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IOM Covid removing restrictions


Filippo

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Just now, swoopy2110 said:

The Government's technology department needs such an overhaul. Everything is just so poor.

No live vaccine booking system. No live way to book a COVID test. Dashboard that can't cope.

To be fair to them, half the stuff they've moved to is hosted by Microsoft.

It's just an Office 365 form for a vaccination booking.

Something has really broken with the PowerBI dashboard though.

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1 minute ago, Nom de plume said:

Sorry guys, I’ve hacked the dashboard.

 

Ah, the infamous Nom de pube. 

Philanthropist, social justice warrior, PHD in medicine & social science.

and an illustrious cyber security expert. 

The cocktail of perfection. 

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3 hours ago, wrighty said:

Same goes for length of stay.  You've used 9.42 days.  I think for youngsters it's a bit shorter.

I mentioned in the report:

"However, when estimating likely demand for Nobles beds, for planning purposes I would heavily skew calibration numbers towards a reasonable worst case scenario."

With regard to 9.42 days I know it is bit longer than would expect for 2-17yo, and I hope it does not happen but I am factoring in some spilling over into other demographics. Again comes back to, whatever the number is how can we make it as small as possible and answer to that is clear, namely:

All 2+2 High Risk groups do whatever they can to prevent becoming infected during the present natural wave.

3 hours ago, wrighty said:

Finally, R.  3.35 may be about right as an R0, but your initial susceptible population of 14765 will be 'diluted' by 70000 who are vaccinated.  This should reduce the effective R to something rather less.  It might be difficult to do, but what's the R if 'admitted to hospital because of covid' is the case definition, rather than a positive PCR?

With model I posed is to consider 0 vax group (which mainly be kids) which I put at 14,765, start ~85K population, assume all 1st jab also get 2nd jab (prior to infection) and also net out 2+2, and estimate had 5K real world infections so far. [With 5K DHSC may have better estimate if the anti-body tests were used and analyzed]. The existing 2+2 separate themselves from 0 jab and wave allowed to evolved (as it happening). Regarding issues such as topology of social networks with society, level of risk-aversion and how how that feeds into 'effective R', put explanation of approach at:   

https://sites.google.com/webcabcomponents.com/seir-model-of-iom-natural-wave/home/effective-r-herd-immunity-and-seir-model

So far no one queried setting R=1.1 on Day 37, which I have least faith in (and put hand up it is a technical smudge). R will shift issue is will it be net result over tail end of infection curve represent by 'effective R' = 1.1 shift on Day 37. Interested in views regarding this, i.e. behavioral science on aggregate level of large populations exposed to SEIR Wave of infection.

Interested in views regarding this, i.e. behavioral science on aggregate levels on large populations exposed to SEIR Wave of infection with mandatory mitigations.

[People will freak out, and rightly so, issue is % of them, to what degree and when]

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Just called the Cabinet Office to obtain figures via force. 

762 new cases. 

1,847 Active Cases

12 in hospital

32 in ICU.

..... Although they did confirm that Tim Baker MHK has calculated the figures today, therefore I would take these as a pinch of salt and await official confirmation.

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3 hours ago, wrighty said:

My conclusion is that this model is too unreliable to be used as a predictive tool - I looked at it last year and thought the sensitivity of the input variables was too high then.

Scientific Advisory board of Fairfax Republic has accepted this model as a useful tool with regard to its members making risk adjusted mitigation judgements for the proposed impended Natural Wave within IoM (model put together 1st July, planning started post 16th June after '1d&release' vote in IoM). We established protocols regarding our testing program, redesign our social networks and policies with regard to interaction with any Islanders not members of Fairfax Republic. As an act of good will decided to share with our fellow Islanders our calibration of standard SEIR model, did so in good faith which they can use as they see fit.

This Monday, we will enact further internal measures in anticipation of the peak infectious period of the Natural Wave in the IoM.     

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3 minutes ago, BenFairfax said:

I mentioned in the report:

"However, when estimating likely demand for Nobles beds, for planning purposes I would heavily skew calibration numbers towards a reasonable worst case scenario."

With regard to 9.42 days I know it is bit longer than would expect for 2-17yo, and I hope it does not happen but I am factoring in some spilling over into other demographics. Again comes back to, whatever the number is how can we make it as small as possible and answer to that is clear, namely:

All 2+2 High Risk groups do whatever they can to prevent becoming infected during the present natural wave.

With model I posed is to consider 0 vax group (which mainly be kids) which I put at 14,765, start ~85K population, assume all 1st jab also get 2nd jab (prior to infection) and also net out 2+2, and estimate had 5K real world infections so far. [With 5K DHSC may have better estimate if the anti-body tests were used and analyzed]. The existing 2+2 separate themselves from 0 jab and wave allowed to evolved (as it happening). Regarding issues such as topology of social networks with society, level of risk-aversion and how how that feeds into 'effective R', put explanation of approach at:   

https://sites.google.com/webcabcomponents.com/seir-model-of-iom-natural-wave/home/effective-r-herd-immunity-and-seir-model

So far no one queried setting R=1.1 on Day 37, which I have least faith in (and put hand up it is a technical smudge). R will shift issue is will it be net result over tail end of infection curve represent by 'effective R' = 1.1 shift on Day 37. Interested in views regarding this, i.e. behavioral science on aggregate level of large populations exposed to SEIR Wave of infection.

Interested in views regarding this, i.e. behavioral science on aggregate levels on large populations exposed to SEIR Wave of infection with mandatory mitigations.

[People will freak out, and rightly so, issue is % of them, to what degree and when]

The reason that we are not querying R37=1.1 is that R0=3 is the cause of the explosion, I think that is first order issue with the model.  The model needs R0 to be representative of transmission between member of the population, when 75% of the population is immune then you need to adjust R0 (or the model initial values).  There is a huge difference between the two approaches.  Going back to basic principles on R0

Current state of the iom, assuming R0=4 and one large population

1st gen A gets covid, meets B1, B2, B3 ad B4. B2-4 are vaccinated, only B1 gets covid.

2st gen B1 meets C1, C2, C3, C4... and so only one person if gen gets covid.

Your model instead assumes with R=3 and none of the vaccinated meet the infected

1st gen A gets covid, meets B1, B2, B3. No one is vaccinated everyone gets covid, the number with covid explodes.

The main people the infected (kids) interact with are their parents (particularly in the summer holidays), and they are vaccinated, this will hugely slow down the spread.

The reason I suspect there has been an outbreak is that a few 2+2 people with covid have silently spread it amongst the iom population, no one really noticed for a few weeks until it started to infect enough to be picked up, then people got worried.  Then everyone started to get tested and now there are loads being reported.  Hopefully now people will start taking some sensible measures and the infection rate will drop.

I wish they hadn't introduced 2+2 at the end of June as could have been avoided so more adults could have been vaccinated but I think the model is giving overly scary predictions.  These models are hugely sensitive to R0 and the assumptions you make about the population mixing.  I suspect that as the IOM has a higher % vaccine coverage than the UK it will do better than the UK.

 

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