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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)6.9M (Johns Hopkins University estimate as of March 1, 2023)

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.

March 1, 2023 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.

Diagram showing R0, or how many people are infected on average by someone with a specific virus

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 1, 2023): We’ve adjusted the death toll for COVID-19, and will continue to update on a regular basis.

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Charted: The World’s Aging Population from 1950 to 2100

This graphic visualizes the world’s aging population, showing data for every country and territory around the world.

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Charted: The World’s Aging Population from 1950 to 2100

As demographics continue to shift in the 21st century, the world’s aging population will continue to be a focal point for many global decision makers.

Most countries around the world have experienced population explosions, or are about to. Combine this with declining birth rates and falling mortality rates, and it’s clear that the global senior population will continue to reach new heights.

These graphics by Pablo Alvarez use data from the 2022 UN World Population Prospects to visualize this increasing aging population across countries.

The World’s Aging Population from 1950 to 2100

In 2022, there were 771 million people aged 65+ years globally, accounting for almost 10% of the world’s population.

This segment has been growing at an increasing rate, and it’s expected to hit 16% in 2050, and eventually 24% by 2100. Here’s what that’s projected to look like, for every country and territory.

Country by Population Aged +65 Years195020222100
🇦🇫 Afghanistan2.85%2.39%16.03%
🇦🇱 Albania6.04%16.66%49.08%
🇩🇿 Algeria3.49%6.39%28.83%
🇦🇸 American Samoa2.38%7.27%45.41%
🇦🇩 Andorra10.02%14.98%37.04%
🇦🇴 Angola2.93%2.6%12.07%
🇦🇮 Anguilla3.69%10.71%37.49%
🇦🇬 Antigua and Barbuda4.14%10.63%35.4%
🇦🇷 Argentina4.13%11.92%31.79%
🇦🇲 Armenia8.17%13.15%36.13%
🇦🇼 Aruba1.77%16.15%36.51%
🇦🇺 Australia8.17%16.9%31.38%
🇦🇹 Austria10.42%19.81%33.93%
🇦🇿 Azerbaijan6.89%7.11%30.5%
🇧🇸 Bahamas4.76%8.89%29.58%
🇧🇭 Bahrain2.88%3.76%21.89%
🇧🇩 Bangladesh3.9%6.04%32.56%
🇧🇧 Barbados5.24%16.28%33.19%
🇧🇾 Belarus8.24%17.18%30.45%
🇧🇪 Belgium11.03%19.73%32.83%
🇧🇿 Belize3.57%5.09%29.21%
🇧🇯 Benin7.85%3.06%11.03%
🇧🇲 Bermuda5.71%20.41%37.73%
🇧🇹 Bhutan2.53%6.25%33.35%
🇧🇴 Bolivia6.11%4.85%21.75%
🇧🇶 Bonaire Sint Eustatius and Saba14.22%13.84%28.94%
🇧🇦 Bosnia and Herzegovina3.95%18.4%36.4%
🇧🇼 Botswana4.32%3.65%17.96%
🇧🇷 Brazil2.39%9.88%33.52%
🇻🇬 British Virgin Islands8.63%9.95%32.47%
🇧🇳 Brunei4.85%6.17%30.93%
🇧🇬 Bulgaria6.66%22.38%37.13%
🇧🇫 Burkina Faso2.01%2.53%13.07%
🇧🇮 Burundi3.22%2.48%13.23%
🇰🇭 Cambodia2.67%5.81%26.43%
🇨🇲 Cameroon3.47%2.67%11.89%
🇨🇦 Canada7.7%19.03%31.55%
🇨🇻 Cape Verde3.67%5.55%32.63%
🇰🇾 Cayman Islands6.05%8.17%28.75%
🇨🇫 Central African Republic5.%2.51%11.43%
🇹🇩 Chad4.33%2.01%9.64%
🇨🇱 Chile3.3%13.03%36.61%
🇨🇳 China5.04%13.72%40.93%
🇨🇴 Colombia3.22%9.%34.49%
🇰🇲 Comoros3.8%4.28%17.81%
🇨🇬 Congo3.36%2.72%11.99%
🇨🇰 Cook Islands2.94%11.73%29.75%
🇨🇷 Costa Rica2.97%10.83%36.99%
🇨🇮 Cote d'Ivoire2.21%2.4%10.86%
🇭🇷 Croatia7.82%22.36%37.03%
🇨🇺 Cuba4.36%15.81%36.31%
🇨🇼 Curacao5.82%14.95%30.46%
🇨🇾 Cyprus5.95%14.83%33.36%
🇨🇿 Czechia8.29%20.64%26.94%
🇨🇩 Democratic Republic of Congo3.77%2.92%10.62%
🇩🇰 Denmark9.04%20.49%30.45%
🇩🇯 Djibouti1.99%4.54%19.68%
🇩🇲 Dominica7.67%9.53%34.28%
🇩🇴 Dominican Republic2.72%7.4%30.47%
🇪🇨 Ecuador5.2%7.83%31.97%
🇪🇬 Egypt2.95%4.83%21.77%
🇸🇻 El Salvador3.93%8.22%36.02%
🇬🇶 Equatorial Guinea5.53%3.12%15.13%
🇪🇷 Eritrea3.2%4.01%19.86%
🇪🇪 Estonia10.56%20.58%34.15%
🇸🇿 Eswatini2.68%4.%16.26%
🇪🇹 Ethiopia3.01%3.14%18.6%
🇫🇴 Faeroe Islands7.59%17.92%26.91%
🇫🇰 Falkland Islands8.27%11.08%35.86%
🇫🇯 Fiji5.99%5.9%20.6%
🇫🇮 Finland6.63%23.27%34.04%
🇫🇷 France11.39%21.66%34.23%
🇬🇫 French Guiana7.96%5.98%21.13%
🇵🇫 French Polynesia3.%10.07%37.85%
🇬🇦 Gabon7.21%3.89%16.25%
🇬🇲 Gambia2.5%2.43%16.06%
🇬🇪 Georgia9.35%14.61%31.19%
🇩🇪 Germany9.46%22.41%33.72%
🇬🇭 Ghana4.62%3.55%15.91%
🇬🇮 Gibraltar6.94%20.84%37.63%
🇬🇷 Greece6.8%22.82%37.52%
🇬🇱 Greenland3.06%10.02%29.16%
🇬🇩 Grenada5.12%10.07%30.54%
🇬🇵 Guadeloupe5.51%20.04%34.45%
🇬🇺 Guam1.11%11.84%31.19%
🇬🇹 Guatemala2.31%4.91%28.05%
🇬🇬 Guernsey11.96%16.64%35.4%
🇬🇳 Guinea5.39%3.32%14.%
🇬🇼 Guinea-Bissau3.45%2.82%14.34%
🇬🇾 Guyana3.89%6.28%28.94%
🇭🇹 Haiti3.64%4.54%19.07%
🇭🇳 Honduras3.96%4.27%26.5%
🇭🇰 Hong Kong2.48%20.47%41.64%
🇭🇺 Hungary7.81%20.01%31.85%
🇮🇸 Iceland7.52%15.33%34.25%
🇮🇳 India3.1%6.9%29.81%
🇮🇩 Indonesia1.74%6.86%25.28%
🇮🇷 Iran5.22%7.62%33.72%
🇮🇶 Iraq2.79%3.41%18.44%
🇮🇪 Ireland10.99%15.14%32.48%
🇮🇲 Isle of Man13.9%22.29%31.8%
🇮🇱 Israel4.%12.04%25.97%
🇮🇹 Italy8.09%24.05%38.19%
🇯🇲 Jamaica3.83%7.45%44.05%
🇯🇵 Japan4.89%29.92%38.7%
🇯🇪 Jersey12.34%16.22%30.52%
🇯🇴 Jordan5.03%3.84%27.3%
🇰🇿 Kazakhstan6.47%8.04%19.58%
🇰🇪 Kenya5.28%2.87%16.98%
🇰🇮 Kiribati7.13%3.81%17.33%
🇽🇰 Kosovo5.33%10.19%43.35%
🇰🇼 Kuwait2.88%4.93%31.56%
🇰🇬 Kyrgyzstan7.91%4.54%21.08%
🇱🇦 Laos2.13%4.45%25.24%
🇱🇻 Latvia10.12%21.86%32.86%
🇱🇧 Lebanon7.24%9.89%32.11%
🇱🇸 Lesotho6.34%4.2%13.44%
🇱🇷 Liberia2.97%3.31%13.88%
🇱🇾 Libya5.21%4.86%27.77%
🇱🇮 Liechtenstein7.89%19.37%34.79%
🇱🇹 Lithuania8.65%20.8%32.79%
🇱🇺 Luxembourg9.71%15.03%31.55%
🇲🇴 Macao3.11%13.%32.39%
🇲🇬 Madagascar3.25%3.35%16.21%
🇲🇼 Malawi3.06%2.61%15.61%
🇲🇾 Malaysia4.91%7.5%30.78%
🇲🇻 Maldives3.14%4.78%35.61%
🇲🇱 Mali2.78%2.38%11.%
🇲🇹 Malta7.42%19.13%38.26%
🇲🇭 Marshall Islands5.68%4.56%17.8%
🇲🇶 Martinique5.85%22.77%37.31%
🇲🇷 Mauritania1.44%3.22%15.03%
🇲🇺 Mauritius3.18%12.79%33.76%
🇾🇹 Mayotte6.61%2.88%18.15%
🇲🇽 Mexico2.99%8.32%34.88%
🇫🇲 Micronesia (country)4.11%6.16%27.59%
🇲🇩 Moldova7.56%12.98%26.36%
🇲🇨 Monaco15.64%35.92%30.16%
🇲🇳 Mongolia3.87%4.61%26.18%
🇲🇪 Montenegro7.85%16.55%34.16%
🇲🇸 Montserrat7.92%17.7%33.05%
🇲🇦 Morocco2.86%7.72%29.97%
🇲🇿 Mozambique3.13%2.57%13.43%
🇲🇲 Myanmar3.21%6.82%23.69%
🇳🇦 Namibia4.1%3.97%15.38%
🇳🇷 Nauru8.98%2.5%15.87%
🇳🇵 Nepal2.74%6.09%29.51%
🇳🇱 Netherlands7.76%20.31%32.89%
🇳🇨 New Caledonia5.%11.02%31.61%
🇳🇿 New Zealand9.09%16.31%33.2%
🇳🇮 Nicaragua2.71%5.29%28.92%
🇳🇪 Niger.92%2.4%9.76%
🇳🇬 Nigeria3.%2.97%12.31%
🇳🇺 Niue4.79%15.16%22.55%
🇰🇵 North Korea2.72%11.71%30.49%
🇲🇰 North Macedonia5.87%14.91%36.56%
🇲🇵 Northern Mariana Islands2.95%10.81%32.09%
🇳🇴 Norway9.52%18.44%31.65%
🇴🇲 Oman3.05%2.76%23.96%
🇵🇰 Pakistan5.48%4.27%17.23%
🇵🇼 Palau8.59%9.93%21.48%
🇵🇸 Palestine4.77%3.53%23.44%
🇵🇦 Panama3.57%8.77%30.03%
🇵🇬 Papua New Guinea1.09%3.19%16.81%
🇵🇾 Paraguay3.73%6.26%26.51%
🇵🇪 Peru3.43%8.41%30.33%
🇵🇭 Philippines3.56%5.44%23.38%
🇵🇱 Poland5.22%18.55%35.69%
🇵🇹 Portugal7.%22.9%36.28%
🇵🇷 Puerto Rico3.63%22.93%48.9%
🇶🇦 Qatar3.5%1.52%15.01%
🇷🇪 Reunion3.81%13.28%32.4%
🇷🇴 Romania7.16%18.64%32.22%
🇷🇺 Russia4.8%15.8%27.86%
🇷🇼 Rwanda2.76%3.2%17.36%
🇧🇱 Saint Barthlemy7.3%10.61%43.89%
🇸🇭 Saint Helena8.63%28.66%32.61%
🇰🇳 Saint Kitts and Nevis5.36%10.13%29.79%
🇱🇨 Saint Lucia3.59%9.23%33.39%
🇲🇫 Saint Martin (French part)4.47%11.14%30.08%
🇵🇲 Saint Pierre and Miquelon6.34%17.32%33.4%
🇻🇨 Saint Vincent and the Grenadines7.71%10.86%32.34%
🇼🇸 Samoa2.52%5.22%18.75%
🇸🇲 San Marino10.15%20.47%35.73%
🇸🇹 Sao Tome and Principe3.92%3.76%15.6%
🇸🇦 Saudi Arabia3.32%2.81%30.28%
🇸🇳 Senegal3.42%3.14%16.54%
🇷🇸 Serbia6.15%20.56%37.55%
🇸🇨 Seychelles10.68%8.16%28.84%
🇸🇱 Sierra Leone3.02%3.14%15.52%
🇸🇬 Singapore2.29%15.12%36.51%
🇸🇽 Sint Maarten (Dutch part)12.03%10.57%34.51%
🇸🇰 Slovakia6.63%16.98%33.4%
🇸🇮 Slovenia7.52%20.96%33.59%
🇸🇧 Solomon Islands4.03%3.47%15.29%
🇸🇴 Somalia2.6%2.57%10.75%
🇿🇦 South Africa4.06%5.89%20.55%
🇰🇷 South Korea2.74%17.49%44.44%
🇸🇸 South Sudan3.48%2.89%13.11%
🇪🇸 Spain7.23%20.27%38.72%
🇱🇰 Sri Lanka8.76%11.54%35.73%
🇸🇩 Sudan3.03%3.5%13.28%
🇸🇷 Suriname4.09%7.39%25.8%
🇸🇪 Sweden10.19%20.25%31.83%
🇨🇭 Switzerland9.49%19.31%32.61%
🇸🇾 Syria7.66%4.68%24.62%
🇹🇼 Taiwan2.11%16.71%37.32%
🇹🇯 Tajikistan4.34%3.47%19.43%
🇹🇿 Tanzania2.2%3.1%14.97%
🇹🇭 Thailand3.21%15.21%39.17%
🇹🇱 Timor3.14%5.21%25.42%
🇹🇬 Togo4.29%3.13%11.77%
🇹🇰 Tokelau4.7%8.66%25.03%
🇹🇴 Tonga4.6%6.22%21.65%
🇹🇹 Trinidad and Tobago3.93%11.52%32.67%
🇹🇳 Tunisia4.4%9.02%31.24%
🇹🇷 Turkey3.77%8.64%33.9%
🇹🇲 Turkmenistan5.84%5.15%21.55%
🇹🇨 Turks and Caicos Islands5.79%10.34%28.25%
🇹🇻 Tuvalu4.98%6.48%16.15%
🇺🇬 Uganda2.87%1.69%14.33%
🇺🇦 Ukraine7.54%18.81%33.2%
🇦🇪 United Arab Emirates3.35%1.83%15.77%
🇬🇧 United Kingdom10.84%19.17%32.56%
🇺🇸 United States8.18%17.13%30.47%
🇻🇮 United States Virgin Islands7.54%20.42%39.11%
🇺🇾 Uruguay8.23%15.58%35.98%
🇺🇿 Uzbekistan5.87%5.14%22.24%
🇻🇺 Vanuatu5.65%3.74%16.29%
🇻🇪 Venezuela2.29%8.61%27.71%
🇻🇳 Vietnam4.13%9.12%30.02%
🇼🇫 Wallis and Futuna1.76%13.47%32.98%
🇪🇭 Western Sahara2.82%5.84%23.73%
🇾🇪 Yemen3.98%2.66%18.25%
🇿🇲 Zambia2.76%1.75%12.66%
🇿🇼 Zimbabwe3.18%3.32%14.22%
🌐 World5.13%9.82%24.03%

Some of the places with high elderly shares today include high-income countries like Japan (30%), Italy (24%), and Finland (23%).

The lowest shares are concentrated in the Middle East and Africa. Many countries have just 2% of their population aged 65 years and older, such as Qatar, Uganda, and Afghanistan.

But over time, almost all countries are expected to see their older population segments grow. In just three decades, it is estimated that one-in-four European, North American, and Asian residents will be over 65 years of age.

By 2100, a variety of Asian countries and island nations facing low population growth are expected to see more than one-third of their populations aged 65 years or older, including South Korea and Jamaica at 44%. However, it’s actually Albania that’s the biggest outlier overall, with a projected 49% of its population to be aged 65 and older by 2100.

Passing the Generational Torch

The challenge of an aging population is set to impact all sectors of society, including labor and financial markets, demand for housing and transportation, and especially family structures and intergenerational ties.

One way to help grasp the nature of transition is to note the changing ratio between seniors and young children in the world population, as seen in the below crossover diagram:

Elderly population surpass that of children aged 5 and below

Dropping fertility rates, in addition to improved child and infant mortality rates, are known to have played a major role in the plateauing population of children.

However, not all countries have witnessed this crossover yet, as it usually coincides with higher levels of economic development.

As countries such as India, Brazil, and South Africa reach higher levels of per capita income, they will be likely to follow down the paths of more advanced economies, eventually experiencing similar demographic fates and challenges.

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