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This helps highlight just how much of this is nothing more than FUD. The CDC counts real flu deaths and estimates infections. It doesn’t test for them. As a re

This helps highlight just how much of this is nothing more than FUD. The CDC counts real flu deaths and estimates infections. It doesn’t test for them. As a result you get a relatively low fatality rate. But for COVID-19 we are using only confirmed deaths and confirmed tested infections to come up with a fatality rate that seems much higher than it actually is because most infections go unreported. This is just a reality of the post-fact based world we now live in. Everything is bonkers.

mlyle 7y ago
Medical statisticians are not tards, and the math used to estimate CFRs is reasonable. Yes, there's uncertainty, because when something is massively growing, it's not meaningful to test the population at large and ordinary surveillance mechanisms are not effective yet. We also don't really have serological testing (allegedly Singapore has a good serological assay?) which doesn't help. It's worth noting that the real issue is that CFR skyrockets when the medical system saturates. With good medical care available, the CFR is still much higher than the flu but less crazy. The problem is, COVID-19 can create enough severely ill cases to saturate medical systems with uncontrolled spread.
- bobcostas55 7y ago
  >Medical statisticians are not tards This paper has 4000 citations: https://journals.lww.com/epidem/Abstract/1990/01000/No_Adjustments_Are_Needed_for_Multiple_Comparisons.10.aspx https://journals.lww.com/epidem/Abstract/1990/01000/No_Adjus...
  - mlyle 7y ago
    So? It has a point. I disagree with a lot of it, but... * The fundamental point: A study with 100 comparisons will erroneously reject the null hypothesis at p<0.05 for 5 of them, which is a good part of why we adjust for multiple comparisons. But the same issue holds if we do 100 studies, and reject null for 5 of them. One of the fundamental problems with p values is that we don't really know the baseline number of things being compared in unpublished and preliminary research, which in turn makes the p value somewhat meaningless. In effect, we've unfairly penalized the study with multiple comparisons vs. the same findings showing up from studies with individual comparisons. * Studies with multiple comparisons are great engines of hypothesis generation. Setting too high a bar for rejecting associations means that we'll possibly discard too much. * Most of our tests for multiple comparisons assume a degree of statistical independence which just isn't present. The abstract is particularly horribly written, but those three points are reasonable points. (At the same time, there's circumstances where obviously we need to adjust appropriately or get absolutely stupid, irreproducible results-- e.g. fMRI data.
enchiridion 7y ago
I keep seeing similar arguments. Does that mean China's response is based on FUD? If it is really just a flu, then why the drastic measures?
- themagician 7y ago
  Because the flu is really bad. But it’s not unusual.
  - mlyle 7y ago
    I don't remember a recent flu year that's prompted governments to weld people inside their dwellings.
    - themagician 7y ago
      Yeah, because it didn’t fit a narrative. It didn’t have a scary name. In 2018, 80,000 people died from the flu in the United States alone. 80,000. The bulk of those deaths happened in a four month window. Sometimes hundreds or thousands of people died PER DAY. Think about that for a moment. Let that sink in. There was a weekend in 2018 that likely saw more deaths from the flu in the US alone than during this entire saga globally, which started back in November.
      - mlyle 7y ago
        I don't think the Chinese government is unduly worried by narratives and scary names, but is instead inclined to be ruthlessly pragmatic. Diseases spread. Yes, in their early phases of spread, the total devastation isn't that high. Your statements would hold just as true for the early phases of the 1918 pandemic-- lots of people die from flu every year; still fewer have died than happened last year; etc. They're statements that are true until they're not. There's no guarantee of catastrophe, but the potential for it is there.
fspeech 7y ago
Read the WHO comment: Guangdong, China, tested 320000 samples with postive rate of 0.15%. So no they did not miss a lot of light cases. The death rate is real, esp for the vunerable population. Medical system will be overwhelmed if this goes unchecked.
- mlyle 7y ago
  I agree that this is likely true, but it's worth noting the big caveat: sensitivity of the tests are poor, particularly (to an unknown extent) in people with mild disease. Until we have good serological antibody testing it's going to be difficult to quantify.

mlyle 7y ago

Medical statisticians are not tards, and the math used to estimate CFRs is reasonable. Yes, there's uncertainty, because when something is massively growing, it's not meaningful to test the population at large and ordinary surveillance mechanisms are not effective yet. We also don't really have serological testing (allegedly Singapore has a good serological assay?) which doesn't help. It's worth noting that the real issue is that CFR skyrockets when the medical system saturates. With good medical care available, the CFR is still much higher than the flu but less crazy. The problem is, COVID-19 can create enough severely ill cases to saturate medical systems with uncontrolled spread.

bobcostas55 7y ago
>Medical statisticians are not tards This paper has 4000 citations: https://journals.lww.com/epidem/Abstract/1990/01000/No_Adjustments_Are_Needed_for_Multiple_Comparisons.10.aspx https://journals.lww.com/epidem/Abstract/1990/01000/No_Adjus...
- mlyle 7y ago
  So? It has a point. I disagree with a lot of it, but... * The fundamental point: A study with 100 comparisons will erroneously reject the null hypothesis at p<0.05 for 5 of them, which is a good part of why we adjust for multiple comparisons. But the same issue holds if we do 100 studies, and reject null for 5 of them. One of the fundamental problems with p values is that we don't really know the baseline number of things being compared in unpublished and preliminary research, which in turn makes the p value somewhat meaningless. In effect, we've unfairly penalized the study with multiple comparisons vs. the same findings showing up from studies with individual comparisons. * Studies with multiple comparisons are great engines of hypothesis generation. Setting too high a bar for rejecting associations means that we'll possibly discard too much. * Most of our tests for multiple comparisons assume a degree of statistical independence which just isn't present. The abstract is particularly horribly written, but those three points are reasonable points. (At the same time, there's circumstances where obviously we need to adjust appropriately or get absolutely stupid, irreproducible results-- e.g. fMRI data.

enchiridion 7y ago

I keep seeing similar arguments. Does that mean China's response is based on FUD? If it is really just a flu, then why the drastic measures?

themagician 7y ago
Because the flu is really bad. But it’s not unusual.
- mlyle 7y ago
  I don't remember a recent flu year that's prompted governments to weld people inside their dwellings.
  - themagician 7y ago
    Yeah, because it didn’t fit a narrative. It didn’t have a scary name. In 2018, 80,000 people died from the flu in the United States alone. 80,000. The bulk of those deaths happened in a four month window. Sometimes hundreds or thousands of people died PER DAY. Think about that for a moment. Let that sink in. There was a weekend in 2018 that likely saw more deaths from the flu in the US alone than during this entire saga globally, which started back in November.
    - mlyle 7y ago
      I don't think the Chinese government is unduly worried by narratives and scary names, but is instead inclined to be ruthlessly pragmatic. Diseases spread. Yes, in their early phases of spread, the total devastation isn't that high. Your statements would hold just as true for the early phases of the 1918 pandemic-- lots of people die from flu every year; still fewer have died than happened last year; etc. They're statements that are true until they're not. There's no guarantee of catastrophe, but the potential for it is there.

fspeech 7y ago

Read the WHO comment: Guangdong, China, tested 320000 samples with postive rate of 0.15%. So no they did not miss a lot of light cases. The death rate is real, esp for the vunerable population. Medical system will be overwhelmed if this goes unchecked.

mlyle 7y ago
I agree that this is likely true, but it's worth noting the big caveat: sensitivity of the tests are poor, particularly (to an unknown extent) in people with mild disease. Until we have good serological antibody testing it's going to be difficult to quantify.