Infographic: The History of Pandemics, by Death Toll
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Healthcare

Visualizing the History of Pandemics

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The History of Pandemics

Pan·dem·ic /panˈdemik/ (of a disease) prevalent over a whole country or the world.

As humans have spread across the world, so have infectious diseases. Even in this modern era, outbreaks are nearly constant, though not every outbreak reaches pandemic level as COVID-19 has.

Today’s visualization outlines some of history’s most deadly pandemics, from the Antonine Plague to the current COVID-19 event.

A Timeline of Historical Pandemics

Disease and illnesses have plagued humanity since the earliest days, our mortal flaw. However, it was not until the marked shift to agrarian communities that the scale and spread of these diseases increased dramatically.

Widespread trade created new opportunities for human and animal interactions that sped up such epidemics. Malaria, tuberculosis, leprosy, influenza, smallpox, and others first appeared during these early years.

The more civilized humans became – with larger cities, more exotic trade routes, and increased contact with different populations of people, animals, and ecosystems – the more likely pandemics would occur.

Here are some of the major pandemics that have occurred over time:

NameTime periodType / Pre-human hostDeath toll
Antonine Plague165-180Believed to be either smallpox or measles5M
Japanese smallpox epidemic735-737Variola major virus1M
Plague of Justinian541-542Yersinia pestis bacteria / Rats, fleas30-50M
Black Death1347-1351Yersinia pestis bacteria / Rats, fleas200M
New World Smallpox Outbreak1520 – onwardsVariola major virus56M
Great Plague of London1665Yersinia pestis bacteria / Rats, fleas100,000
Italian plague1629-1631Yersinia pestis bacteria / Rats, fleas1M
Cholera Pandemics 1-61817-1923V. cholerae bacteria1M+
Third Plague1885Yersinia pestis bacteria / Rats, fleas12M (China and India)
Yellow FeverLate 1800sVirus / Mosquitoes100,000-150,000 (U.S.)
Russian Flu1889-1890Believed to be H2N2 (avian origin)1M
Spanish Flu1918-1919H1N1 virus / Pigs40-50M
Asian Flu1957-1958H2N2 virus1.1M
Hong Kong Flu1968-1970H3N2 virus1M
HIV/AIDS1981-presentVirus / Chimpanzees25-35M
Swine Flu2009-2010H1N1 virus / Pigs200,000
SARS2002-2003Coronavirus / Bats, Civets770
Ebola2014-2016Ebolavirus / Wild animals11,000
MERS2015-PresentCoronavirus / Bats, camels850
COVID-192019-PresentCoronavirus – Unknown (possibly pangolins)2.7M (Johns Hopkins University estimate as of March 16, 2021)

Note: Many of the death toll numbers listed above are best estimates based on available research. Some, such as the Plague of Justinian and Swine Flu, are subject to debate based on new evidence.

Despite the persistence of disease and pandemics throughout history, there’s one consistent trend over time – a gradual reduction in the death rate. Healthcare improvements and understanding the factors that incubate pandemics have been powerful tools in mitigating their impact.

September 2, 2021 Update: Due to popular request, we’ve also visualized how the death tolls of each pandemic stack up as a share of total estimated global populations at the time.

Wrath of the Gods

In many ancient societies, people believed that spirits and gods inflicted disease and destruction upon those that deserved their wrath. This unscientific perception often led to disastrous responses that resulted in the deaths of thousands, if not millions.

In the case of Justinian’s plague, the Byzantine historian Procopius of Caesarea traced the origins of the plague (the Yersinia pestis bacteria) to China and northeast India, via land and sea trade routes to Egypt where it entered the Byzantine Empire through Mediterranean ports.

Despite his apparent knowledge of the role geography and trade played in this spread, Procopius laid blame for the outbreak on the Emperor Justinian, declaring him to be either a devil, or invoking God’s punishment for his evil ways. Some historians found that this event could have dashed Emperor Justinian’s efforts to reunite the Western and Eastern remnants of the Roman Empire, and marked the beginning of the Dark Ages.

Luckily, humanity’s understanding of the causes of disease has improved, and this is resulting in a drastic improvement in the response to modern pandemics, albeit slow and incomplete.

Importing Disease

The practice of quarantine began during the 14th century, in an effort to protect coastal cities from plague epidemics. Cautious port authorities required ships arriving in Venice from infected ports to sit at anchor for 40 days before landing — the origin of the word quarantine from the Italian “quaranta giorni”, or 40 days.

One of the first instances of relying on geography and statistical analysis was in mid-19th century London, during a cholera outbreak. In 1854, Dr. John Snow came to the conclusion that cholera was spreading via tainted water and decided to display neighborhood mortality data directly on a map. This method revealed a cluster of cases around a specific pump from which people were drawing their water from.

While the interactions created through trade and urban life play a pivotal role, it is also the virulent nature of particular diseases that indicate the trajectory of a pandemic.

Tracking Infectiousness

Scientists use a basic measure to track the infectiousness of a disease called the reproduction number — also known as R0 or “R naught.” This number tells us how many susceptible people, on average, each sick person will in turn infect.

Measles tops the list, being the most contagious with a R0 range of 12-18. This means a single person can infect, on average, 12 to 18 people in an unvaccinated population.

While measles may be the most virulent, vaccination efforts and herd immunity can curb its spread. The more people are immune to a disease, the less likely it is to proliferate, making vaccinations critical to prevent the resurgence of known and treatable diseases.

It’s hard to calculate and forecast the true impact of COVID-19, as the outbreak is still ongoing and researchers are still learning about this new form of coronavirus.

Urbanization and the Spread of Disease

We arrive at where we began, with rising global connections and interactions as a driving force behind pandemics. From small hunting and gathering tribes to the metropolis, humanity’s reliance on one another has also sparked opportunities for disease to spread.

Urbanization in the developing world is bringing more and more rural residents into denser neighborhoods, while population increases are putting greater pressure on the environment. At the same time, passenger air traffic nearly doubled in the past decade. These macro trends are having a profound impact on the spread of infectious disease.

As organizations and governments around the world ask for citizens to practice social distancing to help reduce the rate of infection, the digital world is allowing people to maintain connections and commerce like never before.

Editor’s Note: The COVID-19 pandemic is in its early stages and it is obviously impossible to predict its future impact. This post and infographic are meant to provide historical context, and we will continue to update it as time goes on to maintain its accuracy.

Update (March 15, 2020): We’ve adjusted the death toll for COVID-19, and will continue to update on a regular basis.

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Economy

When Will Your Country Recover from the Pandemic?

The path to COVID-19 recovery varies worldwide—some countries have already recovered, while others will not be back to normal for years.

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What started as a novel virus in China quickly became a sweeping disease that shut down the world and put a 1.5 year halt on the global economy.

But while some countries’ economies are already back to normal, others are lagging far behind.

COVID-19 Recovery Timelines, by OECD Country

This chart using data from the OECD anticipates when countries will economically recover from the global pandemic, based on getting back to pre-pandemic levels of GDP per capita.

Note: The categorization of ‘advanced’ or ‘emerging’ economy was determined by OECD standards.

covid-19 recovery time by country

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The Leaders of the Pack

At the top, China and the U.S. are recovering at breakneck speed. In fact, recovering is the wrong word for China, as they reached pre-pandemic GDP per capita levels just after Q2’2020.

On the other end, some countries are looking at years—not months—when it comes to their recovery date. Saudi Arabia isn’t expected to recover until after Q1’2024, and Argentina is estimated to have an even slower recovery, occurring only after Q2’2026.

CountryRecoveryEconomy
🇧🇪 BelgiumAfter Q4 2022Advanced
🇸🇪 SwedenAfter Q4 2021Advanced
🇸🇰 SlovakiaAfter Q4 2021Advanced
🇳🇿 New ZealandAfter Q4 2021Advanced
🇩🇪 GermanyAfter Q4 2021Advanced
🇪🇪 EstoniaAfter Q4 2021Advanced
🇩🇰 DenmarkAfter Q4 2021Advanced
🇮🇸 IcelandAfter Q3 2023Advanced
🇸🇮 SloveniaAfter Q3 2022Advanced
🇵🇹 PortugalAfter Q3 2022Advanced
🇫🇷 FranceAfter Q3 2022Advanced
🇦🇹 AustriaAfter Q3 2022Advanced
🇵🇱 PolandAfter Q3 2021Advanced
🇳🇴 NorwayAfter Q3 2021Advanced
🇱🇺 LuxembourgAfter Q3 2021Advanced
🇱🇻 LatviaAfter Q3 2021Advanced
🇯🇵 JapanAfter Q3 2021Advanced
🇫🇮 FinlandAfter Q3 2021Advanced
🇪🇸 SpainAfter Q2 2023Advanced
🇬🇧 United KingdomAfter Q2 2022Advanced
🇳🇱 NetherlandsAfter Q2 2022Advanced
🇮🇹 ItalyAfter Q2 2022Advanced
🇬🇷 GreeceAfter Q2 2022Advanced
🇨🇿 Czech RepublicAfter Q2 2022Advanced
🇨🇦 CanadaAfter Q2 2022Advanced
🇺🇸 United StatesAfter Q2 2021Advanced
🇰🇷 South KoreaAfter Q2 2021Advanced
🇮🇪 IrelandAfter Q2 2021Advanced
🇨🇭 SwitzerlandAfter Q1 2022Advanced
🇮🇱 IsraelAfter Q1 2022Advanced
🇭🇺 HungaryAfter Q1 2022Advanced
🇦🇺 AustraliaAfter Q1 2022Advanced
🇱🇹 LithuaniaAfter Q1 2021Advanced
🇿🇦 South AfricaAfter Q4 2022Emerging
🇮🇩 IndonesiaAfter Q4 2021Emerging
🇮🇳 IndiaAfter Q4 2021Emerging
🇲🇽 MexicoAfter Q3 2023Emerging
🇨🇴 ColombiaAfter Q3 2022Emerging
🇧🇷 BrazilAfter Q3 2022Emerging
🇨🇱 ChileAfter Q3 2021Emerging
🇹🇷 TurkeyAfter Q3 2020Emerging
🇦🇷 ArgentinaAfter Q2 2026Emerging
🇨🇷 Costa RicaAfter Q2 2023Emerging
🇷🇺 RussiaAfter Q2 2021Emerging
🇨🇳 ChinaAfter Q2 2020Emerging
🇸🇦 Saudi ArabiaAfter Q1 2024Emerging

Most countries will hit pre-pandemic levels of GDP per capita by the end of 2022. The slowest recovering advanced economies—Iceland and Spain—aren’t expected to bounce back until 2023.

Four emerging economies are speeding ahead, and are predicted to get back on their feet by the end of this year or slightly later (if they haven’t already):

  • 🇷🇺 Russia: after Q2’2021
  • 🇨🇱 Chile: after Q3’2021
  • 🇮🇳 India: after Q4’2021
  • 🇮🇩 Indonesia: after Q4’2021

However, no recovery is guaranteed, and many countries will continue face setbacks as waves of COVID-19 variants hit—India, for example, was battling its biggest wave as recently as May 2021.

Trailing Behind

Why are some countries recovering faster than others? One factor seems to be vaccination rates.

CountryDoses Administered per 100 PeopleTotal Doses AdministeredPercent of Population Fully Vaccinated
World473,573,004,544
🇦🇪 U.A.E.16616,194,52669%
🇲🇹 Malta143718,41871%
🇧🇭 Bahrain1362,224,91663%
🇮🇸 Iceland129466,43470%
🇺🇾 Uruguay1294,458,39458%
🇨🇱 Chile12824,248,54560%
🇦🇼 Aruba125133,42159%
🇶🇦 Qatar1233,474,94456%
🇬🇧 United Kingdom12281,438,89253%
Mongolia1213,912,99656%
Israel12110,959,63358%
Canada11844,293,65948%
Singapore1136,440,73542%
Belgium11112,700,51346%
Curaçao108170,85751%
Denmark1086,266,89243%
Maldives106561,74846%
Netherlands10518,273,23843%
Spain10549,585,19749%
Hungary10410,155,46654%
Portugal10310,579,25944%
Luxembourg102633,97441%
Germany10284,989,85045%
China1021,426,347,000
United States101336,054,95348%
Ireland1014,995,71944%
Austria1008,866,47444%
Italy9959,966,90841%
Switzerland958,133,48642%
France9362,321,35540%
Sweden939,536,16436%
Finland904,951,92526%
Norway894,785,93731%
Greece899,560,59242%
Lithuania882,459,60542%
Czech Republic889,346,39738%
Poland8532,413,19942%
Dominican Rep.849,066,15134%
Estonia791,049,41634%
Serbia785,415,43438%
Slovenia781,626,07236%
Cyprus76916,81935%
Turkey7461,747,39923%
Slovakia734,003,63933%
Mauritius71901,53024%
Croatia712,870,86632%
Macau69434,72627%
Cuba697,767,60117%
Latvia661,264,43333%
Bhutan64487,0600.02%
Saudi Arabia6321,556,3149.2%
Hong Kong624,638,90826%
Barbados59168,95525%
Argentina5826,134,81511%
Brazil57120,726,75216%
Kuwait562,375,45522%
Morocco5620,584,81226%
Cambodia56924292524%
El Salvador533,422,21420%
Japan5366,714,52820%
Costa Rica522,606,79116%
French Polynesia51141,52324%
Montenegro49304,65523%
Fiji47419,9988%
Romania479,092,14124%
Guyana46363,44216%
Colombia4522,624,56819%
Jordan454,498,74818%
Azerbaijan424,242,72717%
Panama421,781,54215%
Mexico4152,704,96017%
Malaysia4113,107,68113%
South Korea4121,157,61212%
New Caledonia40115,21819%
Ecuador406,890,87610%
Kazakhstan397,303,18014%
Suriname38222,3778%
Australia389,631,80710%
Belize38147,08010%
Albania371,052,10816%
Russia3550,383,63814%
Oman351,728,6186%
North Macedonia34713,11413%
Samoa3262,1614.7%
Moldova31834,52713%
Grenada3135,07213%
Peru319,954,42912%
Saint Lucia3054,36113%
Sri Lanka296,431,1007.3%
India29391,340,4916%
New Zealand291,404,34311%
Brunei28121,2414.3%
Tonga2728,667
Bulgaria271,896,57412%
Bolivia273,117,5217%
Trinidad and Tobago27375,92411%
Bahamas2597,99210%
Lebanon251,693,1649%
Laos241,708,9819%
Saint Vincent and the Grenadines2325,509
Cape Verde23124,9583%
Timor-Leste22281,2833%
Indonesia2155,819,7816%
Equatorial Guinea21279,1129%
West Bank & Gaza20958,5199%
Thailand1913,533,7175%
Taiwan194,603,6391%
Tunisia192,206,9806%
São Tomé and Príncipe1837,7165%
Bosnia and Herzegovina14470,2185%
Venezuela144,000,0004%
Nepal133,730,3444%
Philippines1314,074,5144%
Botswana12284,6765%
Honduras121,172,8301%
Paraguay12826,6422%
Belarus
Zimbabwe111,575,5394%
Comoros1190,880
Uzbekistan113,541,4424%
Pakistan102,166,06502%
Jamaica9.8290,3824%
Armenia8.8260,8132%
Ukraine8.83,899,8903%
Iran7.96,530,1243%
Georgia7.8289,3993%
South Africa7.74,535,2223%
Guatemala6.91,146,4771%
Namibia6.7166,6161%
Myanmar6.5*3,500,000
Libya6.3425,119
Bangladesh6.210,108,2243%
Guinea6770,6882%
Algeria
Eswatini5.260,0692%
Rwanda5.1646,9092%
Senegal5.1823,6102%
Angola4.91,558,2012%
Egypt4.84,851,3491%
Vanuatu4.714,026
Vietnam4.34,185,6230.3%
Togo
Tajikistan4.3397,6940.2%
Ghana4.21,265,3061%
Mauritania4182,6420.3%
Solomon Islands3.825,6281%
Ivory Coast3.3861,278
Gabon3.372,3511%
Republic of the Congo3163,742
Kenya2.91,550,3891%
Sierra Leone2.9225,3800.2%
Iraq2.81,087,8661%
Djibouti2.826,796
Afghanistan2.71,024,1681%
Kyrgyzstan2.7173,7001.%
Lesotho2.756,3221%
Nicaragua
Uganda2.41,079,943
Malawi2.3428,4070.2%
Nigeria23,938,9451%
Liberia1.995,4230.2%
Ethiopia1.92,090,997
Gambia1.943,5571%
Niger1.8423,3350.3%
Mozambique1.7508,1841%
Central African Republic1.778,685
Somalia1.6249,7901%
Sudan1.6677,9570.3%
Zambia1.4243,8180.3%
Guinea-Bissau1.325,0120.1%
Yemen1297,405<0.1%
Mali1196,8620.3%
Syria0.8131,2210.1%
Madagascar0.7197,001
Turkmenistan
Cameroon0.6163,9210.1%
Papua New Guinea0.651,170<0.1%
South Sudan0.555,915<0.1%
Benin0.452,5630.1%
Burkina Faso0.233,960<0.1%
Chad0.224,459<0.1%
Congo0.173,764<0.1%

As of July 16th, 2021.

The higher the rate of vaccination, the harder it is for COVID-19 to spread. This gives countries a chance to loosen restrictions, let people get back to work and regular life, and fuel the economy. Additionally, the quicker vaccines are rolled out, the less time there is for variants to mutate.

Another factor is the overall strength of a country’s healthcare infrastructure. More advanced economies often have more ICU capacity, more efficient dissemination of public health information, and, simply, more hospital staff. These traits help better handle the pandemic, with reduced cases, less restrictions, and a speedy recovery.

Finally, the level of government support and fiscal stimulus injected into different economies has determined how swiftly they’ve recovered. Similar to the disparity in vaccine rollouts, there was a significant fiscal stimulus gap, especially during the heat of the pandemic.

Recovering to Normal?

Many experts and government leaders are now advocating for funneling more money into healthcare infrastructure and disease research preventatively. The increased funding now would help stop worldwide shut downs and needless loss of life in future.

Time will tell when we return to “normal” everywhere, however, normal will likely never be the same. Many impacts of the global pandemic will stay with us over the long term.

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Markets

Charted: The Gen Z Unemployment Rate, Compared to Older Generations

COVID-19 has impacted everyone, but one generation is taking it harder than the others. This graphic reveals the Gen Z unemployment rate.

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Putting the Gen Z Unemployment Rate in Perspective

There are more than 2 billion people in the Generation Z age range globally. These individuals, born between 1997 and 2009, represent about 30% of the total global population—and it’s predicted that by 2025, Gen Z will make up about 27% of the workforce.

Due to the global pandemic, unemployment has been on the rise across the board—but Gen Z has been hit the hardest. This chart, using data from the OECD, displays the difference between the unemployment rate for Gen Zers and the rate for older generations.

Note: The OECD defines the ‘unemployed’ as people of legal working age who don’t have work, are available to work, and have taken steps to find a job. The final figure is the number of unemployed people as a share of the total labor force.

The Generation Gap: Gen Z Unemployment

Compared to their older working-age counterparts, Baby Boomers, Gen X, and Millennials (Gen Y)—the most recent 2020 data shows that Gen Z has an unemployment rate of nearly 2x more in almost every OECD country.

CountryUnemployment Rate (Gen Z)Unemployment Rate (Millennial, Gen X, Boomer)
🇦🇺 Australia14.3%5.0%
🇦🇹 Austria10.5%4.7%
🇧🇪 Belgium15.3%4.8%
🇨🇦 Canada20.0%7.9%
🇨🇱 Chile24.8%9.6%
🇨🇴 Colombia27.5%13.9%
🇨🇿 Czech Republic8.0%2.3%
🇩🇰 Denmark11.5%4.7%
🇪🇪 Estonia17.7%5.9%
🇫🇮 Finland21.0%6.0%
🇫🇷 France20.1%6.8%
🇩🇪 Germany6.2%4.0%
🇭🇺 Hungary12.4%3.5%
🇮🇸 Iceland11.9%5.5%
🇮🇪 Ireland15.2%4.4%
🇮🇱 Israel7.9%3.7%
🇮🇹 Italy29.1%-
🇯🇵 Japan4.5%2.6%
🇰🇷 South Korea10.5%3.6%
🇱🇻 Latvia14.8%7.7%
🇱🇹 Lithuania19.5%7.7%
🇱🇺 Luxembourg22.4%5.6%
🇲🇽 Mexico8.0%3.8%
🇳🇱 Netherlands9.1%2.8%
🇳🇿 New Zealand12.4%3.3%
🇵🇱 Poland10.9%2.6%
🇵🇹 Portugal22.9%5.9%
🇸🇰 Slovakia19.3%6.0%
🇸🇮 Slovenia14.2%4.3%
🇪🇸 Spain38.3%14.0%
🇸🇪 Sweden23.8%6.4%
🇨🇭 Switzerland8.6%4.3%
🇬🇧 United Kingdom13.5%3.2%
🇺🇸 United States15.1%7.1%

Note: For the purposes of this article, we are only considering the Gen Zers of legal working age—those born 1997-2006. The rest—Baby Boomers, Gen X, and Millennials—are those born between 1946–1996.

The timing for the youngest working generation could not be worse. Gen Z is just beginning to graduate college and high school, and are beginning to search for work and careers.

Gen Z is also an age group that is overrepresented in service industries like restaurants and travel–industries that were equally hard hit by the pandemic. In the U.S., for example, around 25% of young people work in the hospitality and leisure sectors. Between February and May 2020 alone, employment in these sectors decreased by 41%.

Countries like Spain are facing some of the biggest headwinds among OECD countries. The country already has a high unemployment rate for those aged 25-74, at 14%. But the unemployment rate for Gen Z is more than double that, at over 38%.

Implications For the Future

While it may be true throughout history that this age group is often less employed than older cohorts, the share of labor held by those aged 15-24 dropped significantly in 2020.

labor share gen z

Note: This chart represents the data from G7 countries.

In terms of their future employment prospects, some economists are anticipating what they call ‘scarring’. Due to longer periods of unemployment, Gen Z will miss out on formative years gaining experience and training. This may impact them later in life, as their ability to climb the career ladder will be affected.

Starting out slower can also hit earnings. One study found that long periods of youth unemployment can reduce lifetime income by 2%. Finally, it is also postulated that with the current economic situation, Gen Zers may accept lower paying jobs setting them on a track of comparatively lower earnings over their lifetime.

Overall, there are many future implications associated with the current unemployment rate for Gen Zers. Often getting your foot in the door after college or high school is one of the hardest steps in starting a career. Once you’re in, you gain knowledge, skills, and the oh-so-coveted experience needed to get ahead.

The Kids are Alright?

One positive for Gen Z is that they have been found to be more risk averse and financially conscious than other generations, and were so even prior to COVID-19. Many of them were children during the 2008 Recession and became very cautious as a result.

They are also the first digital generation— the first to grow up without any memory of a time before the internet. Additionally, they have been called the first global generation. This could mean that they pioneer location-independent careers, create innovative revenue streams, and find new ways to define work.

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