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[Turing Data Story] Forecasting UK Vaccinations #129
Please provide a high-level description of the Turing Data Story
Based on the current rate of UK vaccinations (1st and 2nd doses), when will we finish vaccinating priority groups and the whole adult population (with 1st and 2nd doses)?
Which datasets will you be using in this Turing Data Story?
Additional context
I have a notebook with a simple analysis in this repo: https://github.com/jack89roberts/covid-vax, and I need to tidy it up and add prose to it. It's currently a simple forecast just assuming we will continue to vaccinate at an identical rate to the last week, with 2nd doses prioritised over 1st doses and being given 11 weeks later.
Possible extensions could include:
A more sophisticated forecast, e.g.:
considering alternatives where supply is limited for a period of time or continue to grow
new vaccines being administered (which could only be given as 1st doses initially, not 2nd doses)
Regional data
Differences in vaccination type, possibly in relation to the news (e.g. trust in the AstraZeneca vaccine)
Ethical guideline
Ideally a Turing Data Story has these properties and follows the 5 safes framework.
[x] The analysis you produce is openly available and reproducible.
[x] Any data used are open and have an explicit licence, provenance and attribution.
[x] Any data used are not personal data (i.e. the data is anonymous or anonymised).
[x] Any linkage of datasets in your data story does not lead to an increased risk of the personal identification of individuals.
[x] The Story must be truthful and clear about any limitations of analysis (and potential biases in data).
[x] The Story will not lead to negative social outcomes, such as (but not limited to) increasing discrimination or injustice.
Story description
Please provide a high-level description of the Turing Data Story
Based on the current rate of UK vaccinations (1st and 2nd doses), when will we finish vaccinating priority groups and the whole adult population (with 1st and 2nd doses)?
Which datasets will you be using in this Turing Data Story?
Mostly data from the .gov.uk Coronavirus dashboard/API: https://coronavirus.data.gov.uk/details/vaccinations . I've also taken the number of people in each priority group from this document.
Additional context I have a notebook with a simple analysis in this repo: https://github.com/jack89roberts/covid-vax, and I need to tidy it up and add prose to it. It's currently a simple forecast just assuming we will continue to vaccinate at an identical rate to the last week, with 2nd doses prioritised over 1st doses and being given 11 weeks later.
Possible extensions could include:
Ethical guideline
Ideally a Turing Data Story has these properties and follows the 5 safes framework.
Current status
Updates