add episodes on estimate severity

avallecam commented 7 months ago

This PR adds episode content for the middle task 3 (MT3)

I'll appreciate your specific feedback providing a clear next step to remove, change or add content.

some questions to guide feedback are:

should we add how Nishiura's method differentiates from other cohort methods to estimate CFR?
what other data sources/arguments can we use in challenges to increase the variability of countries shown?
should we plan to add more episodes covering introductory concepts needed for {cfr}?

how to review?

follow the steps in the reviewer role section of the contributing.md file
Before running sandpaper::build_lesson(), in the config.yaml file deactivate these episodes:

episodes:
# - quantify-transmissibility.Rmd
# - create-forecast.Rmd
- severity-static.Rmd

if local rendering doesn't work, please, report them in Issues.
you can read online the knitted content of this PR in branch md-output-1 (drawback, figure captions not visible)

github-actions[bot] commented 7 months ago

Thank you!

Thank you for your pull request :smiley:

:robot: This automated message can help you check the rendered files in your submission for clarity. If you have any questions, please feel free to open an issue in {sandpaper}.

If you have files that automatically render output (e.g. R Markdown), then you should check for the following:

:dart: correct output
:framed_picture: correct figures
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Rendered Changes

:mag: Inspect the changes: https://github.com/epiverse-trace/tutorials-middle/compare/md-outputs..md-outputs-PR-1

The following changes were observed in the rendered markdown documents:

 config.yaml (gone)                                 |   81 --
 create-forecast.md                                 |   55 +-
 fig/cfr-hhs-scenarios-psaf.png (new)               |  Bin 0 -> 322241 bytes
 fig/cfr-ifr-asserted-irv13181-fig-0002-m.jpg (new) |  Bin 0 -> 193433 bytes
 fig/cfr-pone.0006852.g001.png (new)                |  Bin 0 -> 139459 bytes
 fig/cfr-pone.0006852.g003-fig_abc.png (new)        |  Bin 0 -> 379802 bytes
 fig/cfr-pone.0006852.g003-fig_c.png (new)          |  Bin 0 -> 120588 bytes
 fig/cfr-pone.0006852.g003-fig_d.png (new)          |  Bin 0 -> 174190 bytes
 fig/cfr-s41467-020-19238-2-fig_a.png (new)         |  Bin 0 -> 90405 bytes
 fig/cfr-s41467-020-19238-2-fig_b.png (new)         |  Bin 0 -> 198878 bytes
 fig/cfr-spectrum-cases-covid19.jpg (new)           |  Bin 0 -> 318011 bytes
 ...create-forecast-rendered-unnamed-chunk-11-1.png |  Bin 8313 -> 8263 bytes
 fig/create-forecast-rendered-unnamed-chunk-3-1.png |  Bin 50447 -> 50379 bytes
 fig/create-forecast-rendered-unnamed-chunk-9-1.png |  Bin 10404 -> 10353 bytes
 ...ransmissibility-rendered-unnamed-chunk-15-1.png |  Bin 31316 -> 31537 bytes
 ...ransmissibility-rendered-unnamed-chunk-16-1.png |  Bin 30692 -> 30773 bytes
 ...ransmissibility-rendered-unnamed-chunk-19-1.png |  Bin 84192 -> 84103 bytes
 ...ty-static-rendered-unnamed-chunk-13-1.png (new) |  Bin 0 -> 27448 bytes
 ...ity-static-rendered-unnamed-chunk-7-1.png (new) |  Bin 0 -> 10346 bytes
 md5sum.txt                                         |   25 +-
 quantify-transmissibility.md                       |  110 +-
 reference.md                                       |    3 +
 renv.lock (gone)                                   | 1448 --------------------
 severity-static.md (new)                           | 1014 ++++++++++++++
 24 files changed, 1110 insertions(+), 1626 deletions(-)

What does this mean?

If you have source files that require output and figures to be generated (e.g. R Markdown), then it is important to make sure the generated figures and output are reproducible. This output provides a way for you to inspect the output in a diff-friendly manner so that it's easy to see the changes that occur due to new software versions or randomisation.

:stopwatch: Updated at 2024-03-25 18:40:08 +0000

avallecam commented 7 months ago

@CarmenTamayo @pratikunterwegs could we have your review during the coming two weeks?

pratikunterwegs commented 6 months ago

Thanks @avallecam - I'm not sure what I could add to the theory, but I can check that the use of {cfr} is correct and terms are explained as we intended in the package.

CarmenTamayo commented 6 months ago

@CarmenTamayo @pratikunterwegs could we have your review during the coming two weeks?

Hi @avallecam, thanks for letting me know, I can definitely review this and I'm very interested in doing so, I can do this next week- I hope this is okay!

avallecam commented 5 months ago

@pratikunterwegs thank you for your feedback. I added your specific edit suggestions to most of them.

I have some open replies I would like to prioritize and request your re-review. Here are the links to each of them:

explain the naive CFR concept
- https://github.com/epiverse-trace/tutorials-middle/pull/1#discussion_r1530821069
on discrete distributions
- https://github.com/epiverse-trace/tutorials-middle/pull/1#discussion_r1536208504
the theory behind the apparent low impact of delay-adjusted CFR at the end of the epidemic, compared to the ongoing trend
- https://github.com/epiverse-trace/tutorials-middle/pull/1#discussion_r1537368024
on the misunderstanding sentence of the sampling uncertainty rule of thumb
- https://github.com/epiverse-trace/tutorials-middle/pull/1#discussion_r1537372794

Open to discussing any misunderstanding.

avallecam commented 5 months ago

feel free to merge once Carmen gives her feedback.

Thanks! I'll collect Carmen's feedback in a separate PR

epiverse-trace / tutorials-middle

add episodes on estimate severity #1

Thank you!

Rendered Changes