(3) Should it attempt to classify patients into groups that quantify the certainty they will get sick (and for how long)? Luckily, Purdue keeps their own dashboard and with some calculations their data can be extracted from the county data to give us a ballpark guess. The actual sensitivity and specificity of COVID-19 tests are unknown as these tests were okayed by the FDA under Emergency Use Authorization. Antigen tests will be used on the random population with subsequent confirmatory PCR tests used for anyone who initially tests positive. How can the range be so narrow and stable? So two SDs is .00064, which gives the range .856% – .984%, as you said. Only 14% gave the correct answer of 2% with most answering 95%. A systematic review of the accuracy of covid-19 tests reported false negative rates of between 2% and 29% (equating to sensitivity of 71-98%), based on negative RT-PCR tests which were positive on repeat testing. As the unemployment rate soared in April to its highest levels since the Great Depression, with 14.7 percent of workers without jobs, the coronavirus shutdown fell … In the United States, that appears to be between 5 percent and 15 percent. Using the same test on patients with COVID-19 symptoms, because their incidence of disease is 50% or greater, the test does not have to be perfect. In effect what you’re looking for is an expected temporal sequence among what are likely non-comparable tallies. I also wonder if it could be an issue of defining “COVID related” hospitalizations. Cases are clustered in the city, with certain neighborhoods experiencing more cases than others. In the past few months, we've seen that one of these odd behaviors is attributed to a significant number of health-news headlines recommending vitamin C to purportedly assist one's immune response to COVID-19. Well, in designing the test, you run the test adding “nucleotide free water” instead of sample, and this is your negative control. CP Scott: "Comment is free, but facts are sacred" Their lateral flow assay monitoring (known high number of false positives) or the PCR testing, where whole countries like New Zealand can have no cases despite continued testing? Maybe NY is post-pandemic, in the “endemic” phase of the disease, so it’s basically constant rather than exponentially growing/declining? But .00032 / .0092 is 3.5%, not .35%. Could this be the reason for increased hospitalizations? Only one has been hospitalized and none have died. In mining and metal exploration all assays are done using the same chemical process, but checked using duplicates, certified blanks and certified standards. If positive the person is quarantined and contacts are traced and tested. Certainly positivity rates are going up here. Yeah, I’m not saying that entirely explains it either. To go back to … But still, something seems weird. Across MedPage Today and its businesses, digital accessibility is a core priority for us throughout our design and development phases. Repeat the PCR test multiple times and see it come up negative repeatedly. The samples are prepped and analyzed in the order specified by the collectors, and lab prepping the samples also splits every sample so it can be tested later. And in the age of COVID-19 there's plenty of fear going around (so expect a lot of it). why do you state that there is a high proportion of false positives? The truncation value is usually 40 but I have seen 45. Guess not everyone is prepared to believe the rate in New York is as low as it appears. Abstract. Conjunction fallacy – the assumption that an outcome simultaneously satisfying multiple conditions is more probable than … We have learned in the past from routine PSA testing and mammograms that a positive test in a screening situation needs to be taken in context. If presented with related base rate information and specific information, people tend to ignore the base rate in favor of the individuating information, rather than correctly integrating the two. (2) Should it indicate virulence and the likelihood of a person’s own mortality due to Covid? > These are not randomized tests, through a sparse, clustered set of interactions with a great deal of heterogeneity. We investigate whether potential socioeconomic factors can explain between-neighborhood variation in the COVID-19 test positivity rate. Panic happens because the media industry tends to engage in what can be described as a base rate fallacy (Hardman, 2015) which is the idea that people tend attribute a higher level of risk to a situation when they are not aware of the actual base rates of such phenomena. I think the timing on registration of everything, cases, deaths, tests (maybe not hospitalizations but maybe even that) is so all over the place that it’s hard to pin down leading and lagging based on daily or weekly numbers. The original question is why the % positive is so consistent. Also I definitely believe that false positives are related to true positives. Another wrinkle for the measurement problem; both of contagious individuals and viral load sufficient to be related to death. All rights reserved. Which NY State numbers are we talking about? We’re doing in the US as many tests every day as NZ has done EVER. So far, 90% of the students who test positive do not develop symptoms. Unfortunately, the lack of understanding of the statistical principle of base rate fallacy/false positive paradox has led to some confusing numbers. Hospitalizations ought to lag cases, but lead deaths. So the test serves as its own ‘post-measure’ or gold standard. The researchers asked 60 Harvard physicians and medical students a seemingly simple question: If a test to detect a disease with a prevalence of 1/1,000 has a false positive rate of 5%, what is the chance that a person found to have a positive result actually has the disease? It’s even possible (although I have no idea whether it is true in Texas) that the definition of a “COVID related death” has changed over time. Bad decisions can be made because of a misunderstanding of statistics. You also do not know if a low virus concentration in the sample really means a low virus concentration, for example the swabbing may not have been done properly. It is not implausible that testing is “growing / shrinking in step with the spread / decline of the virus”: the more people in my circle being diagnosed to be positive, the more likely I am undergoing a test. Or is there some reason why that is plausible? Haven’t read all responses, but assume it is PCR tests and their false positives that are discussed. Our state has a population of 6.5 million. Description: Ignoring statistical information in favor of using irrelevant information, that one incorrectly believes to be relevant, to make a judgment. So then would the picture of the “base rate fallacy” effect be different than if there were no heterogeneity and the base rate was uniform? We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. Our efforts are ongoing. Even using a test with only 90% specificity, the number of false positives will be much less significant. Accessibility improvements made to our sites are guided by the Web Content Accessibility Guidelines (WCAG), Level AA. If you … By not reporting these groups separately, we really have no idea what's going on in our town. So how many false positives has NZ had ever since the start of the pandemic? Furthermore, probably if anyone gets a positive in NZ immediately everyone jumps on it and re-tests the original sample. But keep in mind you can also do multiple primers (roughly checking for different viral genes) and see some but not others cross the threshold. This study pretends to know, Basbøll’s Audenesque paragraph on science writing, followed by a resurrection of a 10-year-old debate on Gladwell, Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond, “We’ve got to look at the analyses, the real granular data. It’s kinda like when you find a burnt spot of ground: sure, that area may not be in flames now, but there sure was a fire, so you want to know whereit may have spread while it was burning. We must compare apples to apples and oranges to oranges rather than just making fruit salad out of the whole thing. He's an adjunct professor at Indiana University, a past president and board member of the Indiana Orthopaedic Society, and a past member of the Board of Councilors for the American Academy of Orthopaedic Surgeons. If negative do nothing. Since staff and students combined are 50,000 at Purdue University, 5,000 tests are done every week. Maybe It Shouldn’t Be. But isn’t it also rather implausible that the *genuine* rate would stay the same? It’s more than sufficient to test for contamination. Yes. We also rely on our community to tell us when they experience an issue with any of our sites, and we give consideration to all feedback that is provided to us. False negatives should not really occur in those with recent onset symptoms as viral shedding occurs prior to and for the first week or so of the clinical course. But hospitalizations almost perfectly flat. The base rate is the actual amount of infection in a known population. 6 The use of repeat RT-PCR testing as gold standard is likely to underestimate the true rate of false negatives, as not all patients in the included studies received repeat testing and … I know that US testing runs 40+ cycles. If we are doing the same kind of test, then that’s what we’d expect to be generating EVERY DAY in the US. Did the only the doctor receive the yes-no or does the lab test itself only produce a yes-no? Hmmm. Students who test positive have to isolate in an old dormitory or go home. It’s always tough when you’re looking at a press release to figure out what’s going on.”. But that assumes that each daily or weekly “rate of hospitalizations” has a fixed relationship to the underlying population at risk, same with cases and deaths. (4) Should it predict the likelihood that a person can infect another person, and under what conditions? Remember if you contaminate 1% of the tests with your positive control, then you’ll get 1% positive rate, and that’s easy to do by accident. MedPage Today is committed to improving accessibility for all of its users, and has committed significant resources to making our content accessible to all. Thus, it makes it look like our county's number of positive tests has doubled since Purdue started in-person classes in August. An elaborate plan was implemented, including a signed pledge from all students to behave properly, wear masks, maintain social distancing. >>where whole countries like New Zealand can have no cases despite continued testing? This is the kind of thing you’d see them do when they get a sudden positive after weeks of zero positives in all of New Zealand for example. Base rate fallacy/false positive paradox is derived from Bayes theorem. When these tests return negative, significant confusion occurs. New York City was the first major urban center of the COVID-19 pandemic in the USA. A PCR test can only really come up false positive because of contamination of one kind or another. Base Rate Fallacy Defined Over half of car accidents occur within five miles of home, according to a report by Progressive Insurance in 2002. That’s close to the range stated (.85 – /99%). So what is going on? Such improvements to our sites include the addition of alt-text, navigation by keyboard and screen reader technology, closed captioning, color contrast and zoom features, as well as an accessibility statement on each site with contact information, so that users can alert us to any difficulties they have accessing our content. The confidence that we should have in antibody tests depends on a key factor that is often ignored: the base rate of the coronavirus. If at any time you have questions or concerns regarding accessibility, or experience technical issues, please contact us at accessibility@everydayhealth.com. Yes, and this might be true in some places, but looking at the # of tests performed in NY it does not seem to be true there. There are both known positive and negative controls on those trays. Robert Hagen, MD, is recently retired from Lafayette Orthopaedic Clinic in Indiana. The NFL contamination case in August is an example of how a high false positive rate tied into a situation in a lab. The tests being used have changed over time. COVID deaths in Indiana average about 23 per day, but that too is going up. Restaurant occupancy, sporting events and other large gatherings are again limited at a greater level than state requirements. I know there is some rushing with COVID-19, but any diagnostic test should go through a validation, a series of experiments to assess it specifications. The pretest probability of a patient having COVID-19 versus another diagnosis is dependent upon the community base rate of COVID-19. There would also be variation in the number of tests performed each day. Abstract: We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. Manufacturers' data have not yet been corroborated by the agency. Robert Hagen, MD It might be useful, if we’re speculating about contamination, to find out how often labs have to discard results because the controls show a problem. I think the “positive tests” mean different things to different people. Given the possibility of ‘stale’ PCR tests for weeks or even months after infection, if everyone who is admitted to hospital is tested, could that mess things up if there are relatively few currently symptomatic people but many cases in the recent past? 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