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Axiom of Choice

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  1. We need to set up a shaggy bevo fund and rent a country estate for Cacti to go ride this thing out.
  2. I think hospital loading is a valid point in favor of continued shutdown/isolation for all.
  3. The point did not say the doubling rates would not last more than a month. It said they have not in the harder hit countries. This is a true statement. And all one would need to do to get the overall intent and to understand that I did address the point you claimed I did not address is to read the following point. You have offered no evidence that isolation measures are the only reason this is true. I have offered some evidence that isolation measures are not the only reason this is true.
  4. I addressed the point about isolation measures and their impact on the slowing of death rates in the post you replied to.
  5. We currently have a large amount of data collected from many thousands of cases across multiple nations & conditions. Here are some of the things we have known and are getting additional confirmation on: We know that people under 20 are at very low risk of hospitalization and death from CV. We know that more than 80% of the CV related deaths will likely be among people over 65 years old (see above link). Of those who have died across all age groups, the vast majority have pre-existing medical conditions. We know that the doubling every 3-4 days of daily death rates and new cases have not sustained past about ~1 month of initial reported deaths in the harder hit countries. Death rates and new case reports seem to plateau and decline around this point. Rates of daily reported deaths should lag a couple of weeks behind new case rates, as it has a long incubation period and death follows exposure by several weeks on average. This means we should see significant impacts of isolation measures on death rates kick in around 3 weeks after implementation of isolation measures. Yet death rates began to slow down significantly in less than two weeks of implementation of widespread isolation measures in Italy and Spain. The above is relevant because this information is indicative of a pandemic that is mostly (but not exclusively) killing people who were already close to death. This is one of the reasons why the death rates will not continue to double every 3-4 days for very long, because this pool of people does not double along with it. To put another way, if we take the total number of deaths in April of 2019 and use it to make a projection for the total number of deaths in April 2020, it would not be a matter of simply adding the number of CV related deaths to the April 2019 amount to get an accurate estimate for April 2020. There will be a bump in April 2020, but not a straight addition of the CV deaths onto what would have occurred without CV. The reason the straight addition approach would not work is because a lot of double counting would be involved. In other words, if you are 85 with multiple conditions, you may not have made it past April any way. But this is can get lost when the total CV numbers are given. The point is that we have a lot of data to determine what this pandemic is doing and what it realistically will do in some scenarios. It is very dangerous for the elderly and for those with chronic health conditions. It is not very dangerous (less dangerous than seasonal flu) for young people. About 2.8 million deaths occur each year in the US. There is no scenario in which an additional 2-3 million people die in the US from CV in a 12 month period, and information such as "2-3 million deaths in the US possible from CV" is sensational and misleading. I think today is the right time to reject the rampant sensationalism of this topic and to discuss & determine the best way we can focus resources to protect those who are at risk.
  6. I don't think it is simply a matter of overreaction or not. I think we did not do enough in terms of preparation and prevention in certain areas and we are overreacting in areas where the reduction of risk is not worth the costs. At some point we are going to have to evaluate the actual risks and weigh them against costs and make hard decisions, the same as we do in every other area of life. Right now the focus is solely on what measures will have greatest possible impact on reduction of total infections & number of deaths, and worst case possible projections of the pandemic are often given as justification to this approach. But this approach will lead to poor decisions. In what other area does focusing solely on worst case scenarios, without taking into account risk percentages and costs, lead to good decisions? In what other area is our sole focus on preventing risk of death at all costs? Life is risk and we have to make sensible decisions based on what we know. Oftentimes those decisions will mean more people will die due to some immediate consequence as a result. That does not mean they are poor decisions.
  7. I don't think the period slowed solely because the numbers got bigger. I think they slowed for a number of reasons, a large one being isolation measures as you've mentioned. The point is that the doubling rates when the number of deaths get higher has a much larger impact on the total number of deaths than the rates early on. And the rates seem to slow substantially at a certain length of time when the daily rates get larger. For example, if we take the total number and daily rate for Italy at March 15 and project out with a doubling of daily death rate every 4 days, they would be at over 25,000 deaths and over 4000 deaths per day. But since the rate slowed over the past 10 days, the numbers are far below these. The rates early on in the outbreak have far less impact on the overall numbers. This is why the US being at 400 a day earlier than projected doesn't have much impact on the total if the rate cools next week. So far, no country has maintained the death rate of 2^(n/4) for more than a few weeks.
  8. It is easy to outpace numbers in the early days because they are relatively small. The doubling curves start to bend for countries that have been reporting deaths for around 3-4 weeks. In Italy the first deaths were recorded at the end of February and the daily death rate has now taken about 12 days to double. In Spain, the first deaths were recorded about a week after that (March 6), and the daily death rate has only gone up around 25% from March 24 to March 28. Our first sustained period of reported CV deaths starts on March 13, so if we follow the pattern of harder hit countries of Italy and Spain, we should see slowing of the rates in a week or so. The report you linked shows a slowing of the doubling rate as well and predicts around 31,000 deaths by April 15.
  9. Italy has had the largest impact in terms of total number of deaths from CV, and today's total looks like it will be the highest they've recorded. But on some positive news, the rate of deaths has slowed considerably from unabated projections. Most projections showed doubling every 3-4 days, but going back to March 15, Italy is nowhere near even the slower doubling every four day rate. In order to achieve doubling every four days, the daily amount should increase by ratio of 2^1/4 (about 1.19) day over day. Italy is averaging much lower than that since March 15. deaths/day, Italy 15-Mar 368 16-Mar 349 17-Mar 345 18-Mar 475 19-Mar 427 20-Mar 627 21-Mar 793 22-Mar 651 23-Mar 601 24-Mar 743 25-Mar 683 26-Mar 712 https://www.worldometers.info/coronavirus/country/italy/ Even with the high death toll expected for today, it will likely only be around one-third as much as predicted by doubling every four days since March 15. More data should come out to give some explanation for why the slower rate than predicted; of course, it seems likely quarantine & lock down will be a contributing factor. However, all of Italy did not go into lock down until March 9 (although Lombardy and other parts of Italy implemented restrictions earlier than this) and death rate should lag case rate by a few weeks, so there may be factors involved other than solely isolation measures.
  10. It can be difficult to not come across as hostile or taking things personally in text only debates. I don't feel any hostility towards you nor anyone else. We are all just trying to make sense of the situation by posting points and counter points as we see them with strangers on the internet, probably while stuck on long, dry conference calls.
  11. I wasn't trying to be snide. I thought you simply did not read in detail what I wrote. I still think that. You've made several post hoc changes in an effort to justify faulty claims. What is the polite way to point out that none of them are believable? For example: You claim 78,000 will die given certain assumptions with a given infection rate, I point out that given those assumptions the total number of deaths will be around 30,000. Your response - ok, just triple the infection rate then. This is obviously a sloppy post hoc change to get the number you already claimed. I say you are not reading my posts and give as evidence the fact that I referenced a study and you then referenced it back to me after a few exchanges. In the post that I referenced the study originally, I gave information that came from the table within the full study that is not available in the abstract. Your response - I was trying to be polite to make sure you were looking at the data in the report and not merely reading the abstract. You claim that you have seen no evidence at all that shows an IFR below 1%. However, there are multiple claims linked & posted in this thread from professional epidemiologists based on extrapolations from data that give IFRs well below 1%. Even the study you linked, the one you claimed you linked out of politeness to make sure that I was looking at the data, states "we obtain an overall IFR estimate for China of 0.66%." Your response - I did in fact see all of this evidence, i just reject it. The reason there is no point in continuing the discussion is because no progress can be made due to post hoc changes and goal post moving. April 15 will come, the US will be no where near 50,000 deaths from CV, and my guess is that the goal posts will be moved and victory claimed.
  12. I don't know why you think I am taking anything personally. I don't believe anyone is making any personal attacks or even implying anything of the sort. My perception is that this is a very cordial debate by message board standards. You think there is some significant difference in linking the abstract on which the full study is available for download vs direct linking the study? Obviously I am familiar with the study and its methodology, having already referenced it and linking the abstract page with full study available. I think there may be some disagreement due to the distinction between what can possibly happen and what will likely happen. I am trying to give numbers closer to what I think will happen, you seem to be focused on arriving at max possible impact scenarios based on worst possible conditions replicated throughout the world and extrapolations via single factor exponential curves. You are taking the highest known death toll per capita regions, with high population densities, older average ages, and ideal weather conditions, and applying those situations to the entire US. So there may be some disagreement due simply to approach. If that is not the case and you are giving numbers on what you think will happen, then we will know accuracy over the next few weeks.
  13. None of the above was my analysis. Those quotes were from epidemiologists and medical professionals that had been given in this post. You wrote "Please, point to one study, one piece of evidence,anything, that shows an IFR significantly under 1% is likely. Seriously, anything. I haven't seen it." I posted some evidence you should have seen. On my end, I've read your sources, read the citations they were based on (which I linked in post 140, which you then linked back to me after a few exchanges on post 168, presumably because you are not really spending much time on my posts), and looked at how you were calculating your results. So I have taken the time to familiarize myself with those arguments and points you are making. But this is not being reciprocated and so there is not much point posting more on this topic. And as already mentioned, we have in this case a quantified measure we can use to determine whose approach is more accurate.
  14. From post 114: "The one situation where an entire, closed population was tested was the Diamond Princess cruise ship and its quarantine passengers... Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%." https://www.statnews.com/2020/03/17/a-fiasco-in-the-ming-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/ From post 278: "Next, the northeastern Italian town of Vò, near the provincial capital of Padua. On March 6, all 3,300 people of Vò were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That’s more than 130-fold the number of actual reported cases. Since Italy’s case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%." "An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism." https://www.wsj.com/articles/is-the-coronavirus-as-deadly-as-they-say-11585088464?mod=hp_opin_pos_2
  15. I'm not intentionally ignoring or not factoring in evidence because it makes me uncomfortable. I'm looking at studies that give IFRs based on analysis from the most comprehensive testing within groups that we have. You are taking outlier cases and applying them broadly as averages without any other factors involved. The one study you keep referencing (the imperial college study) is based on data collected from China. China is known to have problems with their methods of data collection & categorization and did not do very widespread testing initially. But at this point I don't see this back and forth making much progress, and in any case we have a quantifiable measure we can use to give indication on whose projections are way off. If the US really is close to 50,000 deaths by April 15, then this is evidence that your projections are valid. If it is much less than that, then maybe they are drastic overestimations.
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