This is the best write up of the whole T cells and herd immunity thing that I've seen, and somehow it still misses a central point: If COVID-19 was this bad WITH EXISTING IMMUNITY then the immunity doesn't matter all that muchhttps://twitter.com/EricTopol/status/1292650588543434752 …
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It's a really simple point but somehow keeps getting missed. If COVID-19 can kill 1% of the population when 50% already have some immunity, it changes almost nothing about the public health response
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Replying to @GidMK
Changes nothing about the response - what about the length? Wouldn't it shorten the overall duration of the battle significantly or no? And if not why not? Thanks for helping explain the potential significance. First truly potentially positive development I've seen since January.
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Replying to @trilnack
Not really. If 50% of people have some immunity it might go a long way to explaining asymptomatic spread, but we're still in a situation where an unmitigated pandemic can cause New York or Lombardy situations regardless
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Replying to @GidMK
Gotcha. Would it at the same time rule out another similar repeat spike in those two locations, specifically, for example? Is that the main takeaway? That, if true, it's herd immunity (vs. ongoing behavioral adaptations) which are preventing a resurgence in hardest hit areas?
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Replying to @trilnack
Not necessarily. If 50% of the population has some immunity, you have to basically double the observed R0 to get the true value, which then has a much higher cutoff
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Replying to @GidMK
I don't grasp that explanation. I want to, but I don't. Not yet, anyway. I'll read up and get to a point where it makes sense. Thank you for the time and answers!!
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Replying to @trilnack
Pretty simple really - we observe an R0 of 2.5 i.e. each person passes the disease on to 2.5 on avg. However, we find out that 50% of people are already immune - that means that the true R0 is actually (x)*0.5 = 2.5 Multiply out, you get R0=5
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Replying to @GidMK
The herd immunity threshold is a very simple calculation = 1-1/R0 So, with R0=5, we get HIT = 1-1/5 = 80%, which means minimum of 30% further need to be infected to get immunity
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But on top of this, we have the fact that 2.5 is a static figure and the observed R0 is really modelled somewhere between 2.2-4, which means that the HIT could be 25-45% in this scenario
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Replying to @GidMK
Ok, that makes sense! The remaining 30% (let's say) in a NYC situ. Is it a solid assumption that those additional cases would be highly unlikely to become infected in a similarly large/fast wave, overwhelming the hospitals a 2nd time? (Due to awareness/behavioral adjustments).
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