What was the deadliest natural catastrophe?
Author: Joao FabianoContenders
Black Death
The Plague of Justinian and the First Plague Pandemic
Spanish Flu
Pre-historical population bottlenecks
Conclusion
References
Intro
Knowing what kind of catastrophes humanity has suffered in the past may provide us
with some insight into how likely we are to experience them in the future. Unfortunately,
existing work on the frequency and severity of past catastrophes is scattered acrossmultiple sources which vary in reliability. In this document, I review the existing evidence
on how many people were killed by three past historical events–the Black Death, thePlague of Justinian, and the Spanish Flu–as well as two, unknown pre-historic events. I
compare these figures to estimates of global population to suggest which event killed
the largest proportion of humanity at the time.
Contenders
In order to arrive at a preliminary list of contenders, I used Wikipedia’s List of natural
disasters by death toll (Wikipedia, 2022). From each sub-list, I collected natural events
that were listed as having caused more than one million deaths. Since I’m interested infinding the event that killed the largest proportion of the population at the time, I divided
the highest estimate of the death toll for each event by world population at the time.
Population data came from Our World in Data (Our World in Data, 2022). The ten
deadliest events by this measure are listed in the table below.
Event

Years

% world killed(Wikipedia’s highest)% world killed(best estimate)Black Death

1346-1353

44%

10%

Plague of Justinian541-54224%

0.6-4.4%

Spanish Flu

1918-1920

10%

Great European Famine

1315-1317

1.9%

Chinese famine

1906-1907

1.45%

Chalisa famine

1783-1784

1.35%

Antioch earthquake

526

0.4%

China floods

1931

0.2%

Shaanxi earthquake

1556

0.18%

Yellow River flood

1887

0.12%

0.9%

In the rest of this post, I focus on just the top 3 disasters from table X. Only those threeaffected the entire world, or a large region of it. I have found that Wikipedia estimates ofthe death tolls tend to be too high, rather than too low, so I’ll use the numbers above as
rough upper bounds. These tend to be almost one order of magnitude higher than thebest estimates available, as I explain below. Since the Wikipedia estimates of the death
tolls of the remaining catastrophes are significantly lower than my best estimates for thedeath tolls of the top three, it seems safe to exclude them from the rest of my analysis.
Black Death
Between 1346 to 1353, it’s estimated that somewhere between a quarter and two-thirdsof all Europeans died from the bubonic infection of the bacteria Yersinia pestis(Benedictow, 2021, p. 875; Byrne, 2012, p. 108; Hays, 2005, p. 43; Ziegler, 2013, p.
231). That is a wide range. Unfortunately, it is hard to be more specific. A classicalsource on the subject summarises the uncertainty: "To maintain that one European inthree died during the period of the Black Death can never be proved but, equally, cannot
be wildly far from the truth. Further than that, in the present state of knowledge, one
cannot go" (Ziegler, 2013, p. 231).1
The global death toll is even more uncertain, but something around 10% is a reasonableguess. Wikipedia’s upper bound of 44% seems nearly impossible. A third of all
Europeans was 5.5% of the world population at the time (Byrne, 2012, p. 108; Goldewijk
et al., 2017). But records are scarce for the Middle East and North Africa, and nearly
absent for Asia. One expert estimates one-third of Syria and Egypt died (Dols, 2019, pp.
1

Recent estimates tend to be on the higher end of the a quarter to two-thirds range. Benedictow’s
two-thirds attracted some controversy initially but it has come to be regarded as one of the mostwell-researched estimates, with a very minute analysis of a plethora of direct historical sources listing
death tolls.

218–223). If we assume all of the Middle East and North Africa experienced the samemortality rate, then we can add an additional 1.5% of the world population to the death
toll (Goldewijk et al., 2017).
Although we have few records of the plague in Asia (Sussman, 2011), the consensus isthat that’s where it originated. It seems likely then that Asia, which had over half of theworld population at the time, was also hit hard. For example, if China alone experienced
the Black Death and had a death rate half as bad as Europe’s, another 3% of the world
would have died (Goldewijk et al., 2017). Thus, this relatively conservative estimate
adds up to 10% of the world population. The actual toll is probably slightly higher orlower than this, of course. Luke Muehlhauser's literature review on the subject arrived at
an estimated global death rate of 5-15% (Muehlhauser, 2017).2
The Plague of Justinian and the First Plague Pandemic
Wikipedia lists three sources for its Plague of Justinian’s death tolls. Each is asecondary source and counts deaths over a period longer than the years 541-542.3 It’s
somewhat difficult to know how exactly to define a ‘catastrophe’ in this case. The
Plague of Justinian was actually just phase one of the First Plague Pandemic, whichstarted in 541, likely peaked a year later in Constantinople, and ended in 750. Although
it seems unlikely that it could rival the Black Death’s mortality rate, Wikipedia’s estimateof 24% worldwide mortality is high enough to make this plague a contender. I looked
into an unlikely, worst-case scenario by assuming that every area affected by the First
Plague Pandemic was affected equally badly. My rough estimate, detailed below,
assumes the plague had a 20% mortality rate and affected 20% of the world population,suggesting a global mortality rate of 4%. This estimate–which again, is almost certainly
too high–is still lower than Muehlhauser's lowest estimate for the Black Death’s death
rate of 5%.
The historical consensus is that the hardest-hit place during the Plague of Justinian wasConstantinople in 542 (Hays, 2005, p. 23; Rosen, 2010, p. 17; Stathakopoulos, 2008,2017). However, actual mortality figures are highly uncertain: official records were lostand most anecdotal accounts seem exaggerated. One leading expert’s best guess, after
correcting a previous erroneous model, is that there were "about 80,000 victims (or 20
percent of the population and roughly about 880 victims a day)" (Stathakopoulos, 2017,2

His low estimate assumes no deaths in Asia, which seems unlikely to me.
For instance, of the three listed sources one states: "By the time Justinian's plague had run its course in
AD 590, it had killed as many as 100 million people" (Maugh, 2002); and a second: "the Plague ofJustinian, to give both pandemic and emperor their names, killed at least twenty-five million people;
depopulated entire cities; and depressed birth rates for generations" (Rosen, 2010, p. 3). But it couldn’t
have depopulated several cities and have a generational effect just within two years as it doesn’t spreadthat fast. Rosen (2007) later states “the range of deaths during the critical three months of 542 can becalculated at anywhere from sixty thousand to two hundred thousand." (p. 210).
3

p. 140).4 He states that the plague eventually spread everywhere across Europe, North
Africa and the Middle East, though reports of its effects outside the Byzantine Empire
are even less reliable.
To estimate the total number of deaths caused by this plague, we can multiply its
estimated mortality rate by the total number of lives it affected over time in the areas it
spread. The 500 AD total population of Europe, North Africa, and the Middle East was
54 million; about 21% of the world population.5 The Population Reference Bureau’s
demographic model suggests that 26.59 billion births took place globally between theyears 1 AD and 1200 AD period (Kaneda & Haub, 2021). Population was mostly steadyin these regions (barring Western Europe, where population doubled) during this time.
Plus, most plague deaths likely occurred within the first half-century. Therefore, I will
make the simplifying assumption that 21% of these births were in the affected regions.
The pandemic lasted for about 17% of the 1-1200 AD period, so it could have affectedslightly under 1 billion lives. Still, even if we make the further unrealistic assumption thatthe plague was in full force throughout these regions, and we ignore high earlychildhood mortality, this Plague would have killed 200 million people out of the 4.5 billion
born within that period.6 That suggests a global mortality rate of 4.4%.
But, given all our assumptions, this is surely too high. If we instead use Wikipedia’s
death toll of 30-50 million we get just 0.6-1% worldwide mortality. On the whole, it
seems unlikely that the Plague of Justinian is a strong contender for the title of deadliest
natural catastrophe.
Spanish Flu
The latest expert estimate of the Spanish Flu’s death toll is that it killed 17.5 million
people between 1918 and 1919, corresponding to only 0.92% of the 1918 world
population (Spreeuwenberg et al., 2018). The highest death toll in the literature is 100
million, which suggests a 5.26% worldwide mortality (Johnson & Mueller, 2002).
Methodological decisions such as which reference year to use and whether to use
age-specific mortality explain some of the variation in these estimates. However, thislatest study demonstrates that anything above 25 million would require implausible
assumptions. For instance, it would require that mortality was highest among children,which is contrary to empirical data everywhere outside India (Spreeuwenberg et al.,2018, p. 2565), and that censuses around the world failed to register the population
4

A good overview of past erroneous figures can be found in Rosen (2007, pp. 209-210).
N. Africa: 7,970,300; W. Europe: 20,642,314; C. Europe: 5,199,620; Turkey: 5,500,012; Middle East:
14,590,841; World: 253,237,587 (Goldewijk et al., 2017).
6
Even in the worst-hit Byzantine Empire the pandemic was not at full force everywhere (Mordechai et al.,2019).
5

decline implied by such figures (Spreeuwenberg et al., 2019; Spreeuwenberg, personalcorrespondence, August 18, 2021). Moreover, 100 million was the upper end of a hugead hoc upwards adjustment to previous research that actually estimated a death toll of
50 million (Johnson & Mueller, 2002).7
Pre-historic population bottlenecks
Recorded history provides no plausible contender for the Black Death. I will now look
into plausible pre-historical population bottlenecks from genetic studies. Although noneof these events could have caused as many deaths as the Black Death, they may rival itin proportional terms because the global population was so much smaller.
But first, a bit of background on the methods used by these studies.8
Suppose you have an urn with ten balls, eight red and two blue. To simulate random
selection, you pull one random ball, note its colour, put it back in the urn and selectanother ball. You repeat this until you’ve drawn ten balls total. The colours you’ve drawn
are used to set the colour distribution of the next generation. For each draw, there is an
8 in 10 chance the ball is red. The cumulative chance the next generation will be entirely
red, given by multiplying the chance of red in all ten draws, is slightly over 1 in 10. But
suppose there was a sudden drop in population, such that the next generation consistsof only five balls. The chance of an entirely red generation is now almost 1 in 3.
Moreover, if there were many different colours, the distribution will shift towards a single
colour over many generations even without a population drop, but will do so at a slower
rate. (See also this didactic simulation from the University of Arizona.)
Certain genes are not subject to strong selective pressures and fluctuate randomly inthe population, just like the successive generations of blue and red balls. Suppose there
are two possible variants of one gene. As in our urn example, when a population
undergoes a drastic size reduction, there’s an increased probability that one variant will
be lost because most population members will have no offspring (Charlesworth, 2009;
Husemann et al., 2016; Plutynski, 2007; Wang et al., 2016). As we will see, genetic
studies reveal that human populations have much less genetic diversity than would be
expected if we had simply had constant growth since the first humans evolved. In other7

After compiling death tolls across the globe totalling close to 50 million, the article’s last paragraphstates: "Global mortality from the influenza pandemic appears to have been of the order of 50 million.
However, even this vast figure may be substantially lower than the real toll [...] the real pandemic mortality
may fall in the range of 50 to 100 million” (Johnson & Mueller, 2002, p. 115). No justification was given for
the 100 million upper bound.
8This field is particularly technical and complex. I will present simplified explanations. I will not address
the biases and their corrections involved in these methods. For instance, some methods will produce
skewed results as they get close to the first human generation because simulations often make a few
simplifying assumptions such as having only one couple at first and a sharp cut-off point between otherhominids and Homo Sapiens. One may simply ignore these results as statistical artefacts.

words, there were probably large reductions in population size at some point in our
history.
Geneticists use several other methods to infer past demographic changes. For instance,
the number of generations it would take with a constant mutation rate for current allele
diversity to have evolved from a homogenous population is known as the coalescence
time (Charlesworth, 2009). Coalescence time is also highly sensitive to changes in
population size, decreasing drastically after a bottleneck.
In all such models, only the population that contributes to genes in the next generationis considered; this population is called the effective population size and is generally
smaller than the actual census population (Allaby, 2020; Frankham, 1995; Yu et al.,2004). It remains the case that a drop in the effective population size will cause adecline in the population contributing to genes in succeeding generations.
Although still uncertain, there is high-quality recent genetic evidence, and modest
consensus among researchers, that a large population bottleneck happened tens of
thousands of years ago. It may have reduced the effective human population size by
40-90% outside Africa (Marth et al., 2004; Osipov et al., 2021; Voight et al., 2005;
Weaver & Roseman, 2008; Williams, 2012).9 The Toba supervolcanic eruption, whichhappened 74,000 years ago, has been proposed as the cause. While that theory is
considered plausible, it’s far from a certainty.10 I found only one very recent study
against the Toba hypothesis. That paper concedes that a population bottleneck very
likely occurred, but argues its timing doesn't coincide with the Toba supervolcano (Yostet al., 2018).11 In any case, while the bottleneck’s exact date is uncertain and it occurred
across hundreds of generations, it would still be the closest we ever came to extinction.
And even if it wasn’t the Toga supervolcano, its cause was almost surely natural.

9

It’s worth noting that the existence of a bottleneck has been disputed by some studies (Gathorne-Hardy& Harcourt-Smith, 2003; Hawks et al., 2000; Weaver & Roseman, 2008), but it is supported by the weightof the evidence.
On dating the bottleneck, a review says “about 50,000 years ago” (Weaver & Roseman, 2008). The mostcomprehensive study I could find considers a wide-range of parameters, with scenarios that range from
20,000 to 120,000 years ago. Their two best-fitting models start at 90,000 and 87,500 years ago (Voight
et al., 2005). A range of 20,000-120,000 correctly reflects the high uncertainty in these models and mightsuggest a 70,000 central figure, but few possible parameters were compatible with the extreme ends ofthis range.
10
For dating see Chesner et al. (1991) and Roberts et al. (2013). See my larger compilation of sources forandagainsttheTobabottleneck
hypothesis
here:
Quick assessment of a ~Toba population bottleneck hypothesis
11
This paper also seems to suffer with several issues, see additional comments here.

There is one other contender for the most deadly pre-historic catastrophe. At least four
recent genetic studies, so far unopposed, indicate the existence of a second population
collapse: a male-only population bottleneck at around 10,000 BC (Batini et al., 2015;
Karmin et al., 2015; Poznik et al., 2016; Zeng et al., 2018). The initial study found a
reduction of 60-80% in the global male effective population size (Karmin et al., 2015, fig.
S4B), which suggests a 20-25% reduction in the overall effective population size. That’s
higher than the highest estimate of the Black Death’s mortality rate of 17%. However,
the main tentatively proposed cause was anthropogenic: endemic wars between early
settlements.12 Moreover, these studies have not yet been closely scrutinised bysceptics. And, without a similar reduction in the female population, it’s unlikely we risked
extinction even with a 90% fall in the male population.
Still, this event would constitute a larger percentage death toll than the Black Death, andit might have had natural causes.
Conclusion
With the caveat that the two prehistoric examples are highly uncertain, the best
candidates for the top five deadliest natural catastrophes in the natural history of our
species are listed below. I’ve also added mortality rates for the COVID-19 pandemic, asof April 2022, for comparison.

12

Event

Years

Est. % world killed

Likely the Toba supervolcanic
eruption

88,000-48,000 BC

40-90%?????

10,000-7,000 BC

Up to 20-25%

Black Death

1346-1353

10%First Plague Pandemic

541-750

0.6-4.4%

Spanish Flu

1918-1920

0.9%

COVID-19 Pandemic

2019-2022

0.08-0.26%13

Sexual selection from surviving females mating with winning males playing as much of a role as war
deaths. Interestingly, the regional onset of this bottleneck tracks the onset of intensive agriculture whichenabled large permanent settlements (compare Karmin et al., 2015, fig. S4B; Stephens et al., 2019, fig.
S2). Intensive agriculture, as opposed to early extensive agriculture, is characterised by the use ofdomesticated animal and plant species, specialised agricultural tools such as the plough and sickle, andtechniques such as irrigation
13
Using the 14 April 2022 total reported and estimated from excess deaths (Economist, 2022).

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