Jump to content
House Price Crash Forum


  • Content Count

  • Joined

  • Last visited

About katchytitle

  • Rank
    HPC Regular

Recent Profile Visitors

934 profile views
  1. on the 17,000 to 9bn - the maths says its +/- 1% accurate assuming a distributed model (big assumption) but as I understand you can do some maths to overcome this and I'm sure the sample size would have to rise. But the point I'm making at a country/ town level is - do you need large scale testing, sampling at 100K in the UK is probably enough but people don't trust the ONS figures? What about covid antibodies...why wouldn't we be doing this analysis for that? Caveat with the tests are still crap (so we do may need to do each person multiple times and take an average) but we could determ
  2. But it would work to a 1% accuracy right? So in your example, less than 1% of people are astronauts so you need to up your sample size. So in covid, you wouldn't see the first 1% of any cases but given exponential increase and daily measuring you'd see it pretty quickly?
  3. I'm not making the point that this is the amount of testing we need. I'm suggesting that population size and sample size are not connected. So if you need to check a local cluster for instance - you'd come into a town check 400 at random in a couple of hours. You'd know how many people in the local area had covid to a +/- 5% accuracy. We don't actually have real test and trace from what I understand. Similarly, if you scaled up as we have done, you should have enough data to stratify by post code age, sex etc to get a larger view for localised out breaks or a country wide view if done a
  4. I'm trying to understand this point. Do you mean to get the stratified view for age or sex or airport arrivals etc? I agree, but then we measure way more than 16,000 people anyway so some of this is already collectable as the ONS shows - so we should have accurate data. I'm inclined to look at data with no political or media filter. The ons is probably right..with the caveat that spreading exponentially means even low "doubling rates" of a virus could infect the entire country in a matter of weeks from a small starting position. At the 95% confidence level (like the ONS) you only need samples
  5. Code seemed fine according to nature - although badly written as a monolithic function. If anyone has ever built something of value, this is just how it is until someone has money or time to clean it up https://www.nature.com/articles/d41586-020-01685-y Lockdown skeptics take the view that the model can generate non repeatable results due to bugs.. https://lockdownsceptics.org/code-review-of-fergusons-model/ Unless you're a coder and epidemiologist its hard to know what matters here...
  6. But this is what I mean - I've given a simple example to show how low it is as a base case. Population sizes do not really affect this number. If you want to test by age/type of activity/obesity/ethnicity/ hospital / north/ south/ towns/ airport arrivals etc - it doesn't matter you just need to get that dataset - the sample size remains low for each case. Surely we record age (DOB) for each Covid test for instance, so then you can just split this data by age easily with your sample sizes same for post codes, ethnicity/ hospital vs public The press and govt keep banging on about test
  7. Maths tells us that sample size is not related to population size. It takes 17000 (truly) random tests to work out how many people have covid in a population of 9bn to a 1% accuracy. Even if tests are not good and need to be performed 4 times on those people, seems pretty simple for any western country to do this. Even to check how many people have covid in the UK you need to test 16700 people and you get an answer with 1% accuracy.... all you need to do is take the test results you already get and randomize them and hey presto, you know the percentage of the population that have co
  8. But you included pensions - people paid in their national insurance for 40 years to receive that. The government obviously mismanaged it, but they are just receiving the money they paid, not receiving benefits for nothing. The problem is always govt mismanagement - you might think its expensive to provide UBI, but if we can work with robots and AI then all it requires is taxing this work rather than the money benefiting a very small group of elite investors who will have way more money than they could possibly spend in their lifetimes or give to their children.
  9. There's always 2 sides to this and its best to pretend to be on both sides to see that things are not so black and white. Covid is new - frankly it could do anything as it spreads. Random mutations could allow it to become more infectious more easily or it could peter out. But when faced with an unknown unknown you need to stop and evaluate the tail risks which "might" wipe out your population. So on the face of it, a total lockdown is an appropriate response over and above a virus like the flu each year. If you think linearly, then you would say well, it hasn't killed more people t
  10. Just imagine...LoL. Everyone walked out alright - no protests and average salaries paid for 3 months. The problem will be bringing the prols back to work.
  11. You speak about these figures as if they are already set - I'm impress that you be so definitive when neither the CDC or WHO can confirm exact infection rates. I was listening to an interview with a British man in Wuhan who had Covid-19 before it was sexy back in Nov 19. He said he felt like he had "the flu" and his lungs felt like "paper". He went to the hospital, they gave him an inhaler, he didn't really use it - and recovered after 8-10 days. No doctor gave it a second thought in Wuhan. There is NO way anyone knows how many people have been infected already and be asymptomatic or in
  12. If you tested people for flu in flu season I would expect rates to be even quicker. Measuring infection gives you no idea how many people have already had it and recovered. ITs just the media making people stare at a counter every day so they can sell you ads - mass hysteria. Old and ill people die of the flu every year - I don't think the media gave a toss about that. All of a sudden this gets to be a story that runs and runs - saves them hunting for other stories - how's that war in Yemen going? Turkey just let immigrants cross into the EU from the middle East and Africa with no limits..it m
  13. Its easy to "predict" stuff if we all just draw straight line graphs - population increasing, religion dying, fertility collapsing. We all need a narrative which fits into our personal experience and the market is there to provide it to you. The older we get the more we understand, but the less we can think of new ideas, constantly seeing the world as a recycling of what we understand. I have often thought about the ideas in this book, but I've come to the conclusion that the future is in a practical sense unknowable, especially the further out you try and predict (e.g 30 years etc). Coul
  14. I'm sure someone has already said this, but the CEO who resigned was called Peter Crook - you couldn't make it so obvious, even in a novel.
  15. I'm sure IVF facilities will continue to boom as sperm counts and fertility continue to collapse....
  • Create New...

Important Information

We have placed cookies on your device to help make this website better. You can adjust your cookie settings, otherwise we'll assume you're okay to continue.