Our Own Covid-19 Epidemiological Model

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• While much of the analysis involves uncertainty, it's not to the extent of the range between the high end and the low end you mention. In countries which have not lost control (China, South Korea, New Zealand, etc), contact-tracing is used to find people potentially infected by known cases and efforts are made to check where an infected person has acquired the infection. If there were a huge number of asymptomatic cases, the symptomatic cases would seem to appear at random. Instead the path of contagion is usually clear, so this limits the proportion of asymptomatic cases. Note also that in some parts of the world quite a large proportion of a local population has been tested. so it's not just that we only know about asymptomatic cases because of their contact with symptomatic ones.

  • Contact tracing is a bizarre myth that some governments have used to make themselves look good and ours is about to use because it can't think of anything else. There is good evidence a large proportion of people are asymptomatic and so never get tested. There's good evidence the sensitivity of the test might be as low as 70%. So let's say 50% are never tested and 30% of the 50% who are tested are false negatives. The first 100 infections then go: 50 not spotted, 15 not traced as false negative. So already we are at only 35% success. Then the contacts of that 35% are only 80% traced... The infection slows but that's all. Whatever happened in South Korea it wasn't track and trace.

    • Well then, consider the Diamond Princess. nearly 20% of the people on board tested positive, with about 400 asymptomatic. If there are 50 asyptomatic cases for each symptomatic one, there should have been only about 14 symptomatic cases. There is plenty data which all points in the same direction - the asymptomatic cases are only sightly more than the symptomatic ones.

  • Dear Charles, if you believe the numbers coming out of China, I have a bridge to sell you.

• Say thirty assumptions, each with ten plausible ranges. So the possible combinations are huge (30 million?). So the chance Ferguson got it right is the same chance as him winning the Lottery tomorrow night. Zero. And the chances the infection will look different are essentially 100%. Yet nobody in government or advising government seems remotely interested in that simple fact.

• It's worse than that. Many of these factors work exponentially, so even if you got every single factor to within 10% of the true value, your results would still be utter shit.

  The difference between a re-infection rate (R) of 1.9 and 2.1 (i.e. 10%) is incredibly significant.

  See also climate models.

• The problem with these epidemic models is the suggestion that analysis using aggregate functions will yield meaningful results. Radioactive decay in even a gram of an element is precisely predictable. Human behaviour is utterly unpredictable, which is why economic predictions always fail to see the next crash coming even when it's right around the corner. People sicken and die when they feel like it, not because an atomic clock tells them to. "Excess deaths" is just another statistic in an illusory quest for certainty.

• A highly complex model that is extremely dependent on assumptions (as all models are) is based on a few critical ones (infection and lethality rate) we don't understand. Yeah, let's re-arrange the world based on that. The more I read about the Kung Flu, the more I'm struck by how confusing the information is. Some people report data that includes China, who we know lies about the virus. Our lethality info is dependent on understanding how many people have been infected, which is bollocks on stilts. And everyone is keeping score differently. In the U.S. if you die and there's a chance you were exposed, you're scored as a virus fatality. God only knows if that doubles the rate or only adds 10-20%. Get out your fucking Ouija board, it's probably a better indicator.

  • "...In the U.S. if you die and there’s a chance you were exposed, you’re scored as a virus fatality..."

    I read an article at the weekend which suggested that US hospitals could claim from Medicare/Medicaid at the rate of $5000 per flu patient, $13000 per 'standard' Covid-19 patient, and $39000 per Covid-19 patient treated in an intensive care unit.

    If that is true (or even approximately true), then the US statistics do not come as a total surprise.....

• It seems obvious to me that we're far too far down the line to use track and trace. Lets take a low end estimate of 100k infected. Someone has to find all of them, and then find all the people each of them met in the last fortnight, and then check their contacts. It's vastly too many to deal with. And if the number of infected people is higher it gets worse.
  Track and trace can only work at the beginning of an outbreak when there are few cases to follow up.
  And even then you will have to keep it up until the disease dies out in the rest of the world, because new cases will be entering the country all the time.

• I think the article is less about constructing “a model” and more about “constructing the picture of where we are”.

  A model will allow you to see the varying outputs as you vary the assumptions.

  If you knew the values of the key parameters you could get an output, and by wriggling the values of the key parameters (to account for measurement errors) you can see the volume of uncertainty arising.

  Then you wriggle all the other parameters and you end up almost certainly discovering that the space of likely outcomes is so enormous as to be useless...

• The number affected by the disease (as opposed to infected by the virus) serious enough to warrant medical attention ranging from little to intensive, is less than 0,5% of any population and deaths are around 0,02% of any population.

  You don’t need a computer model, just Darwin and look at the evidence. Then with pen, paper, pocket calculator, and the published figures of reported cases, deaths and population sizes work out the percentages.

  In other words the insistance that Covid-19 was/is a dangerous virus to the population at large was/is false, and was never was supported by the data. Certainly not supported by outcome.

  In fact the virus is a classic example of Darwin’s Theory. Genetic mutation gave it characteristics to be best adapted to its environment to endure most successful reproduction rate. It doesn’t let the majority of people know they have it, or at most symptoms are very mild, does not immobilise or kill except rarely, and people go about their lives (or did!) spreading it. The virus is only debilitating or fatal in those with low mobility anyway so it has little effect on its reproductive rate. More severe virus which cause serious disease and early death, don’t do well in today’s environment of early recognition, quarantine, hygiene.

  Economy and society collapsed for a mild, mostly benign micro-organism.

  • "In fact the virus is a classic example of Darwin’s Theory. Genetic mutation gave it characteristics to be best adapted to its environment to endure most successful reproduction rate."
    It's probably nowhere near that yet. Viruses make the step from animals to humans quite often, I expect, but almost always have a reproduction rate less than 1. Maybe variants of this one have made the leap before, and failed to stick. This time, Covid-19 has a reproduction rate >1 in human societies. Lucky virus. But it isn't fine tuned for transmission yet.