124k people dead in the US. How many is that?

It's hard for people to grasp how many 124,314 dead actually is. So let's try to visualize is in a couple of ways.

First, let's take a look at how many counties, sorting least populous to most, would fit into 124,314. Can anyone care to guess? Here's the full list.

Total US Deaths - 124,314
# County Name Population Running Total
1 Harding County, New Mexico 625 625
2 Treasure County, Montana 696 1,321
3 Thomas County, Nebraska 722 2,043
4 San Juan County, Colorado 728 2,771
5 Banner County, Nebraska 745 3,516
6 Slope County, North Dakota 750 4,266
7 Mineral County, Colorado 769 5,035
8 Terrell County, Texas 776 5,811
9 Hinsdale County, Colorado 820 6,631
10 Golden Valley County, Montana 821 7,452
11 Roberts County, Texas 854 8,306
12 Billings County, North Dakota 928 9,234
13 Camas County, Idaho 1,106 10,340
14 Alpine County, California 1,129 11,469
15 Sioux County, Nebraska 1,166 12,635
16 Motley County, Texas 1,200 13,835
17 Hyde County, South Dakota 1,301 15,136
18 Sheridan County, North Dakota 1,315 16,451
19 Issaquena County, Mississippi 1,327 17,778
20 Rock County, Nebraska 1,357 19,135
21 Sully County, South Dakota 1,391 20,526
22 Jackson County, Colorado 1,392 21,918
23 Cottle County, Texas 1,398 23,316
24 Glasscock County, Texas 1,409 24,725
25 Throckmorton County, Texas 1,501 26,226
26 Lane County, Kansas 1,535 27,761
27 Irion County, Texas 1,536 29,297
28 Taliaferro County, Georgia 1,537 30,834
29 Briscoe County, Texas 1,546 32,380
30 Comanche County, Kansas 1,700 34,080
31 Sherman County, Oregon 1,780 35,860
32 Hodgeman County, Kansas 1,794 37,654
33 Cheyenne County, Colorado 1,831 39,485
34 Garden County, Nebraska 1,837 41,322
35 Meagher County, Montana 1,862 43,184
36 Armstrong County, Texas 1,887 45,071
37 Steele County, North Dakota 1,890 46,961
38 Boyd County, Nebraska 1,919 48,880
39 Edwards County, Texas 1,932 50,812
40 Oliver County, North Dakota 1,959 52,771
41 Buffalo County, South Dakota 1,962 54,733
42 Garfield County, Nebraska 1,969 56,702
43 Gosper County, Nebraska 1,990 58,692
44 Clark County, Kansas 1,994 60,686
45 Stanton County, Kansas 2,006 62,692
46 Jerauld County, South Dakota 2,013 64,705
47 Worth County, Missouri 2,013 66,718
48 Mellette County, South Dakota 2,061 68,779
49 Oldham County, Texas 2,112 70,891
50 Burke County, North Dakota 2,115 73,006
51 Keweenaw County, Michigan 2,116 75,122
52 Wheatland County, Montana 2,126 77,248
53 Cimarron County, Oklahoma 2,137 79,385
54 Menard County, Texas 2,138 81,523
55 Culberson County, Texas 2,171 83,694
56 Highland County, Virginia 2,190 85,884
57 Dickens County, Texas 2,211 88,095
58 Miner County, South Dakota 2,216 90,311
59 Griggs County, North Dakota 2,231 92,542
60 Divide County, North Dakota 2,264 94,806
61 Grant County, North Dakota 2,274 97,080
62 Eddy County, North Dakota 2,287 99,367
63 Faulk County, South Dakota 2,299 101,666
64 Quitman County, Georgia 2,299 103,965
65 Renville County, North Dakota 2,327 106,292
66 Liberty County, Montana 2,337 108,629
67 Sanborn County, South Dakota 2,344 110,973
68 Greeley County, Nebraska 2,356 113,329
69 Niobrara County, Wyoming 2,356 115,685
70 McPherson County, South Dakota 2,379 118,064
71 Kiowa County, Kansas 2,475 120,539

The US has a lot of small counties, but they quickly add up. Do you know anyone living in any of those?

What about cities? According to Wikipedia this is every city with a population between 100k and 124k

# Number City Population
1 Fargo, North Dakota 124,662
2 Wilmington, North Carolina 123,744
3 Abilene, Texas 123,420
4 Odessa, Texas 123,334
5 Columbia, Missouri 123,195
6 Pearland, Texas 122,460
7 Victorville, California 122,385
8 Hartford, Connecticut 122,105
9 Vallejo, California 121,692
10 Allentown, Pennsylvania 121,442
11 Berkeley, California 121,363
12 Richardson, Texas 121,323
13 Arvada, Colorado 121,272
14 Ann Arbor, Michigan 119,980
15 Rochester, Minnesota 118,935
16 Cambridge, Massachusetts 118,927
17 Sugar Land, Texas 118,488
18 Lansing, Michigan 118,210
19 Evansville, Indiana 117,979
20 College Station, Texas 117,911
21 Fairfield, California 117,133
22 Clearwater, Florida 116,946
23 Beaumont, Texas 116,825
24 Independence, Missouri 116,672
25 Provo, Utah 116,618
26 West Jordan, Utah 116,480
27 Murrieta, California 116,223
28 Palm Bay, Florida 115,552
29 El Monte, California 115,487
30 Carlsbad, California 115,382
31 North Charleston, South Carolina 115382
32 Temecula, California 114,761
33 Clovis, California 114,584
34 Springfield, Illinois 114,230
35 Meridian, Idaho 114,161
36 Westminster, Colorado 113,166
37 Costa Mesa, California 113,003
38 High Point, North Carolina 112,791
39 Manchester, New Hampshire 112,673
40 Pueblo, Colorado 112,361
41 Lakeland, Florida 112,136
42 Pompano Beach, Florida 112,118
43 West Palm Beach, Florida 111,955
44 Antioch, California 111,502
45 Everett, Washington 111,475
46 Downey, California 111,126
47 Lowell, Massachusetts 110,997
48 Centennial, Colorado 110,937
49 Elgin, Illinois 110,849
50 Richmond, California 110,567
51 Peoria, Illinois 110,417
52 Broken Arrow, Oklahoma 110,198
53 Miami Gardens, Florida 110,001
54 Billings, Montana 109,577
55 Jurupa Valley, California 109,527
56 Sandy Springs, Georgia 109,452
57 Gresham, Oregon 109,381
58 Lewisville, Texas 109,212
59 Hillsboro, Oregon 109,128
60 Ventura[ab], California 109,106
61 Greeley, Colorado 108,649
62 Inglewood, California 108,151
63 Waterbury, Connecticut 107,568
64 League City, Texas 107,536
65 Santa Maria, California 107,263
66 Tyler, Texas 106,985
67 Davie[ac], Florida 106,306
68 Lakewood[ad], New Jersey 106,300
69 Daly City, California 106,280
70 Boulder, Colorado 105,673
71 Allen, Texas 105,623
72 West Covina, California 105,101
73 Sparks, Nevada 105,006
74 Wichita Falls, Texas 104,683
75 Green Bay, Wisconsin 104,578
76 San Mateo, California 104,430
77 Norwalk, California 103,949
78 Rialto, California 103,526
79 Las Cruces, New Mexico 103,432
80 Chico, California 103,301
81 El Cajon, California 102,708
82 Burbank, California 102,511
83 South Bend, Indiana 102,026
84 Renton, Washington 101,751
85 Vista, California 101,638
86 Davenport, Iowa 101,590
87 Edinburg, Texas 101,170
88 Tuscaloosa, Alabama 101,129
89 Carmel, Indiana 101,068
90 Spokane Valley, Washington 101,060
91 San Angelo, Texas 101,004
92 Vacaville, California 100,670
93 Clinton[ae], Michigan 100,471
94 Bend, Oregon 100,421
95 Woodbridge[ad], New Jersey 100,145

The next thing I've been seeing a lot is the claim that COVID19 will be the leading cause of death in the US by the end of the year. Unfortunately it's proved difficult to find accurate country-level numbers for causes of death. I've decided to rely on the data from here: https://ourworldindata.org/grapher/annual-number-of-deaths-by-cause?tab=table it's 2017 data, so it will not match the real data for 2020 perfectly.

To show it on a daily basis, I've divided the number by 366 (remember that 2020 is a leap year?) and multiply that by the day of year. This gives us a perfectly flat line. It's important to note that this method does not show any seasonal variation. Flu, for example, is heavily influenced by the season but this will flatten it out completely.

Let's compare to the top 16 causes of death:# Type Count
1 Cardiovascular diseases (deaths) 902,270
2 Cancers (deaths) 699,394
3 Dementia (deaths) 258,587
4 Respiratory diseases (deaths) 196,983
5 Digestive diseases (deaths) 114,419
6 Lower respiratory infections (deaths) 93,792
7 Kidney disease (deaths) 84,944
8 Diabetes (deaths) 68,558
9 Drug use disorders (deaths) 67,629
10 Liver diseases (deaths) 62,493
11 Suicide (deaths) 48,800
12 Road injuries (deaths) 44,214
13 Parkinson disease (deaths) 29,577
14 Homicide (deaths) 19,880
15 Alcohol use disorders (deaths) 13,969
16 Neonatal disorders (deaths) 11,437

Overall we can see that cardiovascular and cancers are still the number 1 killer, but let's take a look at the day over day graphs.

Overall it's unlikely that COVID19 will surpass cardiovascular deaths. They're just too popular. The established brand won't be shaken by this upstart.

Cancer deaths overall are still ahead of Covid deaths, however this is the total of all cancer deaths. I suspect if were to look at each type of cancer individually, Covid would pull ahead.

On a yearly basis, Dementia has twice the number of deaths Covid has at this point, but we're halfway through the year now, and the rate is going up again. I suspect the right graph will look very different in a few months.

Covid is blowing the other respiratory diseases out of the water. We passed the daily deaths back in April, and now we're on track to be more than twice the yearly deaths.

Number 5 on the list is Digestive diseases. We've passed the yearly total for that bucket. and it's only going to get worse.

All coronavirus related data is sourced from JHU: https://github.com/CSSEGISandData/COVID-19
I have a nightly process that pulls the time series tables and performs a number of transformations to make it a usable data source.

County populations are pulled from: https://www.census.gov/data/tables/time-series/demo/popest/2010s-counties-total.html

Causes of death numbers are pulled from: https://ourworldindata.org/grapher/annual-number-of-deaths-by-cause?tab=table

I am not manipulating the data or changing any values in any way, however I suspect there are many cases where data is being under reported from official sources.

Second wave analysis: http://coronavirus.pm2analytics.com/ibmcognos/bi/?perspective=dashboard&objRef=i00C8472A097943CA850E85A78CE6390E
Region dashboard can viewed at http://coronavirus.pm2analytics.com/ibmcognos/bi/?perspective=dashboard&objRef=i51C0486AD2E24D418DF4DFE23162937F
Another dashboard I wrote: http://coronavirus.pm2analytics.com
Mobile ready County report: http://covid19.pm2analytics.com/

EDIT: Apparently the new imgur style screwed up with my carefully arranged tabbed tables. I promise, it looks perfect in edit mode!