# COVID and Kids

[Updated November 3, 2021 to reflect comments from Phil Kerpen (@kerpen). I have appended Phil’s Twitter thread at the end of this article.  I have also added a thread by Emma Woodhouse (@EWoodHouse7) debunking the 744 total deaths reported by CDC.  Finally, there is a new version of my Excel workbook that lets you plug in any figure you want for the percentage of the CDC estimate you’d like to assume.  The Excel workbook uses 65% as an example. There is a third workbook that uses NCHS numbers as cited by Emma Woodhouse.]

 Phil Kerpen Emma Woodhouse

I’ll note in passing that Emma Woodhouse may well be a nom de Twit. Regardless, she’s very good with data.

As noted, Phil Kerpen offers a lengthy critique of the CDC data.  Here’s a summary tweet:

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That put me on to this table from Emma Woodhouse:

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With that as background, let’s look at the data.

## How Many Kids Have Died From COVID?

How many kids have died from COVID? Using two different datasets, I calculated deaths from all causes as listed by the CDC in 2019.  COVID deaths are the latest available from CDC.  The CDC is also responsible for the odd age ranges.  Bottom line on COVID and kids ages 1 through 17: 774 total deaths out of a total population of 72,187,014 or 0.00107%. Conclusion: spend more on protecting kids from accidents, homicides, and suicides.  Masking kids in schools — or anywhere for that matter — has costs that far outweigh any conceivable benefits.

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My total above is 9 more than Emma’s CDC total.  Given the uncertainty about these figures, that difference is negligible.

I’ll go through the various assumptions and calculations I made to get the numbers at the end of this article.  The main issue is that the age brackets used by CDC for deaths by causes and ages are different from the COVID age brackets.  There are also a few other inconsistencies.  But first let’s see the real dangers kids face. (The graphs are difficult to read.  Click here to download the Excel workbook with the data and clear graphs.)

## Causes of Death by Age Group

Let’s start with the babies, ages 1 to 4.

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Accidents are the leading cause of death for each of the four age groups. For the 1-4 age group, the ubiquitous “all other causes” is second, followed by congenital malformations, malignant neoplasms, and homicide.  Yes, you read that correctly.  Very young kids have a greater chance of being murdered than of dying from COVID. One item missing from this list is suicide.  Sadly, that makes its first appearance among the 5 to 11 group.

The percentages are important.  The vertical axis is percentage of population in that age group.  Of the 19,422,515 kids in that age group,  1,149 died from accidents (0.00592%). COVID deaths total 244, 0.00126%.

Next up, the group 5 to 11.

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Accidents once again are the leading cause (1,025 or 0.00364% of the 28,162,647 in this group). All other causes (883, 0.00314%) is next followed by malignant neoplasms (533, 0.00189%), homicide (231, 0.00082%), and suicide (214, 0.00076%).  COVID is in seventh place with 171 (0.00061%).

Before going on, note one thing.  These percentages are tiny, miniscule, very small.  The chances of a kid dying in the U.S. today are incredibly small.  And the chances of dying from COVID are tiny relative to the leading causes of death.

Moving on to 12 to 15,

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Accidents (1,174 and 0.00711%) once again are the leading cause of death.  Sadly, suicides have moved up to second (762 and 0.00462%).  In order we have all other causes (712 and 0.00431%), homicide (490 and 0.00297%), malignant neoplasms (360 and 0.00218%) and COVID (198 and 0.00120%).

The final group is odd, ages 16 and 17.  I suspect CDC wanted to make sure the age groups only included kids in schools up to 12th grade. That has the detrimental effect of a much smaller age group than the first three (8 million compared to 16.5 million in the 12-15 group). For whatever reason, here are the statistics.

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Accidents are once again the number one cause of death (1,415 and 0.00502%).  Suicide is next (884 and 0.00314%) followed by homicide (751 and 0.00267%).  All other causes (528 and 0.00188%) and malignant neoplasms (236 and 0.00084%) are just ahead of COVID (161 and 0.00057%).

## The Kerpen – Woodhouse Alternatives

Phil Kerpen says the actual number of COVID deaths is 35% less than the CDC numbers.  Here’s what that looks like.  (Click here to download the Excel workbook that lets you pick any percentage you want.  For Phil’s numbers, the percentage is 100% – 35% = 65%.

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And here are the Woodhouse numbers:

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As promised, here are the links to the two workbooks.  For the 65% of CDC figures, click here.  For the Woodhouse – NCHS numbers, click here.

## Conclusion

Spending more on child safety and suicide prevention would seem to be a better use of public funds than worrying about masking kids in schools (or anywhere else for that matter).

## Methodology

Translating the mortality from all causes age brackets to match the COVID data took some effort.  I first tried various interpolation methods (cubic spline, Bissel) to see if I could get meaningful data for each individual age.  That was not successful (to put it mildly).  Instead, I just used linear interpolation.  Thus for the COVID age group was 16 to 17 and the all mortality group 15 to 19, I multiplied the all mortality deaths by 0.4 (two years out of five).  Similar procedures were used for the other three groups.  These calculations do not appear in the Excel tables.  To be sure the tables were sorted correctly, I replaced the calculations with the actual values.  (This is pretty easy in Excel.  Copy the data, then paste it into the same area using Paste Special – Values.)

Also, the all mortality data is from 2019.  This is before COVID.  I wanted to make sure COVID deaths were not double-counted in the data.  Naturally, COVID deaths are from January, 2020 through September, 2021.

I urge anyone who has a better methodology for any of this to download the Excel workbook and fix it.  When you’re done, please e-mail me the results so I can learn better techniques.

## Appendix: Phil Kerpen and Emma Woodhouse Threads

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## About Tony Lima

Retired after teaching economics at California State Univ., East Bay (Hayward, CA). Ph.D., economics, Stanford. Also taught MBA finance at the California University of Management and Technology. Occasionally take on a consulting project if it's interesting. Other interests include wine and technology.