The implementation of the UK Covid-19 dashboard

It's funny to read about a dashboard with TBs of memory and distributed DBs when on HN, people pride themselves on getting Web servers to run on floppy disk based systems.

Joking aside, I liked the description of the dashboard, and generally speaking the UK's government Web sites are better quality, support open data more, are easier to read and navigate than other European countries from what I have seen. This includes this dashboard, which looks clean, simple and functional.

I was waiting for the big SQL Server advertising language and positively suprised that the article is very tech agnostic. I did all seem to be rather over-engineered, but Microsoft needs to make some money and government agencies don't generally have wizards from HN working for them, so I can live with an occasionally over-engineered system as long as important systems are working and remain up.

The most mysterious part for me was why one would put JSON inside relational tables?

Yes, I thought the same thing in finding it easier on my eyes/quick perception of the site.

I do think the UK and some other countries do a better job of presenting data compared to the CDC.

It's pretty much agreed that the rate of unvaccinated people vs. vaccinated people winding up in hospital beds is several times higher, however, all the CDC data presented is only rates. I want tallies or counts, and I cannot find them. For instance, on Ontario, Candada's site[1], the vaccinated are 74% vs. the unvaccinated's 26% of COVID hospitalizations. Most non-technical people think the hospitalizations of COVID patients is like over 90%. It's because more and more people are vaccinated, even with a lower rate of hospitalizations, the numbers are higher. Also, it's interesting to see on the Ontario site that COVID hospitalizations consist of 56% directly for COVID, and 44% were admitted for other reasons and then tested positive for COVID once hospitalized. The case is more telling for ICU with 81% admitted for COVID, and 19% for other reasons.

I am trying to play with raw data more for refreshing my munging skills than making a point or fodder to add to the COVID noise. I have been coding since 1978, played with neural nets, GAs, and GP in the late 1980s, but I don't code or do data analysis for a living right now (other than buisness strategy reports that require some basic analysis). There's a lot of data out there, and it can get very confusing. I am back to using R/RStudio from a brief stint using Julia/Pluto notebooks and previously using Python/Jupyter notebooks. I even did a toy DSEIR model in J back in April 2020 based on previous work by a couple of people, which I plan on updating to April[2]. I am going to try and do some Lisp work, and I think I will settle on RStudio and Lisp for more genomic/bioinformatic stuff (yes, I know biolisp has been supplanted by python, however, Lisp is having a renaissance in symbolic-related areas of ML again like NLP). BTW, in what language was GPT implemented, not API languages, but what PL(s) was used to create the code - C++, Java, Go?

I may be bad at navigating the CDC website, but I can't seem to get the dataset of numbers of hospitalizations by vaccination status, only rates or pre-filtered data. I do remember downloading raw data that seemed to have it (over 1.8gb, I think), but I can't seem to find it. I'd appreciate a link if anyone has it.

[1] https://covid-19.ontario.ca/data/hospitalizations#hospitaliz...

[2] https://github.com/phantomics/april

It definitely had a bit of a marketing tone, but it was focused on what's ultimately an open source product you can run pretty much anywhere, from a different cloud provider to your own bare metal, they just happened to use it on Azure.

Microsoft didn't build this project, they just host it.

It's built in-house by the government.