A History of Plagues

As COVID-19 continues to spread, fears and extraordinary predictions have also gone viral. While facing a new infectious threat, the unknowns of how new traits of our societies worldwide or of this novel coronavirus impact its spread. Though no two pandemics are equivalent, I thought it best to face this new threat armed with knowledge from past infectious episodes. The best inoculation against a plague of panic is to use evidence gained through billions of deaths, thousands of years, and a few vital breakthroughs to prepare our knowledge of today’s biological crises, social prognosis, and choices.

Below, I address three key questions: First, what precedents do we have for infections with catastrophic potential across societies? Second, what are the greatest killers and how do pandemics compare? Lastly, what are our greatest accomplishments in fighting infectious diseases?

As foundation for understanding how threats like COVID-19 come about and how their hosts fight back, I recommend reading The Red Queen concerning the evolutionary impact and mechanisms of host-disease competition and listening to Sam Harris’ “The Plague Years” podcast with Matt McCarthy from August 2019, which predated COVID-19 but had a strangely prophetic discussion of in-hospital strategies to mitigate drug resistance and their direct relation to evolutionary competition.

  • The Biggest Killers:

Infectious diseases plagued humanity throughout prehistory and history, with a dramatic decrease in the number of infectious disease deaths coming in the past 200 years. In 1900, the leading killers of people were (1) Influenza, (2) Tuberculosis, and (3) Intestinal diseases, whereas now we die from (1) Heart disease, (2) Cancer, and (3) Stroke, all chronic conditions. This graph shows not that humans have vanquished infectious disease as a threat, but that in the never-ending war of evolutionary one-upmanship, we have won battles consistently since 1920 forward. When paired with Jonathan Haidt’s Most Important Graph in the World, this vindicates humanity’s methods of scientific and economic progress toward human flourishing.Death rates

However, if the CDC had earlier data, it would show a huge range of diseases that dwarf wars and famines and dictators as causes of death in the premodern world. If we look to the history of plagues, we are really looking at the history of humanity’s greatest killers.

The sources on the history of pandemics are astonishingly sparse/non-comprehensive. I created the following graphs only by combining evidence and estimates from the WHO, CDC, Wikipedia, Our World in Data, VisualCapitalist, and others (lowest estimates shown where ranges were presented) for both major historic pandemics and for ongoing communicable disease threats. This is not a complete dataset, and I will continue to add to it, but it shows representative death counts from across major infectious disease episodes, as well as the death rate per year based on world population estimates. See the end of this post for the full underlying data. First, the top 12 “plagues” in history:

Capture disease top 12

 

Note: blue=min, orange=max across the sources I examined. For ongoing diseases with year-by-year WHO evidence, like tuberculosis, measles, and cholera, I grouped mortality in 5-year spans (except AIDS, which does not have good estimates from the 1980s-90s, so I reported based on total estimated deaths).

Now, let’s look at the plagues that were lowest on my list (number 55-66). Again, my list was not comprehensive, but this should provide context for COVID-19:

Capture covid

As we can see, the 11,400 people who have died from COVID-19 recently passed Ebola to take the 61st (out of 66) place on our list of plagues. Note again that several ongoing diseases were recorded in 5-year increments, and COVID-19 still comes in under the death rates for cholera. Even more notably, it has 0.015% as many victims as the plague in the 14th Century,

  • In Context of Current Infectious Diseases:

For recent/ongoing diseases, it is easier to compare year-by-year data. Adding UNAIDS to our sources, we found the following rates of death across some of the leading infectious causes of death. Again, this is not comprehensive, but helps put COVID-19 (the small red dot, so far in the first 3 months of 2020) in context:

Capture diseases by year

Note: darker segments of lines are my own estimates; full data at bottom of the post. I did not include influenza due to the lack of good sources on a year-by-year basis, but a Lancet article found that 291,000-645,000 deaths from influenza in a year is predictable based on data from 1999-2015.

None of this is to say that COVID-19 is not a major threat to human health globally–it is, and precautions could save lives. However, it should show us that there are major threats to human health globally all the time, that we must continue to fight. These trendlines tend to be going the right direction, but our war for survival has many foes, and will have more emerge in the future, and we should expend our resources in fighting them rationally based on the benefits to human health, not panic or headlines.

  • The Eradication List:

As we think about the way to address COVID-19, we should keep in mind that this fight against infectious disease builds upon work so amazing that most internet junkies approach new infectious diseases with fear of the unknown, rather than tired acceptance that most humans succumb to them. That is a recent innovation in the human experience, and the strategies used to fight other diseases can inform our work now to reduce human suffering.

While influenzas may be impossible to eradicate (in part due to an evolved strategy of constantly changing antigens), I wanted to direct everyone to an ever-growing monument to human achievement, the Eradication List. While humans have eradicated only a few infectious diseases, the amazing thing is that we can discuss which diseases may in fact disappear as threats through the work of scientists.

On that happy note, I leave you here. More History of Plagues to come, in Volume 2: Vectors, Vaccines, and Virulence!

Disease Start Year End Year Death Toll (low) Death Toll (high) Deaths per 100,000 people per year (global)
Antonine Plague 165 180 5,000,000 5,000,000 164.5
Plague of Justinian 541 542 25,000,000 100,000,000 6,250.0
Japanese Smallpox Epidemic 735 737 1,000,000 1,000,000 158.7
Bubonic Plague 1347 1351 75,000,000 200,000,000 4,166.7
Smallpox (Central and South America) 1520 1591 56,000,000 56,000,000 172.8
Cocoliztli (Mexico) 1545 1545 12,000,000 15,000,000 2,666.7
Cocoliztli resurgence (Mexico) 1576 1576 2,000,000 2,000,000 444.4
17th Century Plagues 1600 1699 3,000,000 3,000,000 6.0
18th Century Plagues 1700 1799 600,000 600,000 1.0
New World Measles 1700 1799 2,000,000 2,000,000 3.3
Smallpox (North America) 1763 1782 400,000 500,000 2.6
Cholera Pandemic (India, 1817-60) 1817 1860 15,000,000 15,000,000 34.1
Cholera Pandemic (International, 1824-37) 1824 1837 305,000 305,000 2.2
Great Plains Smallpox 1837 1837 17,200 17,200 1.7
Cholera Pandemic (International, 1846-60) 1846 1860 1,488,000 1,488,000 8.3
Hawaiian Plagues 1848 1849 40,000 40,000 1.7
Yellow Fever 1850 1899 100,000 150,000 0.2
The Third Plague (Bubonic) 1855 1855 12,000,000 12,000,000 1,000.0
Cholera Pandemic (International, 1863-75) 1863 1875 170,000 170,000 1.1
Indian Smallpox 1868 1907 4,700,000 4,700,000 9.8
Franco-Prussian Smallpox 1870 1875 500,000 500,000 6.9
Cholera Pandemic (International, 1881-96) 1881 1896 846,000 846,000 4.4
Russian Flu 1889 1890 1,000,000 1,000,000 41.7
Cholera Pandemic (India and Russia) 1899 1923 1,300,000 1,300,000 3.3
Cholera Pandemic (Philippenes) 1902 1904 200,000 200,000 4.2
Spanish Flu 1918 1919 40,000,000 100,000,000 1,250.0
Cholera (International, 1950-54) 1950 1954 316,201 316,201 2.4
Cholera (International, 1955-59) 1955 1959 186,055 186,055 1.3
Asian Flu 1957 1958 1,100,000 1,100,000 19.1
Cholera (International, 1960-64) 1960 1964 110,449 110,449 0.7
Cholera (International, 1965-69) 1965 1969 22,244 22,244 0.1
Hong Kong Flu 1968 1970 1,000,000 1,000,000 9.4
Cholera (International, 1970-75) 1970 1974 62,053 62,053 0.3
Cholera (International, 1975-79) 1975 1979 20,038 20,038 0.1
Cholera (International, 1980-84) 1980 1984 12,714 12,714 0.1
AIDS 1981 2020 25,000,000 35,000,000 13.8
Measles (International, 1985) 1985 1989 4,800,000 4,800,000 19.7
Cholera (International, 1985-89) 1985 1989 15,655 15,655 0.1
Measles (International, 1990-94) 1990 1994 2,900,000 2,900,000 10.9
Cholera (International, 1990-94) 1990 1994 47,829 47,829 0.2
Malaria (International, 1990-94) 1990 1994 3,549,921 3,549,921 13.3
Measles (International, 1995-99) 1995 1999 2,400,000 2,400,000 8.4
Cholera (International, 1995-99) 1995 1999 37,887 37,887 0.1
Malaria (International, 1995-99) 1995 1999 3,987,145 3,987,145 13.9
Measles (International, 2000-04) 2000 2004 2,300,000 2,300,000 7.5
Malaria (International, 2000-04) 2000 2004 4,516,664 4,516,664 14.7
Tuberculosis (International, 2000-04) 2000 2004 7,890,000 8,890,000 25.7
Cholera (International, 2000-04) 2000 2004 16,969 16,969 0.1
SARS 2002 2003 770 770 0.0
Measles (International, 2005-09) 2005 2009 1,300,000 1,300,000 4.0
Malaria (International, 2005-09) 2005 2009 4,438,106 4,438,106 13.6
Tuberculosis (International, 2005-09) 2005 2009 7,210,000 8,010,000 22.0
Cholera (International, 2005-09) 2005 2009 22,694 22,694 0.1
Swine Flu 2009 2010 200,000 500,000 1.5
Measles (International, 2010-14) 2010 2014 700,000 700,000 2.0
Malaria (International, 2010-14) 2010 2014 3,674,781 3,674,781 10.6
Tuberculosis (International, 2010-14) 2010 2014 6,480,000 7,250,000 18.6
Cholera (International, 2010-14) 2010 2014 22,691 22,691 0.1
MERS 2012 2020 850 850 0.0
Ebola 2014 2016 11,300 11,300 0.1
Malaria (International, 2015-17) 2015 2017 1,907,872 1,907,872 8.6
Tuberculosis (International, 2015-18) 2015 2018 4,800,000 5,440,000 16.3
Cholera (International, 2015-16) 2015 2016 3,724 3,724 0.0
Measles (International, 2019) 2019 2019 140,000 140,000 1.8
COVID-19 2019 2020 11,400 11,400 0.1

 

Year Malaria Cholera Measles Tuberculosis Meningitis HIV/AIDS COVID-19
1990 672,518 2,487 670,000 1,903 310,000
1991 692,990 19,302 550,000 1,777 360,000
1992 711,535 8,214 700,000 2,482 440,000
1993 729,735 6,761 540,000 1,986 540,000
1994 743,143 10,750 540,000 3,335 620,000
1995 761,617 5,045 400,000 4,787 720,000
1996 777,012 6,418 510,000 3,325 870,000
1997 797,091 6,371 420,000 5,254 1,060,000
1998 816,733 10,832 560,000 4,929 1,210,000
1999 834,692 9,221 550,000 2,705 1,390,000
2000 851,785 5,269 555,000 1,700,000 4,298 1,540,000
2001 885,057 2,897 550,000 1,680,000 6,398 1,680,000
2002 911,230 4,564 415,000 1,710,000 6,122 1,820,000
2003 934,048 1,894 490,000 1,670,000 7,441 1,965,000
2004 934,544 2,345 370,000 1,610,000 6,428 2,003,000
2005 927,109 2,272 375,000 1,590,000 6,671 2,000,000
2006 909,899 6,300 240,000 1,550,000 4,720 1,880,000
2007 895,528 4,033 170,000 1,520,000 7,028 1,740,000
2008 874,087 5,143 180,000 1,480,000 4,363 1,630,000
2009 831,483 4,946 190,000 1,450,000 3,187 1,530,000
2010 788,442 7,543 170,000 1,420,000 2,198 1,460,000
2011 755,544 7,781 200,000 1,400,000 3,726 1,400,000
2012 725,676 3,034 150,000 1,370,000 3,926 1,340,000
2013 710,114 2,102 160,000 1,350,000 3,453 1,290,000
2014 695,005 2,231 120,000 1,340,000 2,992 1,240,000
2015 662,164 1,304 150,000 1,310,000 1,190,000
2016 625,883 2,420 90,000 1,290,000 1,170,000
2017 619,825 100,000 1,270,000 1,150,000
2018 1,240,000
2019
2020 16,514

Broken Incentives in Medical Innovation

I recently listened to Mark Zuckerberg interviewing Tyler Cowen and Patrick Collison concerning their thesis that the process of using scientific research to advance major development goals (e.g. extending the average human lifespan) has stagnated. It is a fascinating discussion that fundamentally questions the practice of scientific research as it is currently completed.

Their conversation also made me consider more deeply the incentives in my industry, medical R&D, that have shaped the practices that Cowen and Collison find so problematic. While there are many reasons for the difficulties in maintaining a breakneck pace of technological progress (“all the easy ideas are already done,” “the American education system fails badly on STEM,” etc), I think that there are structural causes that are major contributors to the great slowdown in medical progress. See my full discussion here!

The open secrets of what medicine actually helps

One of the things that I was most surprised by when I joined the medical field was how variable the average patient benefit was for different therapies. Obviously, Alzheimer’s treatments are less helpful than syphilis ones, but even within treatment categories, there are huge ranges in actual efficacy for treatments with similar cost, materials, and public conception.

What worries me about this is that not only in public but within the medical establishment, actually differentiating these therapies–and therefore deciding what therapies, ultimately, to use and pay for–is not prioritized in medical practice.

I wrote about this on my company’s blog, but its concept is purely as a comment on the most surprising dichotomy I learned about–that between stenting (no benefit shown for most patients!!) vs. clot retrieval during strokes (amazing benefits, including double the odds of good neurological outcome). Amazingly, the former is a far more common procedure, and the latter is underprovided in rural areas and in most countries outside of the US, EU, Japan, and Korea. Read more here: https://about.nested-knowledge.com/2020/01/27/not-all-minimally-invasive-procedures-are-created-equal/.

There is no Bloomberg for medicine

When I began working in medical research, I was shocked to find that no one in the medical industry has actually collected and compared all of the clinical outcomes data that has been published. With Big Data in Healthcare as such a major initiative, it was incomprehensible to me that the highest-value data–the data that is directly used to clear therapies, recommend them to the medical community, and assess their efficacy–were being managed in the following way:

  1. Physician completes study, and then spends up to a year writing it up and submitting it,
  2. Journal sits on the study for months, then publishes (in some cases), but without ensuring that it matches similar studies in the data it reports.
  3. Oh, by the way, the journal does not make the data available in a structured format!
  4. Then, if you want to see how that one study compares to related studies, you have to either find a recent, comprehensive, on-point meta-analysis (which is a very low chance in my experience), or comb the literature and extract the data by hand.
  5. That’s it.

This strikes me as mismanagement of data that are relevant to lifechanging healthcare decisions. Effectively, no one in the medical field has anything like what the financial industry has had for decades–the Bloomberg terminal, which presents comprehensive information on an updatable basis by pulling data from centralized repositories. If we can do it for stocks, we can do it for medical studies, and in fact that is what I am trying to do. I recently wrote an article on the topic for the Minneapolis-St Paul Business Journal, calling for the medical community to support a centralized, constantly-updated, data-centric platform to enable not only physicians but also insurers, policymakers, and even patients examine the actual scientific consensus, and the data that support it, in a single interface.

Read the full article at https://www.bizjournals.com/twincities/news/2019/12/27/there-is-no-bloomberg-for-medicine.html!

Changing the way doctors see data

Over the past four years, my brother and I have grown a business that helps doctors publish data-driven articles from the two of us to over 30 experienced researchers. However, along the way, we noticed that data management in medical publication was decades behind other fields–in fact, the vital clinical outcomes from major trials are generally published as singular PDFs with no structured data, and are analyzed in comparison to existing studies only in nonsystematic, nonupdatable publications. Effectively, medicine has no central method for sharing or comparing patient outcomes across therapies, and I think that it is our responsibility as researchers to present these data to the medical community.

Based on our internal estimates, there are >3 million published clinical outcomes studies (with over 200 million individual datapoints) that need to be abstracted, structured, and compared through a central database. We recognized that this is a monumental task, and we therefore have focused on automating and scaling research processes that have been, through today, entirely manual. Only after a year of intensive work have we found a path toward creating a central database for all published patient outcomes, and we are excited to debut our technology publicly!

Keith recently presented our venture at a Mayo Clinic-hosted event, Walleye Tank (a Shark Tank-style competition of medical ventures), and I think that it is an excellent fast-paced introduction to a complex issue. Thanks also to the Mayo Clinic researchers for their interesting questions! You can see his two-minute presentation and the Q&A here. We would love to get more questions from the economic/data science/medical communities, and will continue putting our ideas out there for feedback!

My Startup Experience

Over the past 4 years, I have had a huge transition in my life–from history student to law student to serial medical entrepreneur. Essentially, I have learned a great deal from my academic work that taught me the value that we can create if we find an unmet need in the world, create an idea that fills that need, and then use technology, personal networks, and hard work to create novelties. While startups obviously tackle any new problem under the sun, to me, they are the mechanism to bring about a positive change–and, along the way, get the resources to scale that change across the globe.

I am still very far from reaching that goal, but my family and cofounders have several visions of how to improve not only how patients are treated but also how we build the knowledge base that physicians, patients, and researchers can use to inform care and innovation. My brother/cofounder and I were recently on an entrepreneurship-focused podcast, and we got the chance to discuss our experience, our vision, and our companies. I hope this can be a springboard for more discussions about how companies are a unique agent of advancing human flourishing, and about the history and philosophy of entrepreneurship, technology, and knowledge.

You can listen here: http://rochesterrising.org/podcast/episode-151-talking-medical-startups-with-keith-and-kevin-kallmes. Heartfelt thanks to Amanda Leightner and Rochester Rising for a great conversation!

Thank you!

Kevin Kallmes

The Myth of the Nazi War Machine

Nazism and fascism, in the popular imagination, are associated with evil, immoral, inhumane treatment across conquered groups and their own subjects alike. These evil actions loom even larger because the thought of an entire society dedicated to military industry, extending its reach across and beyond Europe, inspires ghastly fears not only of evil intent but also astonishing military might that could overwhelm the Allies with the technological wonder of the V2 rocket, the deadly and ever-present U-boat threat, and the German “Royal Tiger” tank that was so well armored that Sherman-fired shells literally bounced off of it. This vision of the Nazis as conquering through technological and industrial superiority is not just a mistake of modern historians, but is actually based on the overestimation of their foes by the Allies and on the disastrously misplaced overconfident messaging of the Germans, Italians, and Japanese that their technology, industrial power, and elan gave them even a chance of victory. The miscalculation of the Hitler in extrapolating his successes in Poland and France to assuming his alliance could overwhelm the combined defenses of over 1.5 billion people represents the most astonishing delusion in military history.

The inspiration for this comes from Victor Davis Hanson’s fascinating economic and industrial history, The Second World Wars. One of his major arguments is that the Axis leaders lost because their commitment to their ideology became a fantasy that they had abilities that directly contradicted the reality of their actual abilities and those of their opponents. I heartily recommend the book and this shorter interview where he lays out the book’s central concepts. My major takeaway was that this fantasy has gone beyond the minds of Hitler, Tojo, and Mussolini, and the vision of a vast industrial empire looming over the world is now imprinted on our memory of World War II. I think it is past time that we recognize Nazism as not only immoral but also incompetent. Below, I hope to share some astonishing statistics that show beyond a shadow of a doubt that the modern concept of Nazi military might is a myth.

  1. The Allies rode in cars, the Germans rode horses. In 1939, the only transportation available to 85% of German infantry other than walking was horses. By 1945…it was still 85%. In total, the US and UK produced almost 4 million general-use vehicles, compared to 160,000 German vehicles. That is a 25-fold advantage. The Allies also had 1 million infantry-supporting artillery compared to less than 100,000 for all of the Axis.
  2. Where were the supplies? The Allies had 46 million tonnes of merchant shipping vessels to the Axis’ 5 million, five times as much aluminum (key for engines and planes), and by 1943 had cut off all German access to rare metals such as tungsten, one of the key metals used in munitions, manufacturing, and electronics. The US supplied Britain and the USSR through the Lend-Lease Act with almost $700 billion (inflation-adjusted 2019 dollars) in supplies throughout the war, which is roughly double the entire German annual GDP in 1939.
  3. The Allies swam to victory on a sea of oil. Though Rommel came within a battle of accessing the British Middle-Eastern oil fields, the Axis still had astonishingly little fuel (which they needed to power their King Tiger, which drank a gallon of gas every 700 yards, the vast Luftwaffe that put over 130,000 planes into action, and their gigantic battleship Bismark). The Axis as a whole used 66 million metric tonnes of oil, while the Allies used a billion. A 15X advantage.
  4. The panzers were neither numerous nor superior technologically. The Mark 1 and 2 panzers that conquered France were actually less numerous and less technologically advanced than France’s. While blitzkrieg and elan overwhelmed the French, even the Mark 4–the most commonly used panzer in the late war–underperformed Shermans in infantry support and reliability and were even considered inferior to the Soviet T34 by Hitler himself. Even including the outmoded Czech tanks repurposed by the Germans, they fielded only 67,000 tanks on all fronts to face 270,000 Allied tanks (with no help from Italy, with a pitiful 3,300 tanks, and Japan largely ignored mobile land armor and created only 4,500 tanks). The environment of idealogical zeal in Germany prevented a military researcher from telling Hitler about the true tank numbers of the Soviets, as Hitler himself recognized later in the war by repeating that if he had known the true number of T34’s he faced, he would never have invaded. The US and USSR deployed massive numbers of upgraded Shermans and the workhorse T34s, while Germany sank huge investments into specialized and scary duds the Royal Tiger–300,000 man-hours and ten times as much as a Sherman. Only 1,300 Royal Tigers were ever produced, and their 70 tonnes of weight, constant mechanical issues, and cost undercut their supremacy in tank-on-tank duels. The US and Britain used precision bombing to inflict major tank losses on Germany, and while German tanks outfought Soviet tanks roughly 4:1, by 1945 the Soviets still had 25,000 tanks against the Germans’ 6,000.
  5. Collaboration helps both tech and strategy. The Allies worked together–the Sherman’s underpowered 75mm (corrected) could be upgraded with a British gun because of interoperability of parts, and the US and Brits delivered over 12,000 tanks and 18,000 planes to the Soviets under Lend-Lease; the Germans did not even have replaceable parts for their own tanks, and the Germans never helped their Italian allies (who had lost a land invasion even to the collapsing French) develop industrial capabilities. Bletchley Park gave advance warning to US merchant convoys, but the Italians and Japanese found out that Hitler had invaded the USSR only after troops had crossed into Ukraine.
  6. Fascism is not industrially sound. Even though the Nazis put an astonishing 75% of their GDP toward the military by 1944 and despite taking on unsustainable debt to sustain their production, their GDP in 1939 was $384 billion, roughly equal to the Soviets and $100 billion less than the UK and France combined. By the end of the war, this fell to $310 billion, compared to a whopping $1.4 trillion US GDP. However, even these numbers do not fully represent how non-mechanized, non-scalable, and non-industrial Germany was even under military dictatorship. While German science and engineering had been pre-eminent pre-WW I, the central control and obsession with infeasible, custom projects before and during the war meant that the Germans had a lower percentage of their population that could be mobilized for wartime production than their opponents, not to mention that their GDP per capita was half of that of the US, and yet the Axis still took on opponents that had productive populations five times their size.
  7. The V2 was a terrible investment. After losing the Battle of Britain (largely because of inferior training, radar, and plane production), the Nazis tried to use ballistic missiles to bomb the Brits into submission. The less technologically sophisticated V1 delivered a respectable 1,000 kg of explosives, but despite launching over 10,000, by mid-1944 the British countermeasures stopped 80% of these, and many misfired, failed to explode, or had guidance system malfunctions. The V2 was more sophisticated, but was never mass produced: only 3,000 were launched, and more Nazis were killed as part of the development of the rocket than Brits by their launch. The V1 and V2 programs combined cost 50% more than the Manhattan project, and even compared to the US’s most expensive bombing program (developing the B29), the cost-per-explosives-delivered was thirty times higher for the V2.
  8. The Luftwaffe was completely overmatched even by the RAF alone. Before the Battle of Britain, the Luftwaffe (2,500 planes) outnumbered the RAF (about 1,500), and the RAF was using more outdated Hurricanes than they were the newer Spitfire; however, the Brits scaled up training and production and even put novel innovations into their manufacturing within the 3 months of battle.
  9. The Germans underestimated the scalability of their opponent’s production. By the end of the war, the Brits manufactured 177,000 planes, 44,000 more than Germany. Crucially, though they started the war with far fewer experienced pilots, the Brits used this production advantage to train their pilots far better (in fact, the Brits had over 40,000 training aircraft). The US was similarly underprepared in terms of both aircraft production and training, but within a year had increased production from one B-24 every two weeks in 1940 to one every two hours in 1942. The US manufactured almost 300,000 planes by the end of the war, with far superior bombers (the figher-resistant B-17 and the giant, sophisticated Super Fortress B-29). However, the German air force personnel still needed to be more numerous than either the US or Britain because of the lack of mechanization.
  10. The Germans could not replace their pilots. By early 1945, the Germans were losing 30% of their pilots every month, even after giving up on bombing campaigns because of high pilot and plane attrition. They never scaled training and were sending completely green pilots against well-trained Allied opponents who had numerical, technological, and experience superiority by 1943 and air supremacy by 1944.
  11. The Germans did not deploy new air technologies to their advantage. While the jet engine and V2 rockets would revolutionize air power after the war, they did not impact the outcome of the war except to drain German R&D. Germany also failed to develop a functional heavy bomber, did not update their fighters’ technology during the war, never fully or effectively deployed radar, and never matched the Allies’ anti-aircraft defenses.
  12. The Allies could win through strategic bombing, but the reverse was not true. Both sides targeted industry and killed civilians en masse in strategic campaigns, but Germany never had the ability to strategically reduce their enemies’ production. Though Germany dropped 760,000 tonnes of ordnance on the Soviets and systematically destroyed production west of the Urals, the Soviets moved their industry to the East and continued outproducing their opponents with respect to tanks, vehicles, artillery, machine guns, and munitions. The Germans never produced a functional 4-engine bomber, so they could not use strategic bombing to undercut industry beyond this; the Blitz killed 40,000 civilians and destroyed over a million homes, but never developed into a threat against British military production. This also cost the Luftwaffe over 2,200 planes and 3,500 of their best pilots. However, nearly every major German and Japanese city was reduced by an unbelievable 3.5 million tonnes of ordnance dropped by the Allies, which killed over 700,000 German and Japanese civilians and destroyed the majority of both empires’ military production.
  13. The U-boat campaign became a colossal failure by 1943. Though the unrestricted submarine warfare of 1940-41 was sinking enough merchant vessels to truly threaten British supplies, Allied countermeasures–code-cracking, sonar, depth charges, Hedgehogs, Squids, and the use of surface aircraft to screen fleets–systematically destroyed the U-boats, which had losses of over 80% by the end of the war. In fact, the Germans barely managed to exceed the total merchant losses inflicted in World War I, and in May-June 1943 only sank two ships for every U-boat lost, ending the Battle of the Atlantic in just two disastrous months. The US was producing ships and supplies so quickly and in such vast quantities that the U-boats needed to sink 700,000 tonnes of shipping every month just to keep up with this production, which they did in only one month (November 1942); this number sank to less than a tenth of that by early 1943.
  14. The US actually waged a successful submarine campaign. Unlike the Germans, the US completely neutered the Japanese merchant fleet using submarines, which also inflicted over 55% of total Japanese fleet losses during the war, with minimal losses of submarine crews. Using just 235 submarines, the US sank 1,000 ships, compared to roughly 2,000 sunk by Germany (which cost almost 800 U-boat losses).
  15. Naval war had changed, and only the US responded. After the sinking of the HMS Prince of Wales near Singapore, all nations should have recognized that naval air forces were the new way to rule the waves. And yet, the Germans only ever built a single aircraft carrier despite their need to support operations in North Africa, and built the Tirpitz, a gigantic Bismarck-class battleship (that cost as much as 20 submarines), which barely participated in any offensive action before being destroyed by successive air raids. Germany never assembled a fleet capable of actually invading Britain, so even if they had won the Battle of Britain, there were no serious plans to actually conquer the island. Japan recognized the importance of aircraft carriers, and built 18, but the US vastly overmatched them with at least 100 (many of them more efficient light carriers), and Japan failed to predict how naval air supremacy would effectively cut them off from their empire and enable systematic destruction of their homeland without a single US landing on Japanese home soil.
  16. The Nazis forgot blitzkrieg. The rapid advances of Germany in 1939 is largely attributable to the decentralized command structure that enabled leaders on the front to respond flexibly based on mission-driven instructions rather than bureaucracy. However, as early as Dunkirk (when Hitler himself held back his tank forces out of fear), the command structure had already shifted toward top-down bureaucracy that drummed out gifted commanders and made disastrous blunders through plodding focuses on besieging Sevastopol and Stalingrad rather than chasing the reeling Soviets. Later, the inflexibility of defenses and “no-retreat” commands that allowed encirclement of key German forces replayed in reverse the inflexibility of the Maginot line and Stalin’s early mistakes, showing that the fascist system prevented learning from one’s enemy and even robbed the Germans of their own institutional advantages over the course of the war.
  17. Even the elan was illusory. Both Germany and Japan knew they were numerically inferior and depended on military tradition and zeal to overcome this. While German armies generally went 1:1 or better (especially in 1941 against the Soviets, when they killed or captured 4 million badly-led, outdated Soviet infantry), even the US–fighting across an ocean, with green infantry and on the offensive against the dug-in Germans–matched the Germans in commitment to war and inflicted casualties at 1:1. At the darkest hour, alone against the entire continent and while losing their important Pacific bases one by one, the Brits threw themselves into saving themselves and the world from fascists; only secret police and brute force kept the Nazis afloat once the tide had turned. The German high command was neutered by the need for secrecy and the systematic replacement of talented generals with loyal idiots, and the many mutinies, surrenders, and assassination attempts by Nazi leaders show that the illusory unity of fascism was in fact weaker under pressure than the commitment and cooperation of democratic systems.
  18. The Nazis never actually had plans that could win an existential war. Blitzkrieg scored some successes against the underprepared Poles and demoralized French, but these major regional victories were fundamentally of a different character than the conflicts the Nazis proceeded to start. While the Germans did take over a million square miles from the Soviets while destroying a 4-million-strong army, the industry was eventually transferred beyond the Urals and the Soviets replenished their army with, over 4 years, a further 30 million men. But most of all, even if Hitler somehow achieved what Napoleon himself could not, neither he nor Tojo had any ability to attack Detroit, so an implacable, distant foe was able to rain down destruction without ever facing a threat on home soil. The Nazis simply did not have the technology, money, or even the plans to conquer their most industrially powerful opponent, and perhaps the greatest tragedy of the entire war is that 60 million people died to prove something that was obvious from the start.

Overall, the Nazis failed to recognize how air and naval air superiority would impact the war effort, still believed that infantry zeal could overcome technological superiority, could not keep pace with the scale of the Allies’ industry or speed of their technological advances, spent inefficiently on R&D duds, never solved crucial resource issues, and sacrificed millions of their own subjects in no-retreat disasters. Fooled by their early success, delusions of grandeur, and belief in their own propaganda, Hitler and his collaborators not only instituted a morally repugnant regime but destroyed themselves. Fascism a scary ideology that promises great power for great personal sacrifice, but while the sacrifice was real, the power was illusory: as a system, it actually underperformed democracy technologically, strategically, industrially, and militarily in nearly every important category. Hopefully, this diametrical failure is evidence enough for even those who are morally open to fascism to discard it as simply unworkable. And maybe, if we dispel the myth of Nazi industry, we can head off any future experiments in fascism and give due recognition to the awe-inspiring productivity of systems that recognize the value of liberty.

This is in no way exhaustive, and in the interest of space I have not included the analogous Italian and Japanese military delusions and industrial shortcomings in World War II. I hope that this shortlist of facts inspires you to learn more and tell posterity that fascism is not only evil but delusional and incompetent.

All facts taken from The Second World Wars, Wikipedia, or general internet trawling.