I agree with this, but to me, it is actually a mathematical point (about
mixing). Whereas, your point about not assuming infected + survived
implies immune, is biology, not maths - and makes sense. Must be data
somewhere on the percentage of survivors who acquire immunity for various
other diseases, and how long that immunity lasts?
Greg
> At 20:36 14/03/2020, John Bibby wrote:
>>As I understand it - having been reminded by Greg - if 2.35 people
>>are affected and 60% are immune, then 40% x 2.35 is just under one
>>i.e. the exponential curve goes down, not up. .... To answer my own
>>question, if there are two populations P1 and P2 with immunity
>>proportion x1 and x2 and infection multiplier (I forget the
>>technical term) m1 and m2 then the exponential power is xxxx which
>>is quite a simple function. (To be worked out later.) .... Suitable
>>combinations of the parameters can then ensure that the overall
>>growth rate is less than one. This can then be applied to P1 =
>>vulnerable people, P2= the rest. P2 can then be further
>>disaggregated to include the school population.
>
> I think this is another of those situations in which one has to be
> careful not to think only about the maths.
>
> The crucial thing about the concept of herd immunity is that it is
> reliant on homogeneity - in particular that the level of immunity in
> a group of people who 'congregate together' (i.e. are in close
> contact with one another) is at least as high as the HIT. Hence, if
> a particular group (e.g. a regional comminity) who are in close
> contact contains a mixture of your P1 and P2 populations, all that
> matters (in terms of herd immunity - i.e. the likelihood of an
> 'epidemic' of infection spreading rapidly through that group) depends
> only on the overall proportion of people in that 'mixed' group who are
> immune.
>
> Kind Regards,
>
>
> John
>
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