thanks John

your points can be incorporated in the forecast, and the SEIR does already
account for the impact growing immunity but that comes later on - see
panel 1 of Fig 2. The deaths arise from infections contracted 25 days
before death, on average, [5 days incubation + 6 days mild + 14 days from
hospital admission to death, for those who die] so the expected surge in
deaths just around the corner comes from infections before 24 Mar, or even
16 Mar. Which is the price for the gov't failing to act promptly.

but I am currently rethinking another issue in the parameter estimates, so
this is all on hold for now while I find out how wrong I am. Here's
hoping!

Greg

> At 18:49 28/03/2020, Greg Dropkin wrote:
>>hi all ... COVID-19 forecast for the UK lockdown
>>http://www.labournet.net/other/2003/lockdown1.html
>>please fwd this url wherever you think useful. ... and, comments /
corrections please.
>
> Greg, I'm sure you will take it in the right spirit when I say that I
have to agree with the final comment in your conclusions when you say
that "you hope you are wrong" - and, as I'm sure is true of you and many
others, I have been trying hard to think of ways in which you may be
'wrong'.
>
> I imagine that there is nothing intrinsically wrong with the model you
are using.  Within my (seriously) limited ability to comment, the model
looks fair enough and the assumptions on which you have based your
modelling seem reasonable enough.
>
> The best I can do is ask whether you are 'fairly' modelling what the
situation actually was.  You are assuming that the 'lockdown' (which you
hypothesis reduced transmission to 10% or 15%) started suddenly on 24th
March, but the true situation was not as simple as that.
>
> Over a week before that, on 16th March, following a 'warning' the day
before that a 'lockdown' was going to come, the PM advised
> 'social-distancing'.  Non-essential travel (and going to pubs/clubs
etc.) was advised against, home working advocated and, in particular, he
strongly advised the most vulnerable (>70, pre-existing disease of
pregnant) to 'self-isolate' , with that advice becoming progressively
stronger over the coming days, coupled with a warning that it would soon
become 'compulsory'.
>
> There clearly was at least some degree of response to that advice on the
part of the general public but, for what it's worth, anecdotally
speaking, the majority of 'vulnerable people I know seemed to comply
with the self-isolation fairly soon after it was suggested/advised.
Furthermore, again anecdotally, even in relation to mainly
> non-vulnerable people, by/around Monday 16th March, a high proportion of
people \i work with were already working from home.
>
> I would therefore suggest that a 'more complete' model might, in
addition to what you've already got, also include:
>
> 1... A period (maybe about a week) prior to 24th March during which
there was a fairly modest (your guess is as good as mine!)
> progressively increasing reduction in transmission within the general
population
> PLUS, probably more importantly,
> 2... A period (again maybe about a week) there was a more
> substantial, and progressively increasing, reduction in transmission TO
those most likely to end up in hospital, ICU or dead if they
> became infected.
>
> Incorporating those into the model would obviously make it
> appreciably more complex (I don't know how easily it can cope with
progressive, rather than 'step', changes in transmission, nor whether it
can cope with different transmission in sub-groups with different
prognoses), but it would seem closer to reality - albeit the actual
figures you fed in would presumably be little more than blind guesses.
>
> Those additional (earlier) effects, if valid, would presumably have had
an impact on 'new cases' by now, but there is really  no way we can
conclude very much from the daily figures we are now being told in the
UK, which derive from ever-increasing numbers of
> tests.  However, we presumably are fairly close to the time at which any
such ('early') effects should start being reflected in
> hospitalisations, ICU admissions and deaths.
>
> I think the general principle I'm talking about, of trying to model
something as close as possible to the actual situation, cannot be wrong
- but I don't know how easy it would be to implement, and
> certainly haven't got  clue as to how one would guess the relevant
parameters.  I suppose the interesting thing to do, if such a model
could be constructed, would be to explore the impact of varying those
(additional) parameters - essentially to see whether what I'm
> suggesting could/would make any appreciable difference to your
forecasts.
>
> Just one other point/question ... your ("15% reduction") forecast of
150,000 deaths by June 16th presumably implies 7.5 - 15 million
> people infected by then.  When one gets to such a level of (presumed)
immunity in the population, one is presumably getting into the
> territory where a reduction in "R0" pro-rata to the remaining
> non-immune population will start having a significant effect.  Does your
model take that into account?
>
> You, and others, might regard my suggestions as being nonsense, but it's
the best I can currently think of that might possible make your
forecasts look a bit less frightening!
>
> Kind Regards,
>
>
> John
>
> ---------------------------------------------------------------- Dr John
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> Mediscience Services       Fax:      +44 (0) 1296 738893
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