Ontario Science Table lockdown policy, backed by @fordnation, @JohnTory & @epdevilla, appears to have dramatically shifted C-19 disease burden onto the low income, high visible minority, high household density, high service worker areas of Toronto.

Shocking #’s & visuals follow. Image
First, a message to vulnerable communities:

In my opinion, health/govt officials put you in harms way. They⬆️your mobility *relative to the population*, shifting community disease burden onto you. They did not care about you. They cared about themselves and their failed policy.
We know there were relative disease burden differences. But to what degree?
Of Toronto’s 140 neighbourhoods, in the 2nd wave…

The 35 lowest income neighbourhoods vs. the 35 highest income neighbourhoods had*:

2.9x more cases
2.7x more hospitalizations
2.2x more deaths

*all figures are per 100,000 Image
The 35 neighbourhoods with highest concentration of visible minorities vs. the lowest 35 had:

2.6x more cases
2.1x more hospitalizations
1.6x more deaths Image
The 35 neighbourhoods with highest household densities vs. the lowest 35 had:

2.9x more cases
2.2x more hospitalizations
2.0x more deaths Image
And lastly, the 35 neighbourhoods with highest concentration of non-healthcare essential service industries vs. the lowest 35 (i.e. work-from-home neighbourhoods) had:

3.2x more cases
3.0x more hospitalizations
1.9x more deaths Image
IMO, these data show that OST and gov’t lockdown policy may have facilitated dramatically higher C-19 disease burden in the most mobile/vulnerable areas, by reducing the relative mobility of high income, work-from-home, low visible minority, low household density areas.
Yet we are calling for more of these restrictions?
toronto.citynews.ca/2021/03/15/ont…
I first pointed out the disastrous disease burden shifts already occurring across Toronto neighbourhoods back in November 2020, in two extensive threads (this one from the 22nd):
4 days later, on Nov. 26, @SteiniBrown of the OST, for the 1st time (to my knowledge) directly addressed disease burden differences. But he blamed “long-standing structural factors” (not the pandemic or policy) and offered a new term: “Prevention Gap”. Image
On January 28th, @SteiniBrown also acknowledges higher C-19 case burden borne by essential services workers (below slide), but simply reiterates need for workplace safety measures, and does not elaborate on the relative disease burden causes, imo. Image
But (and lastly), before we declare, as many do, that SARS-CoV-2 is simply a prejudicial virus, and its prejudice (and not lockdowns) caused the relative disease burden differences, let’s think a little deeper and remember that…
….as we know, higher service worker neighbourhood concentrations correlate strongly with cases per 100k... Image
…but that, unfortunately, the following neighbourhood characteristics also strongly correlate with high service worker concentration…

Visible minorities
Average household size
Average income (inversely correlated) Image
C-19 is not a prejudicial virus—but imo, the Ontario Science Table and gov’t policies turned the virus prejudicial when it shut down all of society, shifting relative mobility, contact, and thus disease burden onto those the services-based/low-income/vis-min/dense neighbourhoods.
End these lockdowns now.
/sources addendum

Toronto C19 Data: open.toronto.ca/dataset/covid-…
Service industry definitions:

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More from @rubiconcapital_

5 Mar
1/ Mass Vaccination – Why Do We Need it in Ontario (or anywhere?)

- LTC residents nearly vaccinated (55% of C-19 mortality)
- Progress in the most vulnerable (70+, 87% of mortality, 12% of pop)

A short thread with clips & charts, based on my recent video
2/ The public health messaging is clear—everybody needs a vaccine.

Dr. DeVilla of Toronto: “the sooner we have needles in arms and the more needles in arms we have, the better off we all are.”

(all clips from March 1, 2021 pressers)
3/ Dr. Williams, the Chief Doctor in Ontario:

“Wait for your vaccine, it's coming, we want everybody vaccinated, not just some, we want everybody done in a timely pattern.”
Read 18 tweets
31 Jan
Sensational article appealing to emotions, claiming Toronto ICUs "struggling with younger C19 patients". The headline may have you think ICU is in onslaught with young kids. ICUs are challenged, but the following charts don't match this narrative. 1/
twitter.com/i/events/13559…
Here are percentage of total COVID19 ICU admissions by age group in the 1st vs 2nd wave. Extremely low 6% of all ICU admissions in Under 39 ages, with only minimal changes in overall ICU admission mix in older ages. So the age mix of patients is roughly similar.
Here is the actual number of daily ICU admissions by age group... Under 39, 40-69, 70+....
Yes, we see the older ages are increasing... just like they were in the first wave...
Under 39 ages? ABOUT 1 ICU ADMISSION EVERY 5 DAYS.
Read 8 tweets
25 Jan
1/ It's hopeless, a thread.
2/ In the city of Toronto’s COVID19 update today, @epdevilla confirmed all first-round vaccines have been delivered at *ALL 87* of the city’s long-term care facilities and high-risk retirement homes.
3/ That’s great news !!

54.6% of Toronto’s fatalities occurred in these at risk groups…
…and excluding the high-risk LTC population…
…Toronto’s case fatality rate is 0.68%
…and just * 0.21% * in the under 69 population !

(see graph next tweet)
Read 9 tweets
24 Jan
That may currently be true, @BeateSander, but:

1. @DFisman (Science Table member) has helped Scarsin (a for-profit disease modelling software company) lobby the Ford gov't; and

2. York Region (1.2m people) currently uses the Scarsin platform. Image
From the Scarsin website: Image
Read 4 tweets
12 Jan
Please look at these 2 images very carefully & share widely.

Left Image: from today in a doom tweet from @SharkawyMD showing 410 & rising COVID19 ICU patients in Ontario.

Right Image: from Dec 11, when there were 247 COVID19 ICU patients.

BUT THE OVERALL ICU CENSUS IS SIMILAR!
Here is ER Doc @JeanmarcBenoit' tweet. He has been trying to convey overall ICU census is stable *despite* COVID19 census increasing steadily.
And here is @SharkawyMD's tweet from today; again showing similar overall ICU census, despite COVID19 patient census increasing.
Read 4 tweets
11 Jan
Pointing out some interesting peculiarities in the recent Ontario #COVID19 case and mortality data. This brief thread is a bit technical.

These peculiarities are similar to those identified in the UK data by @ClareCraigPath and @RealJoelSmalley
The % Positivity and daily deaths by Date of Death trends meaningfully diverged for the first time during the first two weeks of November…
In the 1st wave, correlation between (i) deaths by date of death and (ii) fatal cases with an episode date 12 days prior was almost perfect, with R=0.983 and R^2=0.976…

The second chart shows the onset-to-fatality lag correlation signal…
Read 12 tweets

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