4 ms·

Related pieces by John PA Ioannidis: - Coronavirus disease 2019: the harms of exaggerated information and non‐evidence‐based measures[1] - A fiasco in the mak

by jkh1 7y ago

Related pieces by John PA Ioannidis: - Coronavirus disease 2019: the harms of exaggerated information and non‐evidence‐based measures[1] - A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data[2] There are two ways of getting the answer to the question: get relevant data to make reliable predictions (e.g. test for prevalence in the population) or run the experiment (which some governments seem prepared to do) 1- https://onlinelibrary.wiley.com/doi/abs/10.1111/eci.13222 https://onlinelibrary.wiley.com/doi/abs/10.1111/eci.13222 2- https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/ https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-a...

fsh 7y ago
One problem with this is that in the early stages of the spread you would have to run hundreds of thousands of tests daily in order to get statistically significant results. This is clearly impossible with the available lab infrastructure. And this is ignoring the possibility of getting false positives. Maybe it will be possible to get quantitative results with fast antibody tests in later stages, but at that point it is probably much too late to act.
skat20phys 7y ago
I have a lot of respect for Ioannidis's work, and kind of lean toward his perspective in some respects, but I think he's misrepresenting certain data and missing certain points. He's right to point to the Diamond Princess Cruise ship for example, but his statistics are already out of date. As of yesterday, 8/712 infected had died; if you expand this to the Grand Princesss, it/s 10/800, which is at 1.1-1.25% CFR. This is a lot bigger than the statistics Ioannadis cites, and greater than the flu. There are some issues about how to extrapolate the cruise ship population to other populations, but that isn't straightforward (cruise ship passengers are probably older on average, but also might be healthier and/or wealthier). In any event, that number can only increase. The other issue is that regardless of CFR in the population, the experiences of various locations points to the threat. That is, we can argue with Ioannadis all he wants about CFR and so forth, but in the end, if places are crumbling under the weight of hospital visits, it doesn't matter. As someone else pointed out, fatality rates are only part of the picture, and in this case it's important. At some level, it's not the the fatalities per se that are the sole problem, it's the much greater percent of cases that require hospital care. It's not like CFR is a fixed statistic that applies everywhere all the time anyway; it will depend on resources and other things. Finally, there's been a lot of discussion by Ioannadis and others about costs of restrictions and so forth but little data about that that's pointed to (even though it's available). For example, if you look into data about the Great Depression and Great Recession, it appears that overall there was a decrease in mortality that followed. Data on health effects of recessions is actually pretty clear: although there tends to be an increase in suicide and mental-health related deaths (e.g., drug overdoses), there's a much bigger decrease in deaths due to things like motor vehicle accidents, cardiovascular events, work-related deaths, and so forth. So this benefit-cost mortality analysis, as morbid as it is, doesn't necessarily play out in the way Ioannadis assumes.

by jkh1 7y ago

fsh 7y ago

One problem with this is that in the early stages of the spread you would have to run hundreds of thousands of tests daily in order to get statistically significant results. This is clearly impossible with the available lab infrastructure. And this is ignoring the possibility of getting false positives. Maybe it will be possible to get quantitative results with fast antibody tests in later stages, but at that point it is probably much too late to act.

skat20phys 7y ago

I have a lot of respect for Ioannidis's work, and kind of lean toward his perspective in some respects, but I think he's misrepresenting certain data and missing certain points. He's right to point to the Diamond Princess Cruise ship for example, but his statistics are already out of date. As of yesterday, 8/712 infected had died; if you expand this to the Grand Princesss, it/s 10/800, which is at 1.1-1.25% CFR. This is a lot bigger than the statistics Ioannadis cites, and greater than the flu. There are some issues about how to extrapolate the cruise ship population to other populations, but that isn't straightforward (cruise ship passengers are probably older on average, but also might be healthier and/or wealthier). In any event, that number can only increase. The other issue is that regardless of CFR in the population, the experiences of various locations points to the threat. That is, we can argue with Ioannadis all he wants about CFR and so forth, but in the end, if places are crumbling under the weight of hospital visits, it doesn't matter. As someone else pointed out, fatality rates are only part of the picture, and in this case it's important. At some level, it's not the the fatalities per se that are the sole problem, it's the much greater percent of cases that require hospital care. It's not like CFR is a fixed statistic that applies everywhere all the time anyway; it will depend on resources and other things. Finally, there's been a lot of discussion by Ioannadis and others about costs of restrictions and so forth but little data about that that's pointed to (even though it's available). For example, if you look into data about the Great Depression and Great Recession, it appears that overall there was a decrease in mortality that followed. Data on health effects of recessions is actually pretty clear: although there tends to be an increase in suicide and mental-health related deaths (e.g., drug overdoses), there's a much bigger decrease in deaths due to things like motor vehicle accidents, cardiovascular events, work-related deaths, and so forth. So this benefit-cost mortality analysis, as morbid as it is, doesn't necessarily play out in the way Ioannadis assumes.