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Aggy last won the day on May 7 2020

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  1. In terms of controlling infections, you’re probably right re nhs. In terms of deaths though I disagree. In terms of covid deaths specifically, you look at lack of PPE, putting front line staff and patients at avoidable risk, leading to avoidable deaths. Lack of ventilators at the outset - and I know ventilation isn’t always used now, but it may have helped at the outset. You look at not having enough physical room to space people out safely so you’ve had people go into hospital with one thing, catch covid and die from that whilst there. In terms of non-covid deaths, we don’t know how many premature deaths there have already been and will continue to be in the next couple of years as a result of cancellation of non-covid treatment and missed diagnoses (or suicide/mental health problems/ poverty related health issues). That’s because we haven’t got enough staff predominantly but also facilities to have been able to keep things open. I should stress that’s not new and happens every year - we already have ridiculous waiting times and cancellation of operations most winters. I’m not massively convinced by your number 2, although it depends what you mean by younger ages. When we see these 18-65 deaths, almost all of them are 60 plus. In the under 40s, the deaths have been very very minimal. If you’re talking about that 50-70 age group though, I’d agree. And that’s not to say the health in the under 40s is good - I imagine lots of under 40s are well on the way to being high risk when they are in their 50s and 60s, but I’m not sure there have been enough deaths in under 40s to call poor personal health in that age group one of the four main things leading to the sheer number of deaths.
  2. 4) Years of underfunding of the nhs
  3. Shocking in terms of disappointing and sad it’s got to that point, yes. Can’t say I’m shocked though that the populace is slow to accept it/sceptical given how the politicians have handled things in the past few weeks and months.
  4. India started today on 99-3, so 46-7 on this “day 2” pitch. England now 77-7 on the same day 2 pitch. That’s 123-14 in one day, 7 wickets a piece, between two top test match sides. That ain’t to do with good bowling or bad batting.
  5. I’m not arguing with the ONS at all. I’m merely pointing out your proposed use of their statistics is flawed. You suggested my earlier post to VW was ‘misguided’ because the ONS stats tell us what the true prevalence is. I have since merely pointed out the ONS stats don’t sample care homes or hospitals, so can’t possibly tell us what the true prevalence is across the country. Since then you’ve typed out an awful lot of hot air and guff but haven’t actually said anything of substance. Unless you fancy actually answering the questions asked in my last post, I don’t think there’s much more to discuss. Your refusal to do so tells me all I need to know I think.
  6. I have genuinely lost track of what you’re on about. Can I take it from this that you’re still suggesting the ONS random samples are actually genuine random samples? Even after seeing the methodology which confirms they don’t sample care homes, hospitals or public institutions? (Not many deaths or cases in any of those right?!) Even after the methodology specifically says they “prioritise” certain areas with higher amounts of the things they are sampling for? (I mean if openly stating you prioritise areas with more of the stuff you’re testing for doesn’t scream “not random” I’m not sure what does.) Or are you now accepting the ONS random sampling isn’t actually random? If you do accept that, are you still trying to argue it is entirely accurate regardless? Or do you accept that sampling which is not random and which omits care homes and hospitals in particular, and which “prioritises” areas with more covid, cannot accurately answer the question “have we definitely got under 1,000 new infections across the whole country today?” Because if then ONS stats can’t definitively answer that question, the Zoe app can’t definitively answer that question, the official positive results can’t definitively answer that question, then what exactly can? Seems utterly bizarre to me to be arguing that we should base our strategy for coming out of lock down on statistics which don’t even bother to look at care homes or hospitals. But each to their own!
  7. So what in that says, as you suggested I said, “random samples are all but meaningless”? It literally says why and when they’re useful but also where they have their limitations for certain purposes.
  8. Yes I know and don’t disagree. The point I made in my initial post to you, as just mentioned in the reply above, is that these things are great for trends and getting the big picture. But neither the Zoe app or the ONS figures give you enough accuracy to say “we should only come out of lockdown if we have fewer than 1,000 new daily cases”. In order to say that, you need to actually know when you get to 1,000 new daily cases. And we simply don’t know with that level of certainty. That’s risky both ways - use the ONS sampling to assume we have below 1,000 new daily infections and you’re literally not taking care homes into account at all (as the ONS stats don’t sample from care homes). So we’d come out of lockdown basically hoping blindly the care homes were alright. So we come full circle - bottom line is we need to keep hospitalisations low. Lots of things help us do that, and keeping tabs broadly on community spread, and checking trends are going in the right direction, are crucial. But they aren’t the goals per se because they’re not properly measureable, certainly not to the extent that you will only allow coming out of lockdown if we have under [unmeasurable arbitrary figure ] infections.
  9. Classic YF. That’s not what my original post claimed at all is it. Did you bother to read it before announcing it was misguided? Here’s what my original post to VW actually said about the Zoe app: ”Really useful for the big picture and getting an idea of trends, and more importantly really useful for helping to ensure we keep those trends going in the right direction, but unless we test everyone everyday, it’s not accurate enough to be used for specific targets (nor is any other form of modelling we see on this either).” I have also said elsewhere that community spread and infections is important for monitoring to ensure hospitals don’t become overwhelmed. However, setting an arbitrary target such as ‘fewer than [.figure ] new daily infections’ or ‘fewer than [ figure] total infections’ if you want to use prevalence, requires you to be able to ascertain whether that target has been achieved. This works both ways. It isn’t anti lockdown or whatever deflecting rubbish you’re about to accuse me of next. If (for example) we said we should come out of lockdown if we have fewer than 1,000 new daily infections and use ONS random sampling to ascertain when we get to 1,000 new daily infections, you’re completely ignoring care homes (where there are huge numbers of the most highly vulnerable people). So nothing about my “agenda”, whatever that means. You have been saying for ages we should have a specified amount of cases as a maximum limit before we come out of lockdown, but you are yet to show any way that can determine how many cases we actually have. Instead you appear to be saying we should base the plan for coming out of lockdown on figures which literally completely ignore care homes. Which seems a strange way of approaching it to me.
  10. Ah, so patronising nonsense about gcse level stats rather than answering the question. If it helps, here’s an extract from the ons infection survey methodology section. They don’t sample care homes. And their apparently random sampling “prioritises” areas with high levels of infection. Link below just in case you want to double check whether my reading capabilities are at gcse level English standard. “Only private households are included in the sample. People living in care homes, other communal establishments and hospitals are not included. Only private households in England are included in the pilot study.” “In line with our plans to increase our overall sample size, we prioritised areas under government local restriction because of an outbreak of the coronavirus (COVID-19).” “We also boosted our sample in London, inviting 50,000 extra households to increase the household involvement rates in this area.” https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/methodologies/covid19infectionsurveypilotmethodsandfurtherinformation And if you’re worried this methodology is out of date (it isn’t), here’s a link to their bulletin in January 2021, which states “In this bulletin, we refer to the number of current COVID-19 infections within the community population; community in this instance refers to private residential households and it excludes those in hospitals, care homes and/or other institutional settings.” https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/22january2021
  11. Even the random sampling doesn’t tell you the exact number. If you widen the pool of random samples, the outcome might be different. Good for showing rough numbers and trends, but not for saying “we definitely have 999 cases today whereas we had 1,001 yesterday, let’s open up”. Comes down yet again to the point that unless you test everyone everyday, we don’t know exactly how many positive tests there are. Which is why the government, presumably advised by SAGE, have stuck to concrete targets (deaths and hospitalisations) and not arbitrary figures based on numbers we are guessing. Edit: PS, does the ONS random sampling take into account care homes, hospitals, other public accommodation?
  12. Good to hear they think it’s now going the right way too. Exactly why though we shouldn’t be using arbitrary figures to determine what happens next, and why number of new infections or prevalence/total number infected isn’t the right thing to be using as the “target”. Can you imagine if we said “we need fewer than [ ] new daily infections”, stayed in lockdown, only for methodologies to change a month later to suggest we could have been out four weeks earlier? Or, worse, if we’d come out only for methodologies to change and revise up a month too late? Really useful for the big picture and getting an idea of trends, and more importantly really useful for helping to ensure we keep those trends going in the right direction, but unless we test everyone everyday, it’s not accurate enough to be used for specific targets (nor is any other form of modelling we see on this either).
  13. Not specifically aimed at you, and I deleted “you” and used “one” for that reason. I don’t think you went looking for anybody - the point is that it’s extremely easy to find renowned scientists and experts who have opinions both ways. Point is though that we already know all of her concerns, as do members of SAGE and the plan has been announced anyway. Yes there is some risk - we know about it already and it has been weighed up against other things.
  14. Doesn’t really say anything others haven’t said before. Anyone can find an expert on Twitter who says one thing or another. Whitty et al clearly already know all of this, but have produced the “roadmap” in its current form. “Follow the science” appears to be follow whichever scientists suit ones argument. In any event, the roadmap isn’t just about hospitalisations. It quite clearly says infections are important too, but only if the rate of new infections risks overwhelming hospitals. Mutation risks, risk to the young etc - we’ve gone over it time and time again. Bird flu cases in Russia last week weren’t there? We could all hide away until we have reached this dreamworld of zero covid some aspire to and then all catch bird flu (or whatever else comes along) and die anyway. Some on here have a fascination with arbitrary numbers. Bottom line is, we went into lockdown because hospitals were apparently about to be overwhelmed, and that’s what will determine when we come out of it.
  15. Bbc suggesting four conditions to be met at each stage of coming out: “The four conditions that must be met at each phase of lockdown easing are: The coronavirus vaccine programme continues to go to plan Evidence shows vaccines are sufficiently reducing the number of people dying with the virus or needing hospital treatment Infection rates do not risk a surge in hospital admissions New variants of the virus do not fundamentally change the risk of lifting restrictions Downing Street said the four tests are currently being met so the first step of lockdown easing in England will proceed as planned on 8 March. The first stage of easing restrictions will be across the whole of England, Downing Street added, due to the current uniform spread of the virus.” https://www.bbc.co.uk/news/uk-56148160
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