I think the main problem is that there are many gradations of "metastable/endemic" with hundreds of possible causes, so grouping it together while in a mathematical sense might be reasonable in an epidemiological sense is less than ideal
The main issue, as I mentioned, is the assumption that 'community immunity' is a) a homogenous state b) the 'end' of a pandemic and c) possible to reach. The other errors stem largely from these mistakes
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a) I have never assumed it is a homogeneous state -> that is why it is a meta-stable state after all (by definition). b) 'pandemics' end. Whether by extintion of the host, the virus or because of co-adaptation. c) See b and a.
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If it's not a homogenous state then the central premise is flawed - endemicity could result in much higher infection rates among vulnerable populations over time
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For example, one potential consequence of long-term endemicity is infections being more common in elderly populations (as with influenza) meaning reaching this state faster could in fact result in far more deaths than the alternative
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Let me rephrase it to understand. So, because over the long-term a certain amount of people will be infected (say N) over time T. If we push T over the infinitum we would be guaranteeing less deaths? How so?
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