https://en.wikipedia.org/wiki/Epidemiology
https://en.wikipedia.org/wiki/Mathematical_modelling_of_infectious_disease https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology - Why we wear masks when we go outside https://en.wikipedia.org/wiki/Technological_singularity https://en.wikipedia.org/wiki/Technology_adoption_life_cycle#See_also On Tue, Mar 24, 2020, 9:36 AM Wes Turner <wes.tur...@gmail.com> wrote: > 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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