Datastream
Visualized: the World’s Deadliest Pandemics by Population Impact
The Briefing
- As of May 27, 2021, COVID has claimed the lives of almost 3.5 million people worldwide
- That’s 0.04% of the global population
- We’ll be updating this graphic as the current pandemic continues
Visualizing the World’s Deadliest Pandemics
Humanity has been battling against disease for centuries.
And while most contagious outbreaks have never reached full-blown pandemic status, there have been several times throughout history when a disease has caused mass devastation.
Here’s a look at the world’s deadliest pandemics to date, viewed from the lens of the impact they had on the global population at the time.
Editor’s note: The above graphic was created in response to a popular request from users after viewing our popular history of pandemics infographic initially released a year ago.
Death Toll, by Percent of Population
In the mid-1300s, a plague known as the Black Death claimed the lives of roughly 200 million people—more than 50% of the global population at that time.
Here’s how the death toll by population stacks up for other significant pandemics, including COVID-19 so far.
| Pandemic | Death Toll by % of Population | Year of Population Estimate |
|---|---|---|
| Black Death | 51.0% | 1300 |
| Plague of Justinian | 19.1% | 500 |
| Smallpox | 12.1% | 1500 |
| Antonine Plague | 2.6% | 200 |
| Spanish Flu | 2.5% | 1919 |
| The Third Plague | 1.0% | 1850 |
| HIV/AIDS | 0.7% | 1981 |
| COVID-19 | 0.04% | 2021 (as of May 27) |
The specific cause of the Black Death is still up for debate. Many experts claim the 14th-century pandemic was caused by a bubonic plague, meaning there was no human-to-human transmission, while others argue it was possibly pneumonic.
Interestingly, the plague still exists today—however, it’s significantly less deadly, thanks to modern antibiotics.
History Repeats, But at Least We Keep Learning
While we clearly haven’t eradicated infection diseases from our lives entirely, we’ve at least come a long way in our understanding of what causes illness in the first place.
In ancient times, people believed gods and spirits caused diseases and widespread destruction. But by the 19th century, a scientist named Louis Pasteur (based on findings by Robert Koch) discovered germ theory—the idea that small organisms caused disease.
What will we discover next, and how will it impact our response to disease in the future?
»Like this? Check out our full-length article The History of Pandemics
Where does this data come from?
Source:CDC, WHO, Johns Hopkins University, Encyclopedia Britannica, Historical Records
Notes: Many of the death toll numbers are best estimates based on available research. Some, such as the Plague of Justinian, are subject to debate based on new evidence
Datastream
Will Connected Cars Break the Internet?
By 2025, connected cars could produce 10 exabytes (exabyte = 1B gigabytes) of data per month, a thousand-fold increase over current volumes.
The Briefing
- Connected cars could be producing up to 10 exabytes of data per month, a thousand-fold increase over current data volumes.
- This has serious implications for policymakers, manufacturers, and local network infrastructure.
Modern connected cars are more like computers on wheels, when compared to the dumb cars that dominated the twentieth century.
Today’s connected cars come stocked with as many as 200 onboard sensors, tracking everything from engine temperature to seatbelt status. And all those sensors create reams of data, which will increase exponentially as the autonomous driving revolution gathers pace.
With carmakers planning on uploading 50-70% of that data, this has serious implications for policymakers, manufacturers, and local network infrastructure.
In this visualization from our sponsor Global X ETFs, we ask the question: will connected cars break the internet?
Data is a Plural Noun
Just how much data could it possibly be?
There are lots of estimates out there, from as much as 450 TB per day for robotaxis, to as little as 0.383 TB per hour for a minimally connected car. This visualization adds up the outputs from sensors found in a typical connected car of the future, with at least some self-driving capabilities.
The focus is on the kinds of sensors that an automated vehicle might use, because these are the data hogs. Sensors like the one that turns on your check-oil-light probably doesn’t produce that much data. But a 4K camera at 30 frames a second, on the other hand, produces 5.4 TB per hour.
| Sensor | Sensors per Vehicle | Data Produced |
|---|---|---|
| RADAR | 4-6 | 0.1-15 Mbit/s/sensor |
| LiDAR | 1-5 | 20-100 Mbit/s/sensor |
| Camera | 6-12 | 500-3,500 Mbit/s/sensor |
| Ultrasonic | 8-16 | <0.01 Mbit/s/sensor |
| Vehicle Motion, GNSS/GPS, IMU | n/a | <0.1 Mbit/s |
| Total Data | 3-40 Gbit/s/vehicle | |
All together, you could have somewhere between 1.4 TB and 19 TB per hour. Given that U.S. drivers spend 17,600 minutes driving per year, a vehicle could produce between 380 and 5,100 TB every year.
To put that upper range into perspective, the largest commercially available computer storage—the 100 TB SSD Exadrive from Nimbus—would be full in 5 hours. A standard Blu-ray disc (50 GB) would be full in under 2 seconds.
Lag is a Drag
The problem is twofold. In the first place, the internet is better at downloading than uploading. And this makes sense when you think about it. How often are you uploading a video, versus downloading or streaming one?
Average global mobile download speeds were 30.78 MB/s in July 2022, against 8.55 MB/s for uploads. Fixed broadband is much higher of course, but no one is suggesting that you connect really, really long network cables to moving vehicles.
Ultimately, there isn’t enough bandwidth to go around. Consider the types of data traffic that a connected car could produce:
- Vehicle-to-vehicle (V2V)
- Vehicle-to-grid (V2G)
- Vehicles-to-people (V2P)
- Vehicles-to-infrastructure (V2I)
- Vehicles-to-everything (V2E)
The network just won’t be able to handle it.
Moreover, lag needs to be relatively non-existent for roads to be safe. If a traffic camera detects that another car has run a red light and is about to t-bone you, that message needs to get to you right now, not in a few seconds.
Full to the Gunwales
The second problem is storage. Just where is all this data supposed to go? In 2021, total global data storage capacity was 8 zettabytes (ZB) and is set to double to 16 ZB by 2025.
One study predicted that connected cars could be producing up to 10 exabytes per month, a thousand-fold increase over current data volumes.
At that rate, 8 ZB will be full in 2.2 years, which seems like a long time until you consider that we still need a place to put the rest of our data too.
At the Bleeding Edge
Fortunately, not all of that data needs to be uploaded. As already noted, automakers are only interested in uploading some of that. Also, privacy legislation in some jurisdictions may not allow highly personal data, like a car’s exact location, to be shared with manufacturers.
Uploading could also move to off-peak hours to even out demand on network infrastructure. Plug in your EV at the end of the day to charge, and upload data in the evening, when network traffic is down. This would be good for maintenance logs, but less useful for the kind of real-time data discussed above.
For that, Edge Computing could hold the answer. The Automotive Edge Computing Consortium has a plan for a next generation network based on distributed computing on localized networks. Storage and computing resources stay closer to the data source—the connected car—to improve response times and reduce bandwidth loads.
Invest in the Future of Road Transport
By 2030, 95% of new vehicles sold will be connected vehicles, up from 50% today, and companies are racing to meet the challenge, creating investing opportunities.
Learn more about the Global X Autonomous & Electric Vehicles ETF (DRIV). It provides exposure to companies involved in the development of autonomous vehicles, EVs, and EV components and materials.
And be sure to read about how experiential technologies like Edge Computing are driving change in road transport in Charting Disruption. This joint report by Global X ETFs and the Wall Street Journal is also available as a downloadable PDF.
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