plz-issues and age groups

[DonGoginho]

Dear Amigos

I've tested data about «3. Cumulative number of vaccinations by postal code per calendar week from 2021-01-18 / Kumulierte Anzahl Impfungen nach Postleitzahl pro Kalenderwoche ab 2021-01-18» and would like to give u the follwing input:

• Referencing on PLZ4 is a quite tricky. According to POST, a 4 digit PLZ is unique with its number AND its 'Ortsbezeichnung' . E.g. 8105 - Regensdorf isn't the same as 8105 - Watt. So it would be great to have

  • either statistical data with 'Ortsbezeichnung' too
  • or prepared PLZ4-Geodata ready to use for this dataset (with dissolved polygones on PLZ4 digits). There is different #OpenData on PLZ, but none of them is - as far as I've seen - ready to be used with your data. Neither «PLZ-Verzeichnis v2?» by POST nor your «Ortschaften und Postleitzahlregionen (kantonaler Datensatz)» can easily be used.

• Differenciating age groups (u13 and over12) Secondly I've been asking myself why we don't make a difference in using total population per PLZ and addidionally a distinction between the population over 12 (impffähiges Alter) and under 12 per PLZ. This would explain how high the percentage of potentially possible vaccinated persons would be. No?

Best regards, Marco

[metaodi]

Maybe adding the geojsons like in the covid_19 repo would help for the PLZ issue: https://github.com/openZH/covid_19/tree/master/fallzahlen_plz ?

[andreasamsler]

Thanks @DonGoginho for using the data and giving back feedback. @rujung @gmacauda, wdyt?

[gmacauda]

Dear all,

Thanks @DonGoginho for your feedback!

• We second metaodi's proposal. The population data used for the vaccination campaign is also being used here: https://github.com/openZH/covid_19/tree/master/fallzahlen_plz We could add the geojsons to this repository.

• Regarding the age: That's a good point. We will look into that.

Best

[DonGoginho]

Hej @andreasamsler & @gmacauda

1. PLZ 4-digits, simplified in GeoJSON:
   • It's good to add the same dataset to this repo. BUT then nobody will find it via the Searches on Opendata.swiss or any other Data Catalog. Therefore it would be better to publish this dataset alone and link it to the relevant repos...
2. PLZ4 handling in the statistical data
   • It still remains unclear how the values are calculated as you only use the PLZ Number. But a geografic region is only unique together with it's name (ortsbezeichnung). 8044 Zürich is not the same as 8044 Gockhausen. Do you summarize all these values?
3. Age groups
   • It makes quite a difference if you ad the population in 'impffähigem Alter'. E.g. in your data in 8055 the percent of 2nd vaccinated persons is 58%. If you take only the persons in 'impffähigen Alter' it is on 72%.

Here are some tests I made in a Jupyter Notebook. This might clearify a bit more what I mean.

[andreasamsler]

Hi @gmacauda, in case this is on 'to be analysed' or 'to be implemented', what's your view on question 2.? Thx, a

[gmacauda]

Dear all, sorry for the delay. Regarding question 2: Yes, it summarizes all values within the PLZ. @DonGoginho Overall, we agree with all your points, especially point 3. We are working on updated vaccination data.

[DonGoginho]

Hej @gmacauda and @andreasamsler , thx for your feedback. I'm glad to hear that and looking foreward to the results +1

Best regards, Marco

[adrupp]

Hey @DonGoginho
We are considering, archiving this repo, because there is no activity anymore and it seems, there will be no activity in the future 🤞. Otherwise it can be unarchived if necessary. Therefore we're checking all open issues. What about this one? Is it still important or can you either close this one as completed or close as not planned? Thank you!

[adrupp]

Friendly reminder (open question): @DonGoginho