Thanks for sharing! I have been building a collection of useful statistics links for Covid-19. This singaporean one takes the cake for detail - a case by case breakdown and network graph, amazing!

Here are some nice resources I've come across: Obligatory global john hopkins/arcgis: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.h...

Another global map, but with different stats: https://thewuhanvirus.com/

A detailed frequency table with sources: https://bnonews.com/index.php/2020/02/the-latest-coronavirus...

A japan dashboard: https://covid19japan.com/

Nextstrain has a bioinformatics overview here: https://nextstrain.org/ncov

We should really applaud Singapore Govt. here. I don't think any other place has handled the situation so well and so transparent.

P.S I live in Singapore. Ask me anything

Looking at the URL here. Wasn't the whole point of naming it COVID-19 to not have it relate to / blamed on a geographic location.

Calling it the Wuhan Virus is not great.

Is there anything similar for South Korea?

I found something interesting about South Korea. According to Worldometers South Korea have tested a lot more people than anyone else - see https://www.worldometers.info/coronavirus/covid-19-testing/

Then if you look at the Country breakdown here https://www.worldometers.info/coronavirus/ (scroll down a bit) South Korea has 5,186 confirmed cases but only 27 are listed as Serious or Critical. This seems to go against the '20% need hospital treatment' narrative and would support the theory that there are a lot of mild cases going undetected (as SK has tested more widely than any other country).

But ... I can't find a source for that '27' Serious or Critical number.

A good dashboard in HK https://wars.vote4.hk/en/

Wish they listed the total number of people tested so far though. Since I think that's a statistic that is important to properly interpret the number of cases.

I really like the network graph showing relationships between clusters and patients

Interesting tech stack.

Erlang + Ruby?

https://i.imgur.com/BZWiC0p.png

I wonder how accurate this Wappalyzer [1] is?

[1] https://www.wappalyzer.com/

I'm really curious how the weather plays an aspect here. Singapore being on the equator

The ONLY dashboard in the world showing Age, Gender & Nationality Distribution.

Surprisingly, Singapore has lots of Indians but I don't see Indians in Singapore who got this virus. And no report of India being affected either. What gives?