Timeline for A chart of daily cases of COVID-19 in a Russian region looks suspiciously level to me - is this so from the statistics viewpoint?
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17 events
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| Mar 5, 2022 at 17:23 | comment | added | denis | For what it's worth, The Economist has a story on death rates through February 2022, "Are some countries faking their covid-19 death counts?": economist.com/graphic-detail/2022/02/25/… | |
| May 22, 2020 at 20:19 | comment | added | Sextus Empiricus | @JohnDvorak, it could be something like that. But I guess that it is more specifically like the hospitals have more testing capabilities themselves (at least some reports state that there is a lot of testing) but the tests that are used for official reporting are limited. Maybe it is only one single lab whose data is used. In this way you get that the testing is not only restricted, but also that the probability/fraction of positive cases is high (because of the pre-selection). | |
| May 22, 2020 at 20:05 | comment | added | John Dvorak | A hypothesis: there's only one hospital in each krai, it gets 100 tests daily, and refuses to report any cases that haven't been tested, irrespective of how well the symptoms match. | |
| May 22, 2020 at 16:51 | comment | added | Sextus Empiricus | @AlexeyBurnakov it is extremely unlikely to not underestimate the cases with these statistics of verified cases (unless it is done intentionally, but I don't follow your reasons why people would like to do that). This is because it is very difficult to trace all cases and verify them. So for all regions/countries, in order to estimate the prevelance or the total number of people that have been affected in the past, one eventually needs to use immunological tests on a random sample and extrapolate those. There is only one statistic that is not so difficult to trace and that is weekly deaths | |
| May 22, 2020 at 16:23 | comment | added | alexeymosco | I don't understand this either. But I am being careful with saying like "the Fed filters results" or Fed forces regions to filter results. A layman logic about covid stats we tend to have is that it is good for everybody but the people to over (not under) estimate cases. It is a good reason to show efforts to save the people and earn some more rating points, for all levels, from President, to Governor's, to Chief Doctors (more budget). It is just a common sense, not math. | |
| May 22, 2020 at 16:13 | comment | added | Sextus Empiricus | @AlexeyBurnakov ” I guess these is a combination of test inaccuracy, limited hospital beds, bias in sampling patient for testing, and maybe artificial (and less possible) case count underestimation. " Certainly all these aspects are likely around. But I do not see how any of them are a cause for underdispersion (low noise). | |
| May 22, 2020 at 15:59 | comment | added | alexeymosco | Correlating cases to population could also be informative. A "boundary" around 100 looks suspicious, but to correct data this way all local authorities would need to correct their timeseries individually. It is hard job. And variance/mean seems individually shaped. I guess these is a combination of test inaccuracy, limited hospital beds, bias in sampling patient for testing, and maybe artificial (and less possible) case count underestimation. All of these were reported on TV and news officially, expect for last point. Moreover people say that number of cases is overestimated all around Russia. | |
| May 22, 2020 at 14:39 | comment | added | Sextus Empiricus | @NuclearWang it is also interesting that these curves are showing that it is neither as if some single person is fabricating the data (I guess that this goes around in some people's minds). For this to be true the person that fabricated the data must have had a lot of imagination in making these different curves that all have the same behaviour, but everytime in a slightly different way. This does not look to me as if it is being fabricated by a single source. (My guess would be that the positive cases from regions undergo a second federal lab test, and this test is limited to 100/day) | |
| May 22, 2020 at 14:15 | comment | added | Nuclear Hoagie | Good answer. I had wondered if there might be some selection bias - the data certainly looks very unusual, but with so many local statistics being tracked around the globe, it's expected that a small number of regions will have correct data that's statistically improbable due to chance alone, and it's easy to focus on those cases. But the consistent pattern of improbable results indicates this isn't a one-off instance due to chance. | |
| May 22, 2020 at 8:05 | history | edited | Sextus Empiricus | CC BY-SA 4.0 |
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| May 22, 2020 at 0:48 | history | edited | Sextus Empiricus | CC BY-SA 4.0 |
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| May 22, 2020 at 0:48 | comment | added | Ben | Nice answer (+1). | |
| May 22, 2020 at 0:06 | history | edited | Sextus Empiricus | CC BY-SA 4.0 |
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| May 22, 2020 at 0:00 | history | edited | Sextus Empiricus | CC BY-SA 4.0 |
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| May 21, 2020 at 23:34 | history | edited | Sextus Empiricus | CC BY-SA 4.0 |
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| May 21, 2020 at 22:43 | history | edited | Sextus Empiricus | CC BY-SA 4.0 |
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| May 21, 2020 at 22:27 | history | answered | Sextus Empiricus | CC BY-SA 4.0 |