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
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