R ecosystem package coronavirus

Dr Rami Krispin of the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) has just released the R package coronavirus, which “provides a daily summary of the Coronavirus (COVID-19) cases by state/province“, caused by 2019-nCoV.

(update 2020-03-12 1337 EDT)

I have noticed that the data in the R package cited above seriously lags the data directly available at the Github site. So if you want current data, go to the latter source.

There is also an open source article in Lancet about the capability.

Estimating mortality rate

(update 2020-03-08, 15:57 EDT)

There’s a lot of good quantitative epidemiological work being done in and around the 2019-nCoV outbreak. I was drawn to this report by Professor Andrew Gelman, one of the co-authors of STAN, but the primary work was done by Dr Julien Riou and colleagues in a pre-print paper at medR\chiiv.

There’ll probably be a good deal more once people have some time to get into case data. I’ll keep this post updated with interesting ones I find.

(update 2020-03-12, 11:37 EDT)

New compilation site by Avi Schiffmann, a budding data scientist.

(update 2020-03-12-13:26 EDT)

The Johns Hopkins data are also accessible from their at their Github site. These are updated every five minutes. And it is cloned in many places.

There is alternative source available and online, and having data last dated from 11 March 2020, yesterday, from many contributors (list available online). This source’s map has much finer spatial resolution.

(update 2020-03-13, 11:49 EDT)

The New England Journal of Medicine has a full page with links about and concerning the Coronavirus (SARS-CoV-2) causing Covid-19, and it is fully open access.

Science magazine this week features four SARS-CoV-2-related articles:



(Above from Wrapp, Wang, et al, Science, p. 1260, 2020)
(update 2020-03-13, 12:41 EDT)


About ecoquant

See https://wordpress.com/view/667-per-cm.net/ Retired data scientist and statistician. Now working projects in quantitative ecology and, specifically, phenology of Bryophyta and technical methods for their study.
This entry was posted in data presentation, data science, epidemiology. Bookmark the permalink.

1 Response to R ecosystem package coronavirus

  1. Pingback: New COVID-19 incidence in the United States as AR(1) processes | hypergeometric

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