A thread to share [collections of] resources, curriculum ideas, etc. about and for during the COVID-19 epidemic
Lots of analyses, some data, some helpful contributions, lots of people learning about exponential growth One video I saw mentioned that a person normal flu infects about 1.3-1.4 other people, but COVID-19 is closer to 3; so what's wrong with this analysis? 1**1.3 1**3 1.3**n 3**n '{:,}'.format(7e9) 1*(3**x) = 7e9 # solve for x with logarithms # Where is the limit with which controls? ## Notebook idea Growth curves: polynomials of degree 0 through 10 ('desic'), exponential, logistic - Exponential growth and epidemics https://youtu.be/Kas0tIxDvrg ## Prompt re: positive, helpful, constructive tone; morale; and amateur data science Here's a prompt for students and teachers alike: Respond to this re: amateur data science, tone, attitude, responsibility: https://www.reddit.com/r/datascience/comments/fm17ja/to_all_data_scientists_out_there_crowdsourcing/ ```quote FWIU, there are many unquantified variables: - pre-existing conditions (impossible to factor in without having access to electronic health records; such as those volunteered as part of the Precision Medicine initiative) - policy response - population density - number of hospital beds per capita - number of ventilators per capita - production rate of masks per capita - medical equipment intellectual property right liabilities per territory - treatment protocols - sanitation protocols So, it **is** useful to learn to model exponential growth that's actually logistic due to e.g. herd immunity, hours of sunlight (UVC), effective containment policies. Analyses that compare various qualitative and quantitative aspects of government and community responses and subsequent growth curves should be commended, recognized, and encouraged to continue trying to better predict potential costs. (You can tag epidemiology tools with e.g. "epidemiology" https://github.com/topics/epidemiology ) Are these unqualified resources better spent on other efforts like staying at home and learning data science; rather than asserting superiority over and inadequacy of others? Inclusion criteria for meta-analyses. - "Call to Action to the Tech Community on New Machine Readable COVID-19 Dataset" (March 16, 2020) https://www.whitehouse.gov/briefings-statements/call-action-tech-community-new-machine-readable-covid-19-dataset/ > “We need to come together as companies, governments, and scientists and work to bring our best technologies to bear across biomedicine, epidemiology, AI, and other sciences. The COVID-19 literature resource and challenge will stimulate efforts that can accelerate the path to solutions on COVID-19.” - https://www.kaggle.com/tags/covid19 - "COVID-19 Open Research Dataset Challenge (CORD-19): An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House" https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge - https://en.wikipedia.org/wiki/Precision_medicine#Precision_Medicine_Initiative ``` ## NIH FigShare instance https://www.niaid.nih.gov/news-events/rapidly-share-discover-and-cite-covid19-research-results-generated-niaid-awards > NIH is assessing the role of a generalist repository for NIH-funded research and has launched the NIH Figshare instance, a pilot project with the generalist repository Figshare You can archive a tag of a [topic-labeled] GitHub repository [containing notebooks] with FigShare. ## Resource Collections https://github.com/topics/2019-ncov https://github.com/topics/covid-19 https://github.com/topics/epidemiology?l=python https://github.com/topics/epidemiology?l=jupyter+notebook Objectively-scored Kaggle competitions: https://www.kaggle.com/tags/covid19 https://github.com/soroushchehresa/awesome-coronavirus On Tue, Mar 24, 2020, 6:35 AM kirby urner <kirby.ur...@gmail.com> wrote: > Awesome! > > If you do any kind of Youtube on this specific SIR model I hope you'll > link it from the cell and share it here. > > I see some Youtubes like that already (SIR models, including in Python), > but everyone codes a little differently. > > I'd like to go back to high school and do it all again from a student > perspective, now that the curriculum and tools are so vastly different. > > High school should be for any age, and one keeps going back every 10 years > or so. Learn it the new way. > > Kirby > _______________________________________________ > Edu-sig mailing list -- edu-sig@python.org > To unsubscribe send an email to edu-sig-le...@python.org > https://mail.python.org/mailman3/lists/edu-sig.python.org/ >
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