NSW R_eff as of Aug 16th with daily cases and Sydney restrictions. Latest estimate: R_eff = 1.33 ± 0.12

Plus projected effect of vaccination rollout.

Cases shown on a linear scale (log scale in next tweet).

More info chrisbillington.net/COVID_NSW.html

#covid19nsw #covidsydney
NSW R_eff as of Aug 16th with daily cases and Sydney restrictions. Latest estimate: R_eff = 1.33 ± 0.12

Plus projected effect of vaccination rollout.

(Cases shown on a log scale)

More info chrisbillington.net/COVID_NSW.html

#covid19nsw #covidsydney
R_eff in LGAs of concern* (*all of Penrith included) vs the rest of NSW:

LGAs of concern: R_eff = 1.32 ± 0.12
Rest of NSW: R_eff = 1.81 ± 0.25

(Cases shown on a log scale)

#covid19nsw #covidsydney
Expected numbers if the current trend continues:

day cases 68% range
Tue: 502 427—581
Wed: 532 442—629
Thu: 561 458—678
Fri: 591 473—728
Sat: 622 487—784
Sun: 655 499—840
Mon: 685 515—898

Doubling time is 12 days.
A change since yesterday, I've increased projected vaccine doses in light of the rollout in NSW being faster than I previously assumed, this brings forward the projected peak in cases.

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More from @Chrisbilbo

6 Sep
Since the modelling the NSW gov has released is in terms of the LGAs of concern only, here's my model re-run with only the LGAs of concern considered instead of the whole of NSW. Result is extremely similar to that of the gov's modelling.
The smoothing for mine is centred though, meaning to compare with their 7-day moving average, you'll wanna push my projection to the right ~3.5 days. Taking that into account, it looks like my model is predicting a peak about ~1 week later than them, but of the same height.
And the difference in timing is pretty much within the uncertainty range of both projections, so they basically agree to within the accuracy claimed by each model
Read 4 tweets
6 Sep
NSW R_eff as of September 6th with daily cases and restrictions. Latest estimate: R_eff = 1.20 ± 0.05

Plus projected effect of vaccination rollout.

Cases shown on a linear scale (log scale in next tweet).

More info chrisbillington.net/COVID_NSW.html

#covid19nsw #covidsydney
NSW R_eff as of September 6th with daily cases and restrictions. Latest estimate: R_eff = 1.20 ± 0.05

Plus projected effect of vaccination rollout.

(Cases shown on a log scale)

More info chrisbillington.net/COVID_NSW.html

#covid19nsw #covidsydney
R_eff in LGAs of concern* vs the rest of NSW (*all of Penrith included):

LGAs of concern: R_eff = 1.28 ± 0.05
Rest of NSW: R_eff = 1.43 ± 0.07

(Cases shown on a log scale)

(note LGA data is several days old, does not include today's cases)

#covid19nsw #covidsydney
Read 4 tweets
5 Sep
VIC R_eff as of September 6th with daily cases and restrictions. Latest estimate: R_eff = 1.92 ± 0.21

Plus projected effect of vaccination rollout.

Cases shown on a linear scale (log scale in next tweet).

More info chrisbillington.net/COVID_VIC_2021…

#COVID19Vic
VIC R_eff as of September 6th with daily cases and restrictions. Latest estimate: R_eff = 1.92 ± 0.21

Plus projected effect of vaccination rollout.

(Cases shown on a log scale)

More info chrisbillington.net/COVID_VIC_2021…

#COVID19Vic
Expected numbers if the current trend continues:

day cases 68% range
Tue: 328 233—430
Wed: 386 255—531
Thu: 452 277—659
Fri: 527 301—811
Sat: 619 323—992
Sun: 721 345—1220
Mon: 838 369—1487

Doubling time is 5.5 days.

#COVID19Vic
Read 4 tweets
5 Sep
Animated version of my NSW projections over time. *not 100% identical to actual past projections because I'm using my current code running on old data and there have been some minor changes, but very close.
And the version with cases on a log scale
You can see that we did not see the projected effect of vaccinations for some time. If they were working as expected, something else must have been increasing R_eff at the same time. If you squint, maybe the decrease in R since mid-August has been in line with expectations.
Read 4 tweets
5 Sep
Some have written to me asking about vaccine assumptions, and how much they affect the projections. I assume a 40% overall reduction in transmission per dose - i.e. an 80% reduction for someone fully vaccinated. How much would it change things if that were different? 1/🧵
TL;DR, this much. Here's the current NSW projection with 70%, 80% and 88% reduction in spread assumed for fully vaccinated people (and half that for single-dosed). More on those numbers below. 2/🧵
The overall reduction in transmission from a vaccine comes from it preventing some fraction of infections—this is called E_i, and also preventing some fraction of onward transmission in the infections it doesn't prevent—this is called E_t. 3/🧵
Read 11 tweets
5 Sep
NSW R_eff as of September 5th with daily cases and restrictions. Latest estimate: R_eff = 1.27 ± 0.05

Plus projected effect of vaccination rollout.

(Cases shown on a log scale)

More info chrisbillington.net/COVID_NSW.html

#covid19nsw #covidsydney
NSW R_eff as of September 5th with daily cases and restrictions. Latest estimate: R_eff = 1.27 ± 0.05

Plus projected effect of vaccination rollout.

(Cases shown on a log scale)

More info chrisbillington.net/COVID_NSW.html

#covid19nsw #covidsydney
R_eff in LGAs of concern* vs the rest of NSW (*all of Penrith included):

LGAs of concern: R_eff = 1.27 ± 0.05
Rest of NSW: R_eff = 1.27 ± 0.07

(Cases shown on a log scale)

(note LGA data is several days old, does not include today's cases)

#covid19nsw #covidsydney
Read 5 tweets

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