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 the Novel Coronavirus (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:

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 – 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 – Unknown (possibly pangolins) 27,000 (Johns Hopkins University estimate as of 3:00pm PT, Mar 27, 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.





Stats




Covid-19 / Corona novel (animal) virus


updated 28/3/2020


28/3/20 covid-19 global
known cases deaths  % day recovery
600000 27000 4.50% 74.0 95.50%
Existing illness 67%
 28/3/20 covid-19 global
UNknown cases deaths  % day recovery
4,000,000 27000 0.68% 74.0 99.33%


compare to 2009 season flu - Swine Flu
  2009 swine flu
cases deaths  % day
1,000,000,000 27000 0.00% 74.0

Related stats


population Tuberculosis % day
8,000,000,000 10,000,000 0.13% 27397.3
population starvation % day
8,000,000,000 9,000,000 0.11% 24657.5
population fin stress % day
8,000,000,000 500,000 0.01% 1369.9
population %
8,000,000,000 major threat
elderly (60+) 960,000,000 12.00%
serious sick 400,000,000 5.00% 17%
not at risk 83.00%
83% of global population NOT AT RISK of death



FC stats







stat clocks




added 30/03




added 28/3


added 28/3 
world Death clock window below https://www.worldometers.info/
scroll the window to see deaths per year or day




Outcome: Covid-19 

95% of the deaths were underlying illness or elderly / terminal 
the data is not accurate as it has been collated in a rush / best guess / using untested equipment 

Italy reported 30% of test equipment from China failed 
Australia has cases of people turned away from initial test station to later confirm they have corona

The Elderly
90% of the elderly that die from Covid-Con would otherwise die from the Season Flu during the next 9 mths
that will be evidenced by the stats for Season Flu (Globally 500k)
Season Flu 2017 600k  2019 400k  - average is 500k  (google search it)




Crisis of covid-19
1. MS media Hysteria reporting 
2. Financial chaos - stressed families, looting, starvation, 
3. Broken emergency service to elderly and sick dying at home from Hysteria no medicals or care support as those
people have to keep a social distance or in isolation due to contracting the virus























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added 24/3/20 
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new data shows 5G triggers Covid-19








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best fake and Truth on COVID-19 Rebrand of Seasonal Flu 
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