Ethernity is proud to provide a general sales report from our first month of aNFT (“authenticated NFT) drops. Total sales: $2,493,771 with 2.5% of the total going to charity. Today, Ethernity is announcing we will be performing an ERN buyback as promised upon launch.

RECAP:

The Ethernity team is hard at work ready to launch a large amount of licensed IPs in upcoming aNFT drops and multipacks. This widely distributed team including crypto natives and advisors teamed up with leading figures in the fields of sports, arts, entertainment, music, movies, gaming, tech, collectibles and more to forge an authenticated, licensed, rights-driven aNFT platform and marketplace producing highly curated quality aNFT collections to drive long term value.

The first community drop rewarded early ERN adopters with an aNFT from the acclaimed digital artist Boss Logic. Then, we opened our marketplace with a statement piece celebrating creators with the Welcome to the Internet aNFT by Jason Heuser. Next, we launched our first real-world collectible; the Fernando Tatis Jr. bat. This past week we released the legendary Muhammad Ali series honoring history while looking towards the future. This next quarter will see legendary figures, present icons, and future stars mint exclusive aNFTs with Ethernity. And, get ready for some major surprises as we continue to innovate what NFTs can be and what the industry can become both culturally and technologically while rewarding its community members and users.

BUYBACK:

Speaking of, Ethernity previously announced that we will be locking 75% of all profits into our ERN vault. How? We will be buying back the ERN token from the circulating supply and locking it for 2 years. And, we’re proud to announce that officially begins today. We’ll be providing the wallet details to make the process as transparent as possible and our community will be able to track its holdings. It’s a true testament to the open source and transparent nature of blockchain and a commitment to our community.

SALES FIGURES:

Drop #0: BOSSLOGIC

Total Sales: 525.556 ETH / $946,000

Ethernity Profits: 35% / $331,100

2.5% to Oxygen Seven Reforestation

NFTs reserved for Stone holders & ePacks : 500

Drop #1: Welcome to the Internet — Jason Heuser

Total Sales: 20,194 ERN / $605,820.00

Ethernity Profit: 20% / $121,164

2.5% to Global Wildlife Conservation

NFTs reserved for Stone holders & ePacks : TBA

Drop #2: Fernando Tatis Jr.-Impossible Brief

Total Sales: $382,566

Ethernity Profit: 10% / $38,256

2.5% Binance Charitable Foundation

NFTs reserved for Stone holders & ePacks : TBA

Drop #3: Muhammad Ali-Raf Grasseti

Total Sales: $559,385

Ethernity Profit: 10% Ethernity / $55,938

2.5% to Muhammad Ali Foundation

NFTs reserved for Stone holders & ePacks : TBA

TOTAL SALES: $2,493,771

TOTAL PROFITS: $546,458

ERN BUYBACK (75%): $409,843 in ERN 🏦

BUY-BACK WALLET: TBR

BUY-BACK SMART CONTRACT ADDRESS : TBR

*There has not been a buyback yet, we will announce the exact start of the buyback on our Ethernity Twitter. Any such announcements claiming to have done so are false.” 🏦

LOOKING AHEAD: 💎

It’s official — 75% of all profits from aNFT sales will be buying ERN and locked for 2 years. So, what’s next? With that firm commitment to our long-term vision intact, Ethernity will now be focusing on rolling out many of our planned innovative product offerings — like “multipacks,” AR unlockables, and virtual world integrations. Even more important, we’ll be rewarding our “Stones” holders with a robust program at the end of the month — providing exclusive access to “Stones” holders to aNFTs retail buyers cannot. And more. Stay tuned to see what’s next in store for Ethernity.

Ethernity Chain Links:

https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411622&authkey=b4a0c5bc-471f-4410-ad2a-0c4f88afa5de

A year ago, At the time, this was a minor side-project I could do in the extra time I had saved because I was working from home during lockdown and no longer had a 1.5-hour commute twice a day. It was a fascinating, complex problem, but also relatively easy to attempt to answer based on current best evidence at the time, because that consisted of only a few dozen scientific papers and preprints.
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411623&authkey=f37524b6-c168-426b-a691-79855a18f89b

12 months on, and instead of a small side-project, the question has become something I spend most of my free time on. I’ve put in endless hours and late nights into trying to answer what at first seems like a very simple question: how likely are you to die if you catch COVID-19? In the process, I’ve published — with some amazing colleagues — two scientific papers on the question that have jointly been read 100,000s of times, cited by the CDC, WHO, EU, and others, and generally dedicated a very surprising amount of time to the whole idea.
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411629&authkey=705937bb-8b2c-433c-9076-98dbe9e09283

So, a year on, let’s look at the question of the fatality rate of COVID-19, and what we’ve learned.
Population Fatality Rates
The problem in March/April 2020 was an interesting one. While we already knew that COVID-19 was dangerous — it could overwhelm healthcare systems in a bad outbreak — there was still a lot of uncertainty. We knew that the case fatality rate, which is simply the number of deaths divided by confirmed cases, likely overestimated the true fatality risk, but we didn’t really have much information on the infection fatality rate (IFR), because we didn’t know how many people had been infected with SARS-CoV-2. While the evidence on asymptomatic spread was already accumulating, testing was sparse and so estimating exactly how many people had already had COVID-19 was very hard.
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411632&authkey=a9eff806-2d6b-456f-9978-f90cc393ff19

In our initial study, we looked at something simple — based on the number of people who were estimated to have caught COVID-19 and died of it across a range of places, the aggregate IFR overall. At this point, research was pretty thin on the ground, so we looked both at people who had modelled what they thought was the likely fatality rate of COVID-19 as well as using antibody studies to infer infection rates and from those IFRs.
From these varied estimates, we produced an aggregate figure that the population IFR at the time was around 0.68% — or about 1 in 150 people who caught the disease died of it — and varied in the studies we examined between a low of 0.17% to a high of 1.7%. We also acknowledged that there was probably no ‘true’ IFR for the disease, that the number varied across populations, and in particular noted that there was growing evidence that the IFR was likely to vary based on the age-breakdown of who got infected in a population.
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411643&authkey=a511eee1-d26b-4014-b9f4-3344e8d547ec

 

In other words, based on the data we had at the time (we submitted the paper at the end of June 2020), the populations with IFR estimates seemed to lie somewhere between these values. But, importantly, it looked like age might be the biggest factor.
Fortunately, people were already working on the problem, and shortly after our first paper was published I was invited to join the effort to look at the age-stratified IFR of COVID-19. I happily accepted, bidding free time goodbye for another few months.
So what did we find?
Age-Stratified IFR
The second paper, with a bigger team including professors from Dartmouth and Harvard, and was also a bit more complex. Because the growth rate of COVID-19 scientific papers is exponential, we had a lot more data on our hands when we systematically reviewed the databases. That being said, there were far fewer places that gave good estimates of the infection rates of COVID-19 by age, which was the biggest thing we needed in a paper. Moreover, the death data was hard to trust for a lot of locations, so we limited the study only to higher-income areas where we could be reasonably sure the numbers were correct.
After aggregating more than 100 datapoints from studies across the globe, we ended up with this somewhat amazing graph.

What this is showing is that COVID-19 death rates by age adhere almost perfectly to a log scale. In other words, there is an impressively robust exponential association between your age and your risk of death from COVID-19 — a 20 year old has a 1 in 17,000 IFR if they catch the disease, while a 60 year old is closer to 1 in 130. You can see this even more clearly in the graph using a linear scale.

https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411644&authkey=e8f779f4-f1f7-42ac-b2af-2c6ccd8b5b67
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411645&authkey=cd33a1f9-4229-4969-aa4e-81433ec589d0
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411646&authkey=ef9a209b-8fa8-4e27-9a3d-2caf034c263c
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411648&authkey=0e3f8f63-4805-4db5-aa2d-e7a12c0ec278
https://laserfiche.ou.edu/Forms/handlers/downloadattachment.ashx?req=DownLoad&aid=411649&authkey=44cb03d0-4318-40b2-9f6c-340ca1ec3dfc
https://myanimelist.net/blog.php?eid=852936