Healthcare
Visualizing the History of Pandemics
The History of Pandemics
Panยทdemยทic /panหdemik/ (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.
Todayโs visualization outlines some of historyโs 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 โ with larger cities, more exotic trade routes, and increased contact with different populations of people, animals, and ecosystems โ the more likely pandemics would occur.
Here are some of the major pandemics that have occurred over time:
Name | Time period | Type / Pre-human host | Death toll |
---|---|---|---|
Antonine Plague | 165-180 | Believed to be either smallpox or measles | 5M |
Japanese smallpox epidemic | 735-737 | Variola major virus | 1M |
Plague of Justinian | 541-542 | Yersinia pestis bacteria / Rats, fleas | 30-50M |
Black Death | 1347-1351 | Yersinia pestis bacteria / Rats, fleas | 200M |
New World Smallpox Outbreak | 1520 โ onwards | Variola major virus | 56M |
Great Plague of London | 1665 | Yersinia pestis bacteria / Rats, fleas | 100,000 |
Italian plague | 1629-1631 | Yersinia pestis bacteria / Rats, fleas | 1M |
Cholera Pandemics 1-6 | 1817-1923 | V. cholerae bacteria | 1M+ |
Third Plague | 1885 | Yersinia pestis bacteria / Rats, fleas | 12M (China and India) |
Yellow Fever | Late 1800s | Virus / Mosquitoes | 100,000-150,000 (U.S.) |
Russian Flu | 1889-1890 | Believed to be H2N2 (avian origin) | 1M |
Spanish Flu | 1918-1919 | H1N1 virus / Pigs | 40-50M |
Asian Flu | 1957-1958 | H2N2 virus | 1.1M |
Hong Kong Flu | 1968-1970 | H3N2 virus | 1M |
HIV/AIDS | 1981-present | Virus / Chimpanzees | 25-35M |
Swine Flu | 2009-2010 | H1N1 virus / Pigs | 200,000 |
SARS | 2002-2003 | Coronavirus / Bats, Civets | 770 |
Ebola | 2014-2016 | Ebolavirus / Wild animals | 11,000 |
MERS | 2015-Present | Coronavirus / Bats, camels | 850 |
COVID-19 | 2019-Present | Coronavirus โ 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 โ 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 Godโs punishment for his evil ways. Some historians found that this event could have dashed Emperor Justinianโs efforts to reunite the Western and Eastern remnants of the Roman Empire, and marked the beginning of the Dark Ages.
Luckily, humanityโs 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 โ the origin of the word quarantine from the Italian โquaranta giorniโ, 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 โ 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, humanityโs 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.
Countries
Charted: The Worldโs Aging Population from 1950 to 2100
This graphic visualizes the worldโs aging population, showing data for every country and territory around the world.

Charted: The Worldโs Aging Population from 1950 to 2100
As demographics continue to shift in the 21st century, the worldโs 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 Worldโs 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 Years | 1950 | 2022 | 2100 |
---|---|---|---|
๐ฆ๐ซ Afghanistan | 2.85% | 2.39% | 16.03% |
๐ฆ๐ฑ Albania | 6.04% | 16.66% | 49.08% |
๐ฉ๐ฟ Algeria | 3.49% | 6.39% | 28.83% |
๐ฆ๐ธ American Samoa | 2.38% | 7.27% | 45.41% |
๐ฆ๐ฉ Andorra | 10.02% | 14.98% | 37.04% |
๐ฆ๐ด Angola | 2.93% | 2.6% | 12.07% |
๐ฆ๐ฎ Anguilla | 3.69% | 10.71% | 37.49% |
๐ฆ๐ฌ Antigua and Barbuda | 4.14% | 10.63% | 35.4% |
๐ฆ๐ท Argentina | 4.13% | 11.92% | 31.79% |
๐ฆ๐ฒ Armenia | 8.17% | 13.15% | 36.13% |
๐ฆ๐ผ Aruba | 1.77% | 16.15% | 36.51% |
๐ฆ๐บ Australia | 8.17% | 16.9% | 31.38% |
๐ฆ๐น Austria | 10.42% | 19.81% | 33.93% |
๐ฆ๐ฟ Azerbaijan | 6.89% | 7.11% | 30.5% |
๐ง๐ธ Bahamas | 4.76% | 8.89% | 29.58% |
๐ง๐ญ Bahrain | 2.88% | 3.76% | 21.89% |
๐ง๐ฉ Bangladesh | 3.9% | 6.04% | 32.56% |
๐ง๐ง Barbados | 5.24% | 16.28% | 33.19% |
๐ง๐พ Belarus | 8.24% | 17.18% | 30.45% |
๐ง๐ช Belgium | 11.03% | 19.73% | 32.83% |
๐ง๐ฟ Belize | 3.57% | 5.09% | 29.21% |
๐ง๐ฏ Benin | 7.85% | 3.06% | 11.03% |
๐ง๐ฒ Bermuda | 5.71% | 20.41% | 37.73% |
๐ง๐น Bhutan | 2.53% | 6.25% | 33.35% |
๐ง๐ด Bolivia | 6.11% | 4.85% | 21.75% |
๐ง๐ถ Bonaire Sint Eustatius and Saba | 14.22% | 13.84% | 28.94% |
๐ง๐ฆ Bosnia and Herzegovina | 3.95% | 18.4% | 36.4% |
๐ง๐ผ Botswana | 4.32% | 3.65% | 17.96% |
๐ง๐ท Brazil | 2.39% | 9.88% | 33.52% |
๐ป๐ฌ British Virgin Islands | 8.63% | 9.95% | 32.47% |
๐ง๐ณ Brunei | 4.85% | 6.17% | 30.93% |
๐ง๐ฌ Bulgaria | 6.66% | 22.38% | 37.13% |
๐ง๐ซ Burkina Faso | 2.01% | 2.53% | 13.07% |
๐ง๐ฎ Burundi | 3.22% | 2.48% | 13.23% |
๐ฐ๐ญ Cambodia | 2.67% | 5.81% | 26.43% |
๐จ๐ฒ Cameroon | 3.47% | 2.67% | 11.89% |
๐จ๐ฆ Canada | 7.7% | 19.03% | 31.55% |
๐จ๐ป Cape Verde | 3.67% | 5.55% | 32.63% |
๐ฐ๐พ Cayman Islands | 6.05% | 8.17% | 28.75% |
๐จ๐ซ Central African Republic | 5.% | 2.51% | 11.43% |
๐น๐ฉ Chad | 4.33% | 2.01% | 9.64% |
๐จ๐ฑ Chile | 3.3% | 13.03% | 36.61% |
๐จ๐ณ China | 5.04% | 13.72% | 40.93% |
๐จ๐ด Colombia | 3.22% | 9.% | 34.49% |
๐ฐ๐ฒ Comoros | 3.8% | 4.28% | 17.81% |
๐จ๐ฌ Congo | 3.36% | 2.72% | 11.99% |
๐จ๐ฐ Cook Islands | 2.94% | 11.73% | 29.75% |
๐จ๐ท Costa Rica | 2.97% | 10.83% | 36.99% |
๐จ๐ฎ Cote d'Ivoire | 2.21% | 2.4% | 10.86% |
๐ญ๐ท Croatia | 7.82% | 22.36% | 37.03% |
๐จ๐บ Cuba | 4.36% | 15.81% | 36.31% |
๐จ๐ผ Curacao | 5.82% | 14.95% | 30.46% |
๐จ๐พ Cyprus | 5.95% | 14.83% | 33.36% |
๐จ๐ฟ Czechia | 8.29% | 20.64% | 26.94% |
๐จ๐ฉ Democratic Republic of Congo | 3.77% | 2.92% | 10.62% |
๐ฉ๐ฐ Denmark | 9.04% | 20.49% | 30.45% |
๐ฉ๐ฏ Djibouti | 1.99% | 4.54% | 19.68% |
๐ฉ๐ฒ Dominica | 7.67% | 9.53% | 34.28% |
๐ฉ๐ด Dominican Republic | 2.72% | 7.4% | 30.47% |
๐ช๐จ Ecuador | 5.2% | 7.83% | 31.97% |
๐ช๐ฌ Egypt | 2.95% | 4.83% | 21.77% |
๐ธ๐ป El Salvador | 3.93% | 8.22% | 36.02% |
๐ฌ๐ถ Equatorial Guinea | 5.53% | 3.12% | 15.13% |
๐ช๐ท Eritrea | 3.2% | 4.01% | 19.86% |
๐ช๐ช Estonia | 10.56% | 20.58% | 34.15% |
๐ธ๐ฟ Eswatini | 2.68% | 4.% | 16.26% |
๐ช๐น Ethiopia | 3.01% | 3.14% | 18.6% |
๐ซ๐ด Faeroe Islands | 7.59% | 17.92% | 26.91% |
๐ซ๐ฐ Falkland Islands | 8.27% | 11.08% | 35.86% |
๐ซ๐ฏ Fiji | 5.99% | 5.9% | 20.6% |
๐ซ๐ฎ Finland | 6.63% | 23.27% | 34.04% |
๐ซ๐ท France | 11.39% | 21.66% | 34.23% |
๐ฌ๐ซ French Guiana | 7.96% | 5.98% | 21.13% |
๐ต๐ซ French Polynesia | 3.% | 10.07% | 37.85% |
๐ฌ๐ฆ Gabon | 7.21% | 3.89% | 16.25% |
๐ฌ๐ฒ Gambia | 2.5% | 2.43% | 16.06% |
๐ฌ๐ช Georgia | 9.35% | 14.61% | 31.19% |
๐ฉ๐ช Germany | 9.46% | 22.41% | 33.72% |
๐ฌ๐ญ Ghana | 4.62% | 3.55% | 15.91% |
๐ฌ๐ฎ Gibraltar | 6.94% | 20.84% | 37.63% |
๐ฌ๐ท Greece | 6.8% | 22.82% | 37.52% |
๐ฌ๐ฑ Greenland | 3.06% | 10.02% | 29.16% |
๐ฌ๐ฉ Grenada | 5.12% | 10.07% | 30.54% |
๐ฌ๐ต Guadeloupe | 5.51% | 20.04% | 34.45% |
๐ฌ๐บ Guam | 1.11% | 11.84% | 31.19% |
๐ฌ๐น Guatemala | 2.31% | 4.91% | 28.05% |
๐ฌ๐ฌ Guernsey | 11.96% | 16.64% | 35.4% |
๐ฌ๐ณ Guinea | 5.39% | 3.32% | 14.% |
๐ฌ๐ผ Guinea-Bissau | 3.45% | 2.82% | 14.34% |
๐ฌ๐พ Guyana | 3.89% | 6.28% | 28.94% |
๐ญ๐น Haiti | 3.64% | 4.54% | 19.07% |
๐ญ๐ณ Honduras | 3.96% | 4.27% | 26.5% |
๐ญ๐ฐ Hong Kong | 2.48% | 20.47% | 41.64% |
๐ญ๐บ Hungary | 7.81% | 20.01% | 31.85% |
๐ฎ๐ธ Iceland | 7.52% | 15.33% | 34.25% |
๐ฎ๐ณ India | 3.1% | 6.9% | 29.81% |
๐ฎ๐ฉ Indonesia | 1.74% | 6.86% | 25.28% |
๐ฎ๐ท Iran | 5.22% | 7.62% | 33.72% |
๐ฎ๐ถ Iraq | 2.79% | 3.41% | 18.44% |
๐ฎ๐ช Ireland | 10.99% | 15.14% | 32.48% |
๐ฎ๐ฒ Isle of Man | 13.9% | 22.29% | 31.8% |
๐ฎ๐ฑ Israel | 4.% | 12.04% | 25.97% |
๐ฎ๐น Italy | 8.09% | 24.05% | 38.19% |
๐ฏ๐ฒ Jamaica | 3.83% | 7.45% | 44.05% |
๐ฏ๐ต Japan | 4.89% | 29.92% | 38.7% |
๐ฏ๐ช Jersey | 12.34% | 16.22% | 30.52% |
๐ฏ๐ด Jordan | 5.03% | 3.84% | 27.3% |
๐ฐ๐ฟ Kazakhstan | 6.47% | 8.04% | 19.58% |
๐ฐ๐ช Kenya | 5.28% | 2.87% | 16.98% |
๐ฐ๐ฎ Kiribati | 7.13% | 3.81% | 17.33% |
๐ฝ๐ฐ Kosovo | 5.33% | 10.19% | 43.35% |
๐ฐ๐ผ Kuwait | 2.88% | 4.93% | 31.56% |
๐ฐ๐ฌ Kyrgyzstan | 7.91% | 4.54% | 21.08% |
๐ฑ๐ฆ Laos | 2.13% | 4.45% | 25.24% |
๐ฑ๐ป Latvia | 10.12% | 21.86% | 32.86% |
๐ฑ๐ง Lebanon | 7.24% | 9.89% | 32.11% |
๐ฑ๐ธ Lesotho | 6.34% | 4.2% | 13.44% |
๐ฑ๐ท Liberia | 2.97% | 3.31% | 13.88% |
๐ฑ๐พ Libya | 5.21% | 4.86% | 27.77% |
๐ฑ๐ฎ Liechtenstein | 7.89% | 19.37% | 34.79% |
๐ฑ๐น Lithuania | 8.65% | 20.8% | 32.79% |
๐ฑ๐บ Luxembourg | 9.71% | 15.03% | 31.55% |
๐ฒ๐ด Macao | 3.11% | 13.% | 32.39% |
๐ฒ๐ฌ Madagascar | 3.25% | 3.35% | 16.21% |
๐ฒ๐ผ Malawi | 3.06% | 2.61% | 15.61% |
๐ฒ๐พ Malaysia | 4.91% | 7.5% | 30.78% |
๐ฒ๐ป Maldives | 3.14% | 4.78% | 35.61% |
๐ฒ๐ฑ Mali | 2.78% | 2.38% | 11.% |
๐ฒ๐น Malta | 7.42% | 19.13% | 38.26% |
๐ฒ๐ญ Marshall Islands | 5.68% | 4.56% | 17.8% |
๐ฒ๐ถ Martinique | 5.85% | 22.77% | 37.31% |
๐ฒ๐ท Mauritania | 1.44% | 3.22% | 15.03% |
๐ฒ๐บ Mauritius | 3.18% | 12.79% | 33.76% |
๐พ๐น Mayotte | 6.61% | 2.88% | 18.15% |
๐ฒ๐ฝ Mexico | 2.99% | 8.32% | 34.88% |
๐ซ๐ฒ Micronesia (country) | 4.11% | 6.16% | 27.59% |
๐ฒ๐ฉ Moldova | 7.56% | 12.98% | 26.36% |
๐ฒ๐จ Monaco | 15.64% | 35.92% | 30.16% |
๐ฒ๐ณ Mongolia | 3.87% | 4.61% | 26.18% |
๐ฒ๐ช Montenegro | 7.85% | 16.55% | 34.16% |
๐ฒ๐ธ Montserrat | 7.92% | 17.7% | 33.05% |
๐ฒ๐ฆ Morocco | 2.86% | 7.72% | 29.97% |
๐ฒ๐ฟ Mozambique | 3.13% | 2.57% | 13.43% |
๐ฒ๐ฒ Myanmar | 3.21% | 6.82% | 23.69% |
๐ณ๐ฆ Namibia | 4.1% | 3.97% | 15.38% |
๐ณ๐ท Nauru | 8.98% | 2.5% | 15.87% |
๐ณ๐ต Nepal | 2.74% | 6.09% | 29.51% |
๐ณ๐ฑ Netherlands | 7.76% | 20.31% | 32.89% |
๐ณ๐จ New Caledonia | 5.% | 11.02% | 31.61% |
๐ณ๐ฟ New Zealand | 9.09% | 16.31% | 33.2% |
๐ณ๐ฎ Nicaragua | 2.71% | 5.29% | 28.92% |
๐ณ๐ช Niger | .92% | 2.4% | 9.76% |
๐ณ๐ฌ Nigeria | 3.% | 2.97% | 12.31% |
๐ณ๐บ Niue | 4.79% | 15.16% | 22.55% |
๐ฐ๐ต North Korea | 2.72% | 11.71% | 30.49% |
๐ฒ๐ฐ North Macedonia | 5.87% | 14.91% | 36.56% |
๐ฒ๐ต Northern Mariana Islands | 2.95% | 10.81% | 32.09% |
๐ณ๐ด Norway | 9.52% | 18.44% | 31.65% |
๐ด๐ฒ Oman | 3.05% | 2.76% | 23.96% |
๐ต๐ฐ Pakistan | 5.48% | 4.27% | 17.23% |
๐ต๐ผ Palau | 8.59% | 9.93% | 21.48% |
๐ต๐ธ Palestine | 4.77% | 3.53% | 23.44% |
๐ต๐ฆ Panama | 3.57% | 8.77% | 30.03% |
๐ต๐ฌ Papua New Guinea | 1.09% | 3.19% | 16.81% |
๐ต๐พ Paraguay | 3.73% | 6.26% | 26.51% |
๐ต๐ช Peru | 3.43% | 8.41% | 30.33% |
๐ต๐ญ Philippines | 3.56% | 5.44% | 23.38% |
๐ต๐ฑ Poland | 5.22% | 18.55% | 35.69% |
๐ต๐น Portugal | 7.% | 22.9% | 36.28% |
๐ต๐ท Puerto Rico | 3.63% | 22.93% | 48.9% |
๐ถ๐ฆ Qatar | 3.5% | 1.52% | 15.01% |
๐ท๐ช Reunion | 3.81% | 13.28% | 32.4% |
๐ท๐ด Romania | 7.16% | 18.64% | 32.22% |
๐ท๐บ Russia | 4.8% | 15.8% | 27.86% |
๐ท๐ผ Rwanda | 2.76% | 3.2% | 17.36% |
๐ง๐ฑ Saint Barthlemy | 7.3% | 10.61% | 43.89% |
๐ธ๐ญ Saint Helena | 8.63% | 28.66% | 32.61% |
๐ฐ๐ณ Saint Kitts and Nevis | 5.36% | 10.13% | 29.79% |
๐ฑ๐จ Saint Lucia | 3.59% | 9.23% | 33.39% |
๐ฒ๐ซ Saint Martin (French part) | 4.47% | 11.14% | 30.08% |
๐ต๐ฒ Saint Pierre and Miquelon | 6.34% | 17.32% | 33.4% |
๐ป๐จ Saint Vincent and the Grenadines | 7.71% | 10.86% | 32.34% |
๐ผ๐ธ Samoa | 2.52% | 5.22% | 18.75% |
๐ธ๐ฒ San Marino | 10.15% | 20.47% | 35.73% |
๐ธ๐น Sao Tome and Principe | 3.92% | 3.76% | 15.6% |
๐ธ๐ฆ Saudi Arabia | 3.32% | 2.81% | 30.28% |
๐ธ๐ณ Senegal | 3.42% | 3.14% | 16.54% |
๐ท๐ธ Serbia | 6.15% | 20.56% | 37.55% |
๐ธ๐จ Seychelles | 10.68% | 8.16% | 28.84% |
๐ธ๐ฑ Sierra Leone | 3.02% | 3.14% | 15.52% |
๐ธ๐ฌ Singapore | 2.29% | 15.12% | 36.51% |
๐ธ๐ฝ Sint Maarten (Dutch part) | 12.03% | 10.57% | 34.51% |
๐ธ๐ฐ Slovakia | 6.63% | 16.98% | 33.4% |
๐ธ๐ฎ Slovenia | 7.52% | 20.96% | 33.59% |
๐ธ๐ง Solomon Islands | 4.03% | 3.47% | 15.29% |
๐ธ๐ด Somalia | 2.6% | 2.57% | 10.75% |
๐ฟ๐ฆ South Africa | 4.06% | 5.89% | 20.55% |
๐ฐ๐ท South Korea | 2.74% | 17.49% | 44.44% |
๐ธ๐ธ South Sudan | 3.48% | 2.89% | 13.11% |
๐ช๐ธ Spain | 7.23% | 20.27% | 38.72% |
๐ฑ๐ฐ Sri Lanka | 8.76% | 11.54% | 35.73% |
๐ธ๐ฉ Sudan | 3.03% | 3.5% | 13.28% |
๐ธ๐ท Suriname | 4.09% | 7.39% | 25.8% |
๐ธ๐ช Sweden | 10.19% | 20.25% | 31.83% |
๐จ๐ญ Switzerland | 9.49% | 19.31% | 32.61% |
๐ธ๐พ Syria | 7.66% | 4.68% | 24.62% |
๐น๐ผ Taiwan | 2.11% | 16.71% | 37.32% |
๐น๐ฏ Tajikistan | 4.34% | 3.47% | 19.43% |
๐น๐ฟ Tanzania | 2.2% | 3.1% | 14.97% |
๐น๐ญ Thailand | 3.21% | 15.21% | 39.17% |
๐น๐ฑ Timor | 3.14% | 5.21% | 25.42% |
๐น๐ฌ Togo | 4.29% | 3.13% | 11.77% |
๐น๐ฐ Tokelau | 4.7% | 8.66% | 25.03% |
๐น๐ด Tonga | 4.6% | 6.22% | 21.65% |
๐น๐น Trinidad and Tobago | 3.93% | 11.52% | 32.67% |
๐น๐ณ Tunisia | 4.4% | 9.02% | 31.24% |
๐น๐ท Turkey | 3.77% | 8.64% | 33.9% |
๐น๐ฒ Turkmenistan | 5.84% | 5.15% | 21.55% |
๐น๐จ Turks and Caicos Islands | 5.79% | 10.34% | 28.25% |
๐น๐ป Tuvalu | 4.98% | 6.48% | 16.15% |
๐บ๐ฌ Uganda | 2.87% | 1.69% | 14.33% |
๐บ๐ฆ Ukraine | 7.54% | 18.81% | 33.2% |
๐ฆ๐ช United Arab Emirates | 3.35% | 1.83% | 15.77% |
๐ฌ๐ง United Kingdom | 10.84% | 19.17% | 32.56% |
๐บ๐ธ United States | 8.18% | 17.13% | 30.47% |
๐ป๐ฎ United States Virgin Islands | 7.54% | 20.42% | 39.11% |
๐บ๐พ Uruguay | 8.23% | 15.58% | 35.98% |
๐บ๐ฟ Uzbekistan | 5.87% | 5.14% | 22.24% |
๐ป๐บ Vanuatu | 5.65% | 3.74% | 16.29% |
๐ป๐ช Venezuela | 2.29% | 8.61% | 27.71% |
๐ป๐ณ Vietnam | 4.13% | 9.12% | 30.02% |
๐ผ๐ซ Wallis and Futuna | 1.76% | 13.47% | 32.98% |
๐ช๐ญ Western Sahara | 2.82% | 5.84% | 23.73% |
๐พ๐ช Yemen | 3.98% | 2.66% | 18.25% |
๐ฟ๐ฒ Zambia | 2.76% | 1.75% | 12.66% |
๐ฟ๐ผ Zimbabwe | 3.18% | 3.32% | 14.22% |
๐ World | 5.13% | 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:
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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