Here's a very quick summary of what I linked above: In Israel it would be easy to look at the data and conclude that vaccines are providing ~67% efficacy against severe disease/death.
But, once the data is broken down into buckets that help address confounding variables (i.e. different vaccination rates among different age groups), things look very different. All of a sudden efficacy numbers are looking better than 90% for a lot of people.
This will similarly matter a great deal as people try to figure out how long vaccines provide protection. The groups that got vaccinated the earliest in many places were older people and health care workers -- groups which start out at higher risk, and also have a higher probability of less effective immune response to vaccines (older people).
As a result of that, it will be easy for analysts that don't consider that issue to under-estimate the effective time period of vaccines.
The archive.is link you provided isn't working for me at the moment, but to address your statement in the context of the above framework:
The group of people most likely to have been infected with the virus are not the same as the group of people most likely to have antibodies as a result of immunization. In many places, there are a lot more younger people who have gotten infected with the disease than older people. There are other socioeconomic and behavioural differences too.
Given that young people tend to have a more effective immune responses to begin with, and given that they have been shown to have better outcomes after being infected with this virus, it's easy to see a way to incorrectly conclude that stronger immunity results from infection-acquired antibodies, even if the opposite may be true.
In short: Apparent differences may be better explained by the fact that it's a different group of people who have been infected vs those who have not been infected.
For a little bit of ancient history: I was one of the admins who worked to create OFTC. We all knew each other from Open Projects Network (which rebranded as Freenode).
I was barely in high school when I came up with the name OFTC and I registered OFTC.net. Very early on in the process of creating OFTC, I agreed with all of the people I was creating OFTC with that I would behave as caretaker rather than owner of OFTC.net while we figured out our governance.
Ultimately we came up with a governance model, and we also managed to convince Software in the Public Interest to take custody of the domain name and have it managed in accordance with the governance model we designed.
We started with a pretty great group of both capable and well-intended people, and one of the things we figured out was that if OFTC was going to be a sustainable project, it needed more sustainable governance than the project we were leaving.
One of the key people behind the very early push for OFTC to have a stable governance model later became a Member of Parliament here in Canada.
With homage Moxie's Cryptographic Doom Principle, I propose the Cache Doom Principle: If a system's behaviour can be influenced by a cache, eventually someone will figure out a way to use that cache to leak data.
(3) Chrome is migrating to using it's own store: "Historically, Chrome has integrated with the Root Store provided by the platform on which it is running. Chrome is in the process of transitioning certificate verification to use a common implementation on all platforms where it's under application control, namely Android, Chrome OS, Linux, Windows, and macOS. Apple policies prevent the Chrome Root Store and verifier from being used on Chrome for iOS."
There's a really big gap between the $0.01/gb you are talking about being charged on droplets and the $0.10/gb that DigitalOcean is using on newer offerings like this and "App Platform".
The fact that somebody could put a caching proxy in front of the container registry -- on a droplet also hosted at DigitalOcean -- and have their bandwidth costs fall 10x for doing that does indeed provide further illustration of the absurdity of DigitalOcean's new approach to bandwidth pricing.
There are many CDNs that make money charging < $0.01/gb.
Indeed DigitalOcean themselves built their place in the market by charging $0.01/gb for bandwidth. How do we reasonably get to $0.10 as is the case here?
If it were really that expensive for them they could outsource it to a CDN for well under $0.01/gb at their scale, which would leave them the ability to get margin. But all of this pricing is in fact completely detached from the underlying physical realities -- they are charging these prices because they think they can get away with it, not because they need to do so to cover costs and have some margin.
Bandwidth prices shouldn't be going up, indeed they should be going down. 100 gigabit interconnects are a thing now.
sigh. DigitalOcean continues their march towards irrelevance.
First it was the app platform and now this. Gouging us at $0.10/gigabyte bandwidth charges makes us: (1) think less of you, and (2) adds a bunch of cognitive complexity & work to developers' lives.
If this is how it's going to be we may as well just use AWS or move on to one of your competitors that isn't trying to pretend that bandwidth is expensive. It isn't, and there isn't any reason we should have to design applications around artificially absurdly inflated costs.
Even Oracle pretends to understand this. _ORACLE_ are the ones trying to make the case that they aren't only about having hostages/locked in customers.
When Oracle is beating you on this metric you've really jumped the shark.
The .com zone file is updated every few minutes. Caching behaviours will vary significantly. Frequently a significant fraction of traffic can be using new nameservers within minutes, with a long tail of traffic with older information.
Each TLD does their own thing. For example, last time I checked, .ca only seemed to be serving a new zone file every few hours. How long new nameservers take will depend on your luck in terms of where you are in their refresh cycle.
It does seem to use S3 behind the scenes based on URLs I've seen. The data loss incidents I've seen reported have tended to be after outages. Amazon Cloud Drive seems to keep an index mapping amazon cloud drive filenames to S3 objects, I suspect the index entry was corrupted/lost/rolled back. While the object likely still existed in S3 somewhere, that doesn't do much if users don't any way of accessing it.
Some of the supported providers (e.g. Amazon Cloud Drive) have a reputation for days-long service outages. Some users of Amazon Cloud Drive have even reported files going missing on occasion.
But the great thing with git-annex is you can have your data on multiple clouds (in addition to being on your own equipment), so partial or complete loss of a cloud provider does not need to result in availability or durability issues.
But, once the data is broken down into buckets that help address confounding variables (i.e. different vaccination rates among different age groups), things look very different. All of a sudden efficacy numbers are looking better than 90% for a lot of people.
This will similarly matter a great deal as people try to figure out how long vaccines provide protection. The groups that got vaccinated the earliest in many places were older people and health care workers -- groups which start out at higher risk, and also have a higher probability of less effective immune response to vaccines (older people).
As a result of that, it will be easy for analysts that don't consider that issue to under-estimate the effective time period of vaccines.
The archive.is link you provided isn't working for me at the moment, but to address your statement in the context of the above framework:
The group of people most likely to have been infected with the virus are not the same as the group of people most likely to have antibodies as a result of immunization. In many places, there are a lot more younger people who have gotten infected with the disease than older people. There are other socioeconomic and behavioural differences too.
Given that young people tend to have a more effective immune responses to begin with, and given that they have been shown to have better outcomes after being infected with this virus, it's easy to see a way to incorrectly conclude that stronger immunity results from infection-acquired antibodies, even if the opposite may be true.
In short: Apparent differences may be better explained by the fact that it's a different group of people who have been infected vs those who have not been infected.