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Visualizing the History of Pandemics

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The History of Pandemics by Death Toll

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)373,000 (Johns Hopkins University estimate as of 9:32am PT, June 1, 2020)

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.

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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Chart of the Week

The Road to Recovery: Which Economies are Reopening?

We look at mobility rates as well as COVID-19 recovery rates for 41 economies, to see which countries are reopening for business.

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The Road to Recovery: Which Economies are Reopening?

COVID-19 has brought the world to a halt—but after months of uncertainty, it seems that the situation is slowly taking a turn for the better.

Today’s chart measures the extent to which 41 major economies are reopening, by plotting two metrics for each country: the mobility rate and the COVID-19 recovery rate:

  1. Mobility Index
    This refers to the change in activity around workplaces, subtracting activity around residences, measured as a percentage deviation from the baseline.

  2. COVID-19 Recovery Rate
    The number of recovered cases in a country is measured as the percentage of total cases.

Data for the first measure comes from Google’s COVID-19 Community Mobility Reports, which relies on aggregated, anonymous location history data from individuals. Note that China does not show up in the graphic as the government bans Google services.

COVID-19 recovery rates rely on values from CoronaTracker, using aggregated information from multiple global and governmental databases such as WHO and CDC.

Reopening Economies, One Step at a Time

In general, the higher the mobility rate, the more economic activity this signifies. In most cases, mobility rate also correlates with a higher rate of recovered people in the population.

Here’s how these countries fare based on the above metrics.

CountryMobility RateRecovery RateTotal CasesTotal Recovered
Argentina-56%31.40%14,7024,617
Australia-41%92.03%7,1506,580
Austria-100%91.93%16,62815,286
Belgium-105%26.92%57,84915,572
Brazil-48%44.02%438,812193,181
Canada-67%52.91%88,51246,831
Chile-110%41.58%86,94336,150
Colombia-73%26.28%25,3666,665
Czechia-29%70.68%9,1406,460
Denmark-93%88.43%11,51210,180
Finland-93%81.57%6,7435,500
France-100%36.08%186,23867,191
Germany-99%89.45%182,452163,200
Greece-32%47.28%2,9061,374
Hong Kong-10%97.00%1,0671,035
Hungary-49%52.31%3,8161,996
India-65%42.88%165,38670,920
Indonesia-77%25.43%24,5386,240
Ireland-79%88.92%24,84122,089
Israel-31%87.00%16,87214,679
Italy-52%64.99%231,732150,604
Japan-33%84.80%16,68314,147
Malaysia-53%80.86%7,6296,169
Mexico-69%69.70%78,02354,383
Netherlands-97%0.01%45,9503
New Zealand-21%98.01%1,5041,474
Norway-100%91.87%8,4117,727
Philippines-87%23.08%15,5883,598
Poland-36%46.27%22,82510,560
Portugal-65%58.99%31,59618,637
Singapore-105%55.02%33,24918,294
South Africa-74%52.44%27,40314,370
South Korea-4%91.15%11,34410,340
Spain-67%69.11%284,986196,958
Sweden-93%13.91%35,7274,971
Switzerland-101%91.90%30,79628,300
Taiwan4%95.24%441420
Thailand-36%96.08%3,0652,945
U.S.-56%28.20%1,768,346498,720
United Kingdom-82%0.05%269,127135
Vietnam15%85.02%327278

Mobility data as of May 21, 2020 (Latest available). COVID-19 case data as of May 29, 2020.

In the main scatterplot visualization, we’ve taken things a step further, assigning these countries into four distinct quadrants:

1. High Mobility, High Recovery

High recovery rates are resulting in lifted restrictions for countries in this quadrant, and people are steadily returning to work.

New Zealand has earned praise for its early and effective pandemic response, allowing it to curtail the total number of cases. This has resulted in a 98% recovery rate, the highest of all countries. After almost 50 days of lockdown, the government is recommending a flexible four-day work week to boost the economy back up.

2. High Mobility, Low Recovery

Despite low COVID-19 related recoveries, mobility rates of countries in this quadrant remain higher than average. Some countries have loosened lockdown measures, while others did not have strict measures in place to begin with.

Brazil is an interesting case study to consider here. After deferring lockdown decisions to state and local levels, the country is now averaging the highest number of daily cases out of any country. On May 28th, for example, the country had 24,151 new cases and 1,067 new deaths.

3. Low Mobility, High Recovery

Countries in this quadrant are playing it safe, and holding off on reopening their economies until the population has fully recovered.

Italy, the once-epicenter for the crisis in Europe is understandably wary of cases rising back up to critical levels. As a result, it has opted to keep its activity to a minimum to try and boost the 65% recovery rate, even as it slowly emerges from over 10 weeks of lockdown.

4. Low Mobility, Low Recovery

Last but not least, people in these countries are cautiously remaining indoors as their governments continue to work on crisis response.

With a low 0.05% recovery rate, the United Kingdom has no immediate plans to reopen. A two-week lag time in reporting discharged patients from NHS services may also be contributing to this low number. Although new cases are leveling off, the country has the highest coronavirus-caused death toll across Europe.

The U.S. also sits in this quadrant with over 1.7 million cases and counting. Recently, some states have opted to ease restrictions on social and business activity, which could potentially result in case numbers climbing back up.

Over in Sweden, a controversial herd immunity strategy meant that the country continued business as usual amid the rest of Europe’s heightened regulations. Sweden’s COVID-19 recovery rate sits at only 13.9%, and the country’s -93% mobility rate implies that people have been taking their own precautions.

COVID-19’s Impact on the Future

It’s important to note that a “second wave” of new cases could upend plans to reopen economies. As countries reckon with these competing risks of health and economic activity, there is no clear answer around the right path to take.

COVID-19 is a catalyst for an entirely different future, but interestingly, it’s one that has been in the works for a while.

Without being melodramatic, COVID-19 is like the last nail in the coffin of globalization…The 2008-2009 crisis gave globalization a big hit, as did Brexit, as did the U.S.-China trade war, but COVID is taking it to a new level.

Carmen Reinhart, incoming Chief Economist for the World Bank

Will there be any chance of returning to “normal” as we know it?

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Charting the Rise and Fall of the Global Luxury Goods Market

This infographic charts the rise and fall of the $308 billion global personal luxury market, and explores what the coming year holds for its growth

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The Rise and Fall of the Global Luxury Goods Market

Global demand for personal luxury goods has been steadily increasing for decades, resulting in an industry worth $308 billion in 2019.

However, the insatiable desire for consumers to own nice things was suddenly interrupted by the coming of COVID-19, and experts are predicting a brutal contraction of up to one-third of the current luxury good market size this year.

Will the industry bounce back? Or will it return as something noticeably different?

A Once Promising Trajectory

The global luxury goods market—which includes beauty, apparel, and accessories—has compounded at a 6% pace since the 1990s.

Recent years of growth in the personal luxury goods market can be mostly attributed to Chinese consumers. This geographic market accounted for 90% of total sales growth in 2019, followed by the Europe and the Americas.

Analysts suggest that China’s younger luxury goods consumers in particular have significant spending power, with an average spend of $6,000 (¥41,000) per person in pre-COVID times.

An Industry Now in Distress

The lethal combination of reduced foot traffic and decreased consumer spending in the first quarter of 2020 has brought the retail industry to its knees.

In fact, more than 80% of fashion and luxury players will experience financial distress as a result of extended store closures.

luxury market McKinsey supplemental

With iconic luxury retailers such as Neiman Marcus filing for bankruptcy, the pressure on the luxury industry is clear. It should be noted however, that companies who were experiencing distress before the COVID-19 outbreak will be the hardest hit.

Predicting the Collapse

In a recent report, Bain & Company estimated a 25% to 30% global luxury market contraction for the first quarter of 2020 based on several economic variables. They have also modeled three scenarios to predict the performance for the remainder of 2020.

  • Optimistic scenario: A limited market contraction of 15% to 18%, assuming increased consumer demand for the second and third quarter of the year, roughly equating to a sales decline of $46 billion to $56 billion.
  • Intermediate scenario: A moderate market contraction of between 22% and 25%, or $68 to $77 billion.
  • Worst-case scenario: A steep contraction of between 30% and 35%, equating to $92 billion to $108 billion. This assumes a longer period of sales decline.

Although there are signs of recovery in China, the industry is not expected to fully return to 2019 levels until 2022 at the earliest. By that stage, the industry could have transformed entirely.

Changing Consumer Mindsets

Since the beginning of the pandemic, one-quarter of consumers have delayed purchasing luxury items. In fact, a portion of those who have delayed purchasing luxury goods are now considering entirely new avenues, such as seeking out cheaper alternatives.

However, most people surveyed claim that they will postpone buying luxury items until they can get a better deal on price.

luxury market supplemental

This frugal mindset could spark an interesting behavioral shift, and set the stage for a new category to emerge from the ashes—the second-hand luxury market.

Numerous sources claim that pre-owned luxury could in fact overtake the traditional luxury market, and the pandemic economy could very well be a tipping point.

The Future of Luxury

Medium-term market growth could be driven by a number of factors, from a global growing middle class and their demand for luxury products, as well as retailers’ sudden shift to e-commerce.

While analysts can only rely on predictions to determine the future of personal luxury, it is clear that the industry is at a crossroads.

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