TDS Modelling Hospital Admissions in the UK

edaub commented 3 years ago

Summary

Fixes #149

Adds story examining hospital admissions in England during the second and third waves of Covid-19.

List of changes proposed in this PR (pull-request)

New story carrying out Bayesian modelling of hospital admissions in England.

What should a reviewer concentrate their feedback on?

[ ] Is the context of the story well described?
[ ] Is the model clear and understandable?
[ ] Is the model implementation clear and understandable?
[ ] Do I sufficiently cover the caveats in the analysis?
[ ] Everything looks ok?

Acknowledging contributors

[x] All contributors to this pull request are already named in the table of contributors in the README file.
[ ] The following people should be added to the table of contributors in the README file:

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crangelsmith commented 3 years ago

Hi Eric, thank you very much for this new story! I have set up the review issue in #152, @helendduncan, @ChristinaLast and @lukehare will be the reviewers of this story.

@edaub Could I ask you to write a small abstract about the story that we can pass on to Comms once we publish it? You can just write it in here as a comment. Thank you!

ChristinaLast commented 3 years ago

@edaub Assigned you to take a look at some of the reproducibility issues. Let me know how you get on!

edaub commented 3 years ago

I appreciate the comments -- hoping to tackle this in the next week or so (though no rush @lukehare -- I'd rather get thoughtful comments later than ones that are hurried because I'm going on holiday...)

lukehare commented 3 years ago

Review added to #152 - looks good to me other than local environment issues, which may be a wider TDS issue (See #160). I could fully reproduce the story both locally (after some minor fixes) and in binder.

edaub commented 2 years ago

Hi All,

Sorry for the delay in revising this story -- I've finally had time to look at everyone's comments and very much appreciate the feedback. I've revised the story and pushed the updated notebook file. Specific comments in response to which I have made edits are included below:

Are the dates of the fall second lock-down correct? In the story they appear to be 2021 and a comment is made about widespread testing not being available but I think it was from then? This could well be me mis-reading it. Similarly with the cut-off comment being December 2021?

You are right that given the length of the pandemic some of those time frames have become ambiguous. I've tried to find any places where I used months/seasons and added a year to clarify exactly the time frame that I was referring to.

When running the calculations locally, some sections took 10-12 minutes to complete, and my laptop sounded. like it was working hard. I assume this is expected behaviour. Note left in notebook

This sounds about right. The sampling method has to run many, many simulations to find the parameter combinations that best agree with the data, which is why your computer fan started running steadily.

Are the dates of the fall second lock-down correct? In the story they appear to be 2021 and a comment is made about widespread testing not being available but I think it was from then? This could well be me mis-reading it. Similarly with the cut-off comment being December 2021?

As with above, I've tried to clarify dates by specifying the year. All the data on which I fit the model was from 2020, and all predictions were made for data in 2021 based on the parameters of the 2020 data.

the second national lockdown came into force on the 5th November and the third national lockdown is announced on 6 January, using this resource.

Yes, this is correct. I've added some comments to clarify exactly when the lockdowns began in the text.

It may be worth adding a non-technical explanatory sentence to this

I've added some additional explanatory text to the model section to try and make it slightly less technical.

There is also the fact that it is not just the probability of infection given a vaccine but the reduction in the probability of infection given the vaccination status of those around you.

This is a good point, I've added a comment to this effect in the discussion section.

As mentioned by Helen and Christina, I believe there are typos in the introduction section, and several references to 2021 ("July", "May", "31 December") should refer to 2020.

As discussed above, I have tried to clarify these by adding the year. Please check that I haven't missed any!

The notebook appears to have been duplicated, i.e., the entire notebook is repeated (following the discussion section, the introduction reappears, followed by the authors, ...). This is probably a result of awkward notebook/git interaction. Currently leads to some Non-unique cell id errors, but these are easily ignored.

I also ran in to this problem when pulling down the changes from Github. I ended up creating a new notebook and committing the edited file all at once, which I hope will fix this problem!

I also made a number of edits and tweaks that hopefully helped further clarify some aspects of the story and model.

ChristinaLast commented 2 years ago

Ah, I wasnt aware they were merged. I can create a hotfix branch to remove and add to .gitignore?

crangelsmith commented 2 years ago

Ah, I wasnt aware they were merged. I can create a hotfix branch to remove and add to .gitignore?

Sounds great! Thanks!

ChristinaLast commented 2 years ago

So @crangelsmith the hotfix PR is here. Please feel free to approve and I can merge. Apologies for those files getting into master!

alan-turing-institute / TuringDataStories