Some interesting questions about the new "active" and "serious" by age graph on the IMoH dashboard. Here's "active" cases and the verticle black line is when they changed the dataset they were reporting
Question 1: What has caused the surge in the population of unvaccinated people that the normalized figures have dropped. If it was that the partially vaccinated were now being counted then we would expect absolute cases for 12-15 to jump by 1400 but they fall slightly... not that
Question 2: Where did the 1400 active cases in 12-15yo disappear to? They're not added to the unvaccinated cases... they're not added to the vaccinated cases... they're not added to the 3rd shot vaccinated cases... these cases have magically disappeared
I haven't done the maths, but by eyeball it looks like the splitting of the vaccinated into 2 shot and 3 shot explains the drop in cases from the old vaccinated dataset as well as the increased normalized numbers (as population of 2nd shot only is smaller than combined)
Now we can move on to the "serious" cases. This is much noisier data. Again I think the 2nd shot changes are explained by the separation into 2nd only and 3rd only
There aren't enough "serious" 1 shot cases to determine where they go...
But we now see a similar pattern to active cases whereby the population normalized unvaccinated case numbers have significantly dropped. In fact the normalized case numbers for 70+ have dropped to the rates for 60-69. There must be some wonder cure everyone got on the 5th of Sept
The cynic part of me, however, has a darker view. Suppose one were to move the population counts of the partially vaccinated over to the unvaccinated column and but not count the cases... anywhere... would that hide a significant increase in active cases in the partial group?
If Blofeld were seeing a massive surge in 12-15y partially vaccinated active cases (rate above unvaccinated rate) and he wanted to encourage 12-15y to get vaccinated it would certainly be convenient if those cases were not being counted any more... but this is not a Bond movie
Anyway... these are interesting questions none the less. I strongly advise against holding your breath if you are waiting for an answer /cc @daridor @OS51388957 @MatanHolzer @prof_shahar @RanIsraeli
Footnotes: The data is from this graph on the IMoH dashboard (datadashboard.health.gov.il/COVID-19/gener…) and I have been running a scraper for a bit of time now. The scraped data is available at github.com/stephenc/2021-…

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with 😀 Stephen Connolly

😀 Stephen Connolly Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @connolly_s

10 Sep
Ok. So I finally automated my Z-score analysis of Israeli case data. I have yet to automate publishing the generated graphs to Twitter... but here comes 9 weeks of the same analysis methodology... so you can easily compare. First up 29th August to 4th September inclusive
2021-08-22 to 2021-08-28
2021-08-15 to 2021-08-21
Read 17 tweets
30 Aug
Latest Israeli cases analysis, and previous analysis revisited.

First a data health warning. I am basing the numbers in each dose using the published data on ages of vaccinated (data.gov.il/dataset/covid-…).

The readme (data.gov.il/dataset/covid-…) has this caveat. 🤷

(1/n)
With the new data on the 3rd dose I have had to rework the analysis, so the layout will be slightly different than previously. Also to try and limit information overload I only present Z-scores and P-values for selected comparisons against both unvax and 2 dose fully vax

(2/n)
Anyway, here's the data. Interpretation to follow...

(3/n)
Read 11 tweets
18 Aug
Here's the update for Aug 8-14th
@RanIsraeli @MLevitt_NP2013 @prof_shahar @OS51388957 @daridor
I do not think my conclusion that its different reporting rates vs vaccination status is contradicted.
At this point I think this dataset on its own is telling all it can tell 1/n
That doesn't mean there are not useful analysis that can be constructed by pairing other data sets with this data set, but certainly anyone saying this data on its own shows any conclusion about rates across vaccination status is IMHO stretching beyond breakpoint 2/n
Also you can use this data to make statements about individual groups, e.g.:
* The case rate in the vaccinated group is not non-trivial, this supports the assertion that "vaccine does not prevent infection"
3/n
Read 7 tweets
11 Aug
Latest Israeli case data... @RanIsraeli @MLevitt_NP2013 it's complicated, but I'm going to try and explain what it says and what we can conclude. First the background 1/n
So there have been these spreadsheets popping up on social media reporting the age breakdown of cases and the percentage of the population fully vaccinated and highlighting the similarity of those numbers, citing datadashboard.health.gov.il/COVID-19/gener… as the source 2/n
Using that data I was able to compute statistical Z-scores, but as I do not speak Hebrew, my ability to verify the numbers was limited. Those Z-scores implied a significant difference in the case rate between vaccinated and unvaccinated with unvaccinated lower! 3/n
Read 26 tweets
9 Aug
When facing Z scores of 5 and 7 indicating that the unvaccinated care rate is significantly lower than the vaccinated case rate, the precautionary principle has a lot to say about whether to continue vaccination while we await understanding of the cause of this difference. Image
For a null hypothesis is that there is no difference in case rates between vaccinated and unvaccinated, the probability of observing a difference like this is 1 in 8110. This is monthly data so that's once in 675 years Image
The hypothesis everyone is hoping for is that the case rate for vaccinated is less than the case rate for unvaccinated. That requires us to use a single tailed test. The probability of seeing Z=7 on a single tailed test is 1 in 16,207 or once every 1350 years Image
Read 10 tweets
8 Aug
Thanks to spotting this retweet on @RanIsraeli 's feed I was able to update my basic Z-score analysis ImageImageImageImage
Here's the aggregate for almost the full month. A Z-score of 3.77 is, single tailed P<0.00008, double tailed P<0.00004. The Z-score of 5.28 and 7.00 is where the NCEST tables give up and say it's effectively beyond doubt. These are +ve Z-scores ie saying unvaccinated LESS likely Image
Caveat: This says there is a difference between the two groups... and it says for the 20-29, 40-49 and 60-69 age groups there is a very significant difference between vaccinated and unvaccinated rates... but it doesn't tell us what the difference is
Read 10 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!

:(