5 ms·
Does anyone know of any good, publicly accessible case data (for any country)? E.g. for each case, date of detection, age of patient, ongoing|recovery date
by patrec 7y ago
Does anyone know of any good, publicly accessible case data (for any country)?
E.g. for each case,
date of detection, age of patient, ongoing|recovery date|date of death
- DataDrivenMD 7y agoThe best and closest to what you’re looking for comes from Johns Hopkins: - https://data.humdata.org/dataset/novel-coronavirus-2019-ncov-cases https://data.humdata.org/dataset/novel-coronavirus-2019-ncov... The GitHub repo with datasets: - https://github.com/CSSEGISandData/COVID-19 https://github.com/CSSEGISandData/COVID-19 Start there, and reach out to the staff if you’re looking for something more specific. They may be able to point you in the right direction.
- patrec 7y agoYeah, I'm aware of the JHU dataset. Unfortunately working out useful CFRs from that is not easy. You need to be able to figure out infected_at_t_and_dead/(infected_at_t_and_recovered+infected_at_t_and_dead) for some time t sufficiently in the past so that basically everyone falls into these two categories. And if you want to draw transferable conclusions you also need an interval where treatment conditions were relatively uniform (e.g. already completely overwhelmed health system, or health system that could cope, throughout). As well as an age breakdown of recovered and dead. The data from Italy does not look promising, they have an old population but seem to have reacted well and still have capacity to treat people. And yet CFR seems 3.8%, without excluding people who are ongoing and will die in the next days and weeks. It would be very interesting to have a more detailed comparison with the South Korean outbreak, where again reaction has been very good as well and we could look at a subset of people for whom we have no undetected cases, so very good estimates ought to be possible.
- Kliment 7y agoThere is some good data on 1100 early cases in China. See https://www.nejm.org/doi/full/10.1056/NEJMoa2002032 https://www.nejm.org/doi/full/10.1056/NEJMoa2002032
- patrec 7y agoThanks! The ratio of CT abnormalities and proportion of severe cases in young-ish patients in that one is scary. 40% of people in 14-49 age bracket were classed as severe cases.
- deleted 7y ago[deleted]
- akg_67 7y agoTry This page from Hokkaido government in Japan. You should be able to extract relevant data from the table and pdf using a translator. http://www.pref.hokkaido.lg.jp/hf/kth/kak/hasseijoukyou.htm http://www.pref.hokkaido.lg.jp/hf/kth/kak/hasseijoukyou.htm Table shows quite a bit of data about each case including age, gender, location, any link discovered to other patients and status. The pdf shows additional data on when they had fever and other symptoms, when they went to different medical facilities and when they were confirmed as infected.
- Maxious 7y agoThis kind of data is called a "line list". There's two good ones from Harvard and University of Washington "BeOutbreakPrepared" linked on https://nssac.github.io/covid-19/covid-19_imported_cases/ https://nssac.github.io/covid-19/covid-19_imported_cases/
- patrec 7y agoThanks a lot for teaching me the right term and linking this data set!
- zekrioca 7y agoSweden, for e.g.: https://www.thelocal.se/20200304/who-are-the-coronavirus-patients-in-sweden https://www.thelocal.se/20200304/who-are-the-coronavirus-pat...