What is wrong with Ontario's latest approach to COVID?
It is #So1stWave. Emerging from the first wave, we were happy we survived it, and thought that if we could just keep case counts reasonably low or prevent hospitals or ICUs from being overwhelmed, we would win the battle.
This is the ExCUSE (Examples of Canada, US, and Europe) approach. The govt. released their new plan predicated on this thinking. If I were to bet, it was conceived over 6 weeks ago (i.e. around Sept. 23). To remind you, this was ExCUSE total deaths and cases 6 weeks ago.
I will focus on 2 countries to demonstrate what happens when you take a #So1stWave approach. We will start with Belgium (pop 11.5m), using data from @OurWorldInData and Belgium's National Science Institute: epistat.wiv-isp.be/covid/covid-19…. Here was where they were Sep 23. <4 deaths/d.
If you plugged in all the data, they would be in our new "Restrict" (orange) zone: 13.8 cases/100 000/day
%positivity 4.3%
Ro was 1.34 (which would place it in the red "Control" category)
550 patients hospitalized
105 in the ICU
All is good.
But fast forward 4 weeks (remembering the various lags of inaction and effect of any new PH measures).
104 cases/100 000/day
%positive 18.6%
Rt 1.53
3275 patients hospitalized
525 in the ICU
Country overwhelmed (and over 40 deaths/d)
Well, you might say, why would we look at Belgium. They are a tiny, largely insignificant country with an overstated importance of waffles. Fair enough. Let's look at Germany (popn 83M). This is where they were at on Sep 23
13 cases/100 000/WEEK
%positivity 1.1%
Rt <1
Surely we can relate (or be envious of) the Germans.
Let's read their situation report (found at the Robert Koch Institute rki.de/EN/Home/homepa…) from Sep 23, and see if it sounds familiar. They would firmly be in our yellow "Protect" zone.
Now let's move forward 4 weeks in Germany.
51 cases/100K/wk
3.6% positivity
Rt~1.3
25-30 deaths/day
They would fall within our Amber "Restrict" zone. They also responded in a cool-headed manner, similar to how we are responding. That was Oct. 21.
Today: 90 deaths/day. This is their most recent situation report.
We have seen this before. Let's not repeat the mistakes of Europe. Make no mistake, we should not pursue a strategy that is #So1stWave. It is indefensible, and WE DON'T HAVE TIME TO TWEAK. We need to pursue an A-PAC strategy
Prompted by several posts and threads, I am going to outline what I view as the "A-PAC Approach"
A-PAC refers to Asia-Pacfic and Atlantic Canada: 🇦🇺(25M), 🇨🇳(1.39B), 🇯🇵(126M), 🇳🇿 (5M), 🇰🇷(52M), 🇹🇼(24M), 🇹🇭(69M), and 🇻🇳(96M). Atlantic 🇨🇦 has 4 provinces ((NS, NB, NFLD, PEI, 2.4M)
These countries/provinces have varying geography, population size and density, degrees of democratic norms; some are islands, but others share sizable borders. Several have used a cordon sanitaire (i.e. making a region an island, even if it isn't one) to create an "island".
The A-PAC Approach consists of 6 principles: 1. Aim for really low number of new cases and zero transmission 2. Ensure any new people (esp. cases) coming in from outside are quarantined 3. Aggressive test-trace-isolate 4. Strong public health leadership
I have spent the past day weighing whether to like article because it is a fantastically executed example of #scicomm or dislike it because it is propaganda that distorts the evidence. english.elpais.com/society/2020-1… via @elpaisinenglish
What makes it so effective is the #dataviz, the relatable examples, and the plainspeak. I read the translated English version, and it really is wonderful to read. I came away thinking that aerosol transmission was so clear and plainly obvious. Until I realized this is propaganda.
It quotes a letter as an "article in the prestigious @ScienceMagazine" [finding] that there is 'overwhelming evidence' that airborne transmission 'is a major route'" for transmission. This is misleading.
As @JPSoucy points out in this excellent 🧵, we have a experienced a considerable drop in testing. The question we don't know is: how many should we be testing? @skepticalIDdoc and other super-smart people suggest keeping our eye on %+. I am going to try to reframe the problem.
I will start off by saying this:
"cases" are numerator
"tests performed" are denominator
"% positivity" are cases/tests performed
If you do 20 surveillance tests (i.e. in asymptomatics) in a school, or 200, the % positivity will remain the same, but the "cases" will increase.
Cases matter.
They theoretically matter to the case (so they can receive treatment if they need it).
They should matter to public health to identify contacts (who may be infected) #ContactTracing
They should matter to everyone if we are treating them as surveillance.
This is a followup to my thread yesterday to help the public understand better what is going on in Toronto (and Ottawa, Peel, and the rest of Ontario). I am going to focus on what everyone needs to understand about the ON testing fiasco (which is being played out elsewhere too)
First: I get my data from @jkwan_md@imgrund@JPSoucy@ishaberry2 to support my understanding. They get it primarily from publicly available sources, and make the data easy to understand.
Second: our daily case # in ON are artificially low (by ~330) because of the backlog.
The backlog was entirely preventable. I was told months ago when I asked that the reason labs weren't able to increase capacity was $$ from govt. @bruce_arthur covers this accurately here
My biggest concern in Toronto at present: the public doesn't understand the acuity of the situation, and are therefore understandably upset at current developments. So I will try and outline my understanding of the current situation:
Testing: we have a 7-day average of about 240 cases/day. This is an underestimate of the number of tests, because of a) backlog, b) system challenges that are dissuading people from being tested, c) over-weighing of younger cases, which makes asymptomatic cases more likely.
Regardless, our testing system is overwhelmed, and so we have no gauge on our gas tank.
The number of cases has totally exhausted @TOPublicHealth capacity.
My bread-and-butter framework comes from @SusanMichie and colleagues: The behaviour change wheel: a new method for characterising and designing behaviour change interventions. doi: 10.1186/1748-5908-6-42 ncbi.nlm.nih.gov/pubmed/21513547
1. Education: this has a weak track record. But maybe universities/colleges—regardless of virtual or not—can make knowledge a criterion of ongoing assessment/performance.