This is how the shares of #CovidVaccines by manufacturer and by available country looks like on 01oct2021 #COVID19
Here is a quick visualization of #COVIDVaccination over time by manufacturer for selected countries, "champions" of a particular manufacturer, based on data from 01oct2021 (Hungary is "champ". for both Sputnik & Sinopharm)
Chile is a champ. of Sinovac
Approaching 80% of fully vaxxed folks
well notice how bumps in "cases" follows new vaxx
no data on owid for hospi. but deaths labeled c-19 are down
Czechia is a champ of Pfizer
Approaching 60% of fully vaxxed folks
seems to "work" according to these curves (for now...)
no bumps in "cases" following bump in vaxx
Hungary (also East Europe like Czechia) is champ of "non EU" vaxx: Sinopharm & Sputnik
Approaching 60% of fully vaxxed folks as well
weird new vaxx curve
here it seems to work as well (for now)
bump in "cases" precede bump in new vaxx (?)
Latvia is a champ. of J&J (as % of injections on 1.10.21)
Approaching 50% of fully vaxxed
doesn't seem to work as promised
but they "test" like mad, so "cases" explode, hosp. & c-19 labeled deaths follow
notice the coincidence with uptick in new vaxx...
Liechtenstein is Moderna champ
Approaching 60% of fully vaxxed folks
boy those curves are all over the place...
seems that recent bumps in new vaxx are correlated with "cases" but they ramped up "testing" as well
notice similar pattern for initial ramp in new vaxx in spring
South Korea is Astra champ.
Approaching 50% fully vaxxed folks
doesn't seem to work as promised, everying goes up but notice they "test" like mad...
on notera, comme d'habitude (sic), la discordance entre:
- les données vaxx (dernière date connue)
- les données décès "avec" c-19 (moyenne dernière semaine)
[et comme par hasard plus on va à l'est plus l'automne est précoce...]
du coup voyons voir France (FRA) vs Ukraine (UKR) avec les données owid de ce jour (n.b. données hospi. n.d.):
quelle surprise !
courbe "tests" et donc "positifs" en chute libre en FRA => courbes hospi. et décès suivent
tout le contraire en UKR #CQFD #Covid_19#COVID19
#thread follow up to previous thread below
i repeat the same excercise with positivity rate instead of reproduction rate vs stringency index by adding country, week and both effects in the panel regressions #COVID19 1/n
the graphs:
(notice higher positive rate when stringency stronger)
benchmark: within R² = 5.82%
+country dummies: same
+week dummies = 47.36% (~ x 100 w/r benchmark)
+country & week dum. = as above
again "seasonality" explains most of what is going on in the data #COVID19 2/n
and so again one can ask if they #lockdown during colder seasons and this makes actually things worse ? #COVID19
3/3
#thread
Following recent success of this thread (thanks @FatEmperor i guess :)just wanted to get back to this
i will just take the first graph as exemple: it's reproduction rate vs stringency index
panel (country-time in days) regression with random effects #COVID19 1/n
i put the initial graph as "benchmark" and i add 3 other graphs
panel regression with random effects
with countries dummies included
with weeks dummies included
with countries & weeks dummies included
and we will compare the R² as these are the only changing in this excercise 2/n
in panel regression what is most important is the R² within
adding country effects changes nothing
adding weeks (i.e. time trend or "seasonality" in this context) increases a lot the R² within (~ x100)
adding countries & weeks => same results as with weeks added only
3/n