Oh, apologies, wrong piece. Here's the correct one on the 'casedemic' nonsensehttps://gidmk.medium.com/there-is-no-casedemic-c6b0ba8b9fec …
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I don't care what the PCR test is turning over. Ontario, a province of 13.5m people, is experiencing what looks like a plateau of 15 covid deaths per day, 10 of which are non-community LTC.
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This is the deaths from Ontario public health. Ignoring the reporting lags, there is a pretty clear exponential increase there. I suspect if you averaged the weekly increase even with the reporting lag it would be an exponential functionpic.twitter.com/m4NMhysfSS
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I see a epidemic Gompertz curve and a hump topping off our herd immunity prior to going seasonally endemic. If you see something else (even with reporting lags) the I want whatever you're smoking !
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I say this without malice - you have absolutely no clue whatsoever what you are talking about. You are misusing every term you have used there, it is a garbled sentence that literally doesn't make sense
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I am intimately familiar with the chart you posted. Here is the 7-day trailing average of deaths by original symptom/episode date vs. the death reported date. Do you see it?pic.twitter.com/MTVSO9byKq
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Replying to @rubiconcapital_
...the clear reporting lag? Yes, that's officially stated by the public health authority I believe. It's like the Sweden figures - every fool makes a graph and points out that deaths are falling once a week because they don't report deaths within 14 days well
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Replying to @GidMK
The height of the blue line (symptom onset dates that eventually resulted in deaths) is roughly the same (certainly not exponentially higher) at Oct 30 vs Sept 30, which covers the 14-day reporting period. Honestly, what am I missing?
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Replying to @rubiconcapital_
Quickly eyeballing, looks like it's gone up by ~20% in that time. The reporting lag would also include the 29/30th, and symptom reporting is not a perfect measure. Would be more useful to look at day of death than day of reported symptoms
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Replying to @GidMK
Agree date of death vs. report would tell better story (date of death not published in daily CSV). Anyway, thanks for the debate and we can leave it there. My prediction is that natural herd immunity is nigh; heterogeneity was not included in epi models, and we see this soon.
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Look, again that is a statement that makes no sense whatsoever. If cases are increasing, herd immunity by definition cannot be "nigh". I honestly think you should look up some of this terminology before throwing it around - read an epi textbook!
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Replying to @GidMK
It doesn't take an epidemiologist to know we are not all identical dots bouncing around in the same box. We all have different immune susceptibility and contact susceptibility and this simply is not being built into public policy epi models and that is a fact.
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Replying to @rubiconcapital_
Modelling herd immunity is a fascinating and challenging topic, and it's true that some lower thresholds such as 40-50% may be viable in a fixed population. We have, however, now seen several examples of cities reaching above that threshold
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