this era.

Sources of Data

WORLD : Cases and deaths from Wikipedia website https://en.wikipedia.org/wiki/COVID-19_pandemic_by_country_and_territory

US and STATES : Five main sources of data are available – Wikipedia, COVID Tracking Project, CDC, JHU, and HHS

COVID Tracking Project: The COVID Tracking Project was a collaborative effort of free labor overseen by The Atlantic. This project ended on 3/7/2021. The Atlantic’s COVID Tracking Project was provided under Common Creative license “CC BY-NC-4.0” and covered cases, deaths, hospitalization, and positivity, amongst other data.
API: https://covidtracking.com/api/v1/states/daily.csv
Table: daily

CDC: CDC has become a replacement for the COVID Tracking Project for me although the data will often come in a few days later. Hospitalization comes in a week later. I’m tracking cases, deaths, hospitalization, and positivity.
Centers for Disease Control and Prevention, COVID-19 Response. COVID-19 Case Surveillance Public Data Access, Summary, and Limitations
Table: rows

API:
Cases and deaths: https://data.cdc.gov/api/views/9mfq-cb36/rows.csv
Hospitalization: https://beta.healthdata.gov/api/views/g62h-syeh/rows.csv (Good data doesn’t start until about 7/15/2020)
Testing: https://beta.healthdata.gov/api/views/j8mb-icvb/rows.csv
Positivity: https://beta.healthdata.gov/api/views/j8mb-icvb/rows.csv

John Hopkins University (JHU): I rarely show these sets of data; I mostly use Wikipedia or CDC but sometimes I like to reference the JHU.

Please cite our Lancet Article for any use of this data in a publication (link)
Provided by Johns Hopkins University
Center for Systems Science and Engineering (JHU CSSE):

https://systems.jhu.edu/

Terms of Use:

1. This data set is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020.

2. Attribute the data as the “COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University” or “JHU CSSE COVID-19 Data” for short, and the

url: https://github.com/CSSEGISandData/COVID-19.

3. For publications that use the data, please cite the following publication: “Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1”

Website https://github.com/CSSEGISandData/COVID-19

HHS: Hospitalization data for US – can be US level, state level or county level

url: https://healthdata.gov/api/views/anag-cw7u/rows.csv

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