Crowdfight Covid-19 – Call for R-community action

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Dear R-community,

This is a rather unusual post for an R-blog, but unusual times may require that. I am not involved into organizing this effort except for volunteering in the same way I want you to do. So, if you aren’t aware of this initiative yet, please likewise
consider subscribing to Crowdfight Covid-19.

Motivation: Most current plans to fight COVID-19 rely on the assumption that treatments and/or vaccines will be available in a few months. Delays in these treatments will have enormous consequences, both in terms of economic impact and human lives.

Aim: To put the wider scientific community at the service of COVID-19 research. There is now a huge pool of highly skilled scientists, willing to volunteer their time and expertise for this cause. This goes from virologists who don’t have the resources to get directly involved with COVID-19 to researchers in other disciplines (bioinformatics, image analysis, AI…). This is a huge resource, the “bottleneck” being coordination. The team behind the platform tries to remove that bottleneck.

The distribution of tasks has been ongoing for three days now. Among many requests less related to coding, the daily task list also contains some data wrangling and modeling tasks every now and then, and many of us probably have additional spare time right now. Examples thus far have been calls for

    1. Building webscraping tool from scratch, which should help to consolodate government measures that have been put into place across various countries at different points in time,
    2. Support for unit testing and data fetching functionality wrapped around a more domain specific R functionality (biochemistry struff)
    3. Bayesian modeling and corresponding clinical experiment design
    4. Phylogenetic tree analyis of the virus RNA
I cannot share any concrete code snippets or implementation outlines, as the mentioned examples are either not existent yet or within private repositories. 
But it’s free to subscribe, and you can also put an upper bound on your weekly availability.

Published by

Hendrik Thiel

Applied Statistician by training, now working in industry (data science, they call it...)

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