{"id":3002,"date":"2020-03-31T20:30:34","date_gmt":"2020-04-01T00:30:34","guid":{"rendered":"http:\/\/stockpicks4you.com\/?p=3002"},"modified":"2020-03-31T20:30:34","modified_gmt":"2020-04-01T00:30:34","slug":"unscientific-and-sloppy","status":"publish","type":"post","link":"https:\/\/stockpicks4you.com\/index.php\/2020\/03\/31\/unscientific-and-sloppy\/","title":{"rendered":"Unscientific and Sloppy"},"content":{"rendered":"

I want to state upfront that I know nothing about pandemics and epidemics. However, I am good at looking at statistics and spotting fallacies.
\nTake for instance this chart that shows the exponential rise in number of cases which has the whole USA in a worry.
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\nWhen looking at something like this we should ask a few questions.
\nFirst, how many people are being tested?
\nSecond, in which manner is the test being administered?
\nThe exponential rise in COVID-19 cases corresponds to an exponential rise in the amount of people being tested. Understand? The more people you test per 100K the more cases you will find. Makes sense?
\nThe second question is even more important. Where and how is this test being administrated?
\nImagine you wanted to get an accurate picture of who was going to win the presidency in 2020. Would you go a RNC conference and do a random sample of the people at the conference? Do you think this would give you the best representation for understanding the voters as a whole?
\nOr would you do a random sample of the general public and get a margin of sampling error for the given full sample and calculate a confidence level? The amount of sloppy thinking on this by so called experts is astounding.
\nRobert Zurbin<\/a> is an aerospace engineer. Read the below carefully. Read it twice. He nails it.<\/p>\n

In the face of the current coronavirus pandemic, authorities are taking measures that are having massive negative economic impacts. Some say that these measures are wildly unwarranted. Others, that they are disastrously insufficient. Who is right?
\nNobody knows. No one can know what the right course of action is, because the available data to provide a basis for these enormously consequential decisions is woefully inadequate. The most important statistics we need to know to develop a strategy to deal with the situation are the size of the pandemic and its lethality. Current data provides no basis for accurate estimation of these vital metrics.
\nFor example, as of the morning of March 30, Johns Hopkins<\/a> reports that 143,532 Americans have tested positive for COVID-19, with 2,572 deaths. If taken at face value, this would suggest that the infection rate among Americans is 0.044 percent, with a 1.8 percent death rate among those infected.
\nBut we know that such a conclusion would be inaccurate, because millions of people feeling symptoms are being turned away by testers, and there must be millions more, with and without symptoms, who are choosing not to volunteer for testing. So, without doubt, the size of the infected population is being underreported, perhaps grossly so.
\nThe shortage of testing has led to a situation where only VIPs can be sure of getting tested if they suspect illness. Thus we hear about Tom Hanks, Prince Charles, and Boris Johnson testing positive, but how can any such assemblage provide a statistical base? Well, there is the U.S. Congress, where four House members and one U.S. senator have tested positive for COVID-19, for an infection rate of 1 percent and a death rate of zero. But Congress, while arguably politically representative of America at large, is hardly an optimal sample for medical polling purposes. Plausible arguments can readily be made why congressmen should have either higher (they attend lots of meetings) or lower (they don\u2019t take mass transit) infection rates than the general population.
\nTo get the right answer, we need to random-test the public.<\/strong> We don\u2019t need to test all 327 million citizens \u2014 although, when feasible, that would be very desirable for the purpose of identifying immune individuals and putting them back to work. For the purpose of getting a rough estimate of the size of the infected population, we need to random-test only about 1,000 people nationwide. That is the approximate size of most election polls, and, provided that reasonable care is taken to ensure that the sample is representative of the electorate, such polls can generally predict the outcome within plus or minus 3 percent. It\u2019s true that occasionally a 45 percent\u2013polling underdog can pull off an upset victory, but never a 20 percenter, let alone a 1 percenter.\u00a0 Limited polls might not always predict the winner, but they inevitably show who is in the competitive range. For purposes of quantifying the epidemic, that would be an enormously valuable correction to our current state of ignorance.
\nIt is also probable that deaths by coronavirus are being underreported, or overreported, given opportunistic infectious diseases, notably pneumonia. There is reason to suspect this is the case for Germany, which reports 560 deaths in 63,929 cases (compared with 2,612 deaths in 40,751 cases in France), and certainly Russia, which claims nine deaths in 1,836 cases. So all deaths from disease should be tested to see if coronavirus played a role. But clearly, the great unknown that needs to be measured is the prevalence of COVID-19 among the population that is outside the medical system altogether.
\nLet\u2019s say that the poll tests show that the general infection rate is, in fact, the same 1 percent as seen so far with Congress. That would mean that instead of there being 120,000 infected Americans, there are over 3 million. It would also imply a much lower lethality rate than 1.8 percent, although care must be exercised in drawing conclusions in this regard, since the deaths occurring today need to be compared against not today\u2019s infected population but what its size was in the recent past, as there is a time lag between infections, illness, and death. Once that average time lag is assessed, the true lethality rate can be computed. This is very important, because if the lethality rate really were 1 percent, then, lacking alternatives, it could make sense to allow risky treatments that kill 0.1 percent of patients, whereas this would not hold true if lethality were only 0.01 percent.
\nIf we can increase the nationwide random-testing rate to 5,000 per day (about twelve daily in each congressional district), then once the time lag is assessed, repeated poll testing of the population would provide predictive information about what to expect in the near future, giving advance intelligence to our defenders about how hard the enemy virus will hit us and when and where such blows will strike.
\nWe need that intelligence if we are going to win this war. Random poll testing of the general public should begin without delay.<\/p>\n