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When will this shit end?


Chrisp1986

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16 minutes ago, steviewevie said:

Covid-19: Growth in cases may be slowing in England

https://www.bbc.co.uk/news/health-54366478

They think R might have fallen to 1.1. If that’s the case we might be able to push it below 1 by playing whack-a-mole, but I think the local lockdowns would probably need to get more strict for that to work. Also, some are suggesting there’s only weak evidence that the rule of 6 has suppressed R to this extent. 

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Just now, Fuzzy Afro said:

They think R might have fallen to 1.1. If that’s the case we might be able to push it below 1 by playing whack-a-mole, but I think the local lockdowns would probably need to get more strict for that to work. Also, some are suggesting there’s only weak evidence that the rule of 6 has suppressed R to this extent. 

So our common sense has done the rest then ?!! 

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26 minutes ago, crazyfool1 said:

Mine is just a few pages of data like this ... don’t know what it’s supposed to tell me ? That my phone checked if I had been exposed umpteen times on 24th sept at 9.39 ? Why does it not just check once ? 

795BB758-051A-4908-85E9-1110B98B33B9.png

If you go into each one it will allow you to drill down to tell you how many keys it’s shared with you and more importantly how many you matched with. 

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37 minutes ago, steviewevie said:

Covid-19: Growth in cases may be slowing in England

https://www.bbc.co.uk/news/health-54366478

The graphs are the data set they used to come to that conclusion, well graph B is. Graph A would show an R rate at 1.4. The R=1.7 and R=1.1 are the slopes within the little regions on graph B. But the data there is fairly noisy, and the lines don't join up in a sensible way. Whereas graph A gives a more coherent picture across time periods and has no slowing down at all.

For reference the 2 graphs mean:

A models fit to REACT-1 data for sequential rounds; 1 and 2 (yellow), 2 and 3 (blue), 3 and 4 (green) and 4 and 5 (pink). B models fit to individual rounds only (red). Vertical lines show 95% confidence intervals for observed prevalence (black points).

 

In the report by Imperial College they show the following results. Using data from rounds 4 and 5 and we estimate a doubling time of 10.6 (9.4, 12.0) days covering the period 20th August to 26th September 2020 using a model of exponential growth and decay. This
4 corresponds to a reproduction number R of 1.47 (1.40, 1.53) (Table 2, Figure 2A). However, using only the most recent data we observe a more gradual slope (Figure 2B), with an estimated reproduction number of 1.06 (0.74, 1.46) and 63% probability that R is greater than 1 (Table 2).

 

They also state that prevalence of swab positivity had increased to over 1 in 200 across the population in England.

 

So whilst they said before that R=1.7 (and now down to 1.1) that was based on the graph showing a noisy data set whereas it’s probably been more in the middle when using data covering the period as a whole and doesn’t really show a slowing down. 

75FE225F-10BB-49AD-996C-2672353A0295.png

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It’s not hyperbole to suggest that today’s case count might be the most important since the pandemic began more than half a year ago.

 

We’ve caught up on the reporting backlog now and today’s case numbers will mainly be reporting positive tests from Tuesday 29th September, meaning that it should reflect transmission after the rule of six came into force just over two weeks ago.

 

Last week we posted 6,633 infections on the Thursday. We really want to be squeezing that 7 day moving average now such that it’s growing by 10% or less per week, preferably not growing at all. My guess is that we might see about 9,000 cases today, but for a good result, we really want 7,500 at an absolute maximum or preferably below 7,250.

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8 minutes ago, Fuzzy Afro said:

It’s not hyperbole to suggest that today’s case count might be the most important since the pandemic began more than half a year ago.

 

We’ve caught up on the reporting backlog now and today’s case numbers will mainly be reporting positive tests from Tuesday 29th September, meaning that it should reflect transmission after the rule of six came into force just over two weeks ago.

 

Last week we posted 6,633 infections on the Thursday. We really want to be squeezing that 7 day moving average now such that it’s growing by 10% or less per week, preferably not growing at all. My guess is that we might see about 9,000 cases today, but for a good result, we really want 7,500 at an absolute maximum or preferably below 7,250.

Yes that is hyperbole. It’s just another day, no more important than the last. Just because the cases might or might not meet the arbitrary target that you’ve set doesn’t mean it’s a good or a bad day. 
Putting increased pressure on any one specific days set of figures isn’t helpful and beneficial in the long run when you need to look at trends and more sets of data.

 

Also a ‘good’ set of results isn’t going to be 7,500 new cases of COVID, when 2 weeks ago we were seeing 3,100. Especially when a fairly sized small portion of those 7,500 people could see long term implications of that positive result. 

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57 minutes ago, crazyfool1 said:

 

Mine is just a few pages of data like this ... don’t know what it’s supposed to tell me ? That my phone checked if I had been exposed umpteen times on 24th sept at 9.39 ? Why does it not just check once ?

 

Where were you at that time? 
 

I get multiple pings at random times of the night so assuming it’s picking up my neighbours phones but not getting a covid flag. 
 

For that many pings at once I’m guessing your phone was in the work locker room and detecting everyone else’s phone at the same time. 

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27 minutes ago, Ozanne said:

The graphs are the data set they used to come to that conclusion, well graph B is. Graph A would show an R rate at 1.4. The R=1.7 and R=1.1 are the slopes within the little regions on graph B. But the data there is fairly noisy, and the lines don't join up in a sensible way. Whereas graph A gives a more coherent picture across time periods and has no slowing down at all.

For reference the 2 graphs mean:

A models fit to REACT-1 data for sequential rounds; 1 and 2 (yellow), 2 and 3 (blue), 3 and 4 (green) and 4 and 5 (pink). B models fit to individual rounds only (red). Vertical lines show 95% confidence intervals for observed prevalence (black points).

 

In the report by Imperial College they show the following results. Using data from rounds 4 and 5 and we estimate a doubling time of 10.6 (9.4, 12.0) days covering the period 20th August to 26th September 2020 using a model of exponential growth and decay. This
4 corresponds to a reproduction number R of 1.47 (1.40, 1.53) (Table 2, Figure 2A). However, using only the most recent data we observe a more gradual slope (Figure 2B), with an estimated reproduction number of 1.06 (0.74, 1.46) and 63% probability that R is greater than 1 (Table 2).

 

They also state that prevalence of swab positivity had increased to over 1 in 200 across the population in England.

 

So whilst they said before that R=1.7 (and now down to 1.1) that was based on the graph showing a noisy data set whereas it’s probably been more in the middle when using data covering the period as a whole and doesn’t really show a slowing down. 

75FE225F-10BB-49AD-996C-2672353A0295.png

I think it has narrowed though. Whether its enough is another thing, but its clear that the North West and North East areas are massively bumping things up as well. 

 

Hopefully it is showing that the rule of six and higher public perception is enough to improve things on its own

 

Also the previous study of 1.7  was what made Whitty and Valence say that it could double every week. Its clearly not doing that at least

Edited by zahidf
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5 minutes ago, squirrelarmy said:

Where were you at that time? 
 

I get multiple pings at random times of the night so assuming it’s picking up my neighbours phones but not getting a covid flag. 
 

For that many pings at once I’m guessing your phone was in the work locker room and detecting everyone else’s phone at the same time. 

Ah ... I’d gone for my break or to the toilet .. passing the lockers ... that’s gonna be it ... well done detective squirrel 🐿 :) ., it does show quite a few have installed the app at work which is good but really should have phones on them I would think and not in lockers 

Edited by crazyfool1
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https://www.theatlantic.com/health/archive/2020/09/k-overlooked-variable-driving-pandemic/616548/

 

 In an overdispersed regime, identifying transmission events (someone infected someone else) is more important than identifying infected individuals. Consider an infected person and their 20 forward contacts—people they met since they got infected. Let’s say we test 10 of them with a cheap, rapid test and get our results back in an hour or two. This isn’t a great way to determine exactly who is sick out of that 10, because our test will miss some positives, but that’s fine for our purposes. If everyone is negative, we can act as if nobody is infected, because the test is pretty good at finding negatives. However, the moment we find a few transmissions, we know we may have a super-spreader event, and we can tell all 20 people to assume they are positive and to self-isolate—if there are one or two transmissions, there are likely more, exactly because of the clustering behavior. Depending on age and other factors, we can test those people individually using PCR tests, which can pinpoint who is infected, or ask them all to wait it out....

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8 minutes ago, crazyfool1 said:

Ah ... I’d gone for my break or to the toilet .. passing the lockers ... that’s gonna be it ... well done detective squirrel 🐿 :) ., 

It’s a good sign that lots of your colleagues also have the app

Edited by squirrelarmy
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9 minutes ago, zahidf said:

I think it has narrowed though. Whether its enough is another thing, but its clear that the North West and North East areas are massively bumping things up as well. 

 

Hopefully it is showing that the rule of six and higher public perception is enough to improve things on its own

 

Also the previous study of 1.7  was what made Whitty and Valence say that it could double every week. Its clearly not doing that at least

Is it showing it’s improving things though? Because if you go from the first graph it shows prevalence is increasing slightly which is probably down to NW and NE, they even state in their own report that prevalence of swab positivity has increased, 7 fold increases in over 65s and all regions of the country showed a rise with highest prevalence in the North West and five-fold increase in prevalence in London over this period. With the caveat of indications in recent data showing that the rate of increase in prevalence may have slowed.

 

Yes it’s not doubling every week like the CMO and CSO said could happen which would indicate that R wasn’t 1.7 like in the previous report so we should take with a pinch of salt the current report indicating a standalone R of 1.1 now. 

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17 minutes ago, squirrelarmy said:

Where were you at that time? 
 

I get multiple pings at random times of the night so assuming it’s picking up my neighbours phones but not getting a covid flag. 
 

For that many pings at once I’m guessing your phone was in the work locker room and detecting everyone else’s phone at the same time. 

Sleep walking!? 😉

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17 minutes ago, squirrelarmy said:

Where were you at that time? 
 

I get multiple pings at random times of the night so assuming it’s picking up my neighbours phones but not getting a covid flag. 
 

For that many pings at once I’m guessing your phone was in the work locker room and detecting everyone else’s phone at the same time. 

How does it explain this then, been stuck working at home and pinged again when I woke up. I wouldn't mind but I haven't left the house 😆

Screenshot_20201001-092740.png

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27 minutes ago, Ozanne said:

Yes that is hyperbole. It’s just another day, no more important than the last. Just because the cases might or might not meet the arbitrary target that you’ve set doesn’t mean it’s a good or a bad day. 
Putting increased pressure on any one specific days set of figures isn’t helpful and beneficial in the long run when you need to look at trends and more sets of data.

 

Also a ‘good’ set of results isn’t going to be 7,500 new cases of COVID, when 2 weeks ago we were seeing 3,100. Especially when a fairly sized small portion of those 7,500 people could see long term implications of that positive result. 

I mean, 7500 cases would still be 7500 too many. That goes without saying. But my point is that if it is 7500 and there’s no reporting backlog, that would constitute emerging evidence that the rule of six is slowing the growth of the second wave, which would be good news. 

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1 minute ago, Fuzzy Afro said:

I mean, 7500 cases would still be 7500 too many. That goes without saying. But my point is that if it is 7500 and there’s no reporting backlog, that would constitute emerging evidence that the rule of six is slowing the growth of the second wave, which would be good news. 

yep I agree ... taking small crumbs of good news is massively important at the moment when there is so much bad news about ... it not necessarily good news but its not such bad news as previously .... so much data about that we can easily find negatives but the positives need to be balanced to help us as humans 

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5 minutes ago, squirrelarmy said:

How close to your house are your neighbours 

Semi detached, the one next door doesn't have the app because they never leave the house. I don't know how it all works to be honest, just hope I'm lucky enough to not pickup a match. It's like opposite tinder 😆

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