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Damian Rafal; coll.

**'EXTENDED ABSTRACT'**

BACKGROUND: What do the data presented in the CDC tables „Deaths involving coronavirus” mean? The one objective information is: „xxx thousands of people have died, being (probably) infected with Covid-19”. But how many of these people would for sure still live if not Covid-19 (/as including into this group has been based on mechanical assumptions) ? The paramount aim of this paper is to present the math-logic method that makes possible to reveal the genuine number of Covid-19 lethal victims.

METHODS: The ideas for solutions are original, mathematical – logical, there were used constructed equations; a few riddles had to be solved. Calculations are in some places somewhat simplified, if the simplification matters only very little both to the final result and to the partial-result, to chase calculations. There were used the CDC, NSC, SSA and other agencies/institutions’ databases.

FINDINGS: Under 10% of those reported as Covid-19 victims, in the U.S. in 2020, died from Covid-19 complicity (giving ⩽30 thousands) and all the rest would have died in the same or in a very close to identical time anyway (also without Covid-19), because their deaths resulted from the normal age-structure of deaths in the United States, and from causes/conditions already existing before Covid-19, creating the expected average age of death* actual in the given year (*due to not-Covid-19 causes). Also, a conclusion about an overestimation could be made even from the fact that for a statistically big group of mostly real victims of the infection there should be the increased, against the comparative group, average number of chronic conditions, as the number and the health-state, at a given age, are correlated (the importantly increased number usually reflects the worsened health-state) and Covid-19 should have actively shortened life of its real victims; any increase in this number is not visible in the 2020-"deaths involving coronavirus group" (DIC). The 2020-DIC group is a mixture of genuine Covid-19 deaths and natural (not Covid-19) 2020-deaths, with the very strong domination of the second ones. (/please read also 'HINTS' -points 13, and 'ERRATUM and DEVELOPMENT' -F). The quick "result" of Part1, even if it is the starting point of the analysis, which analysis must be looked at as at the process of/with increasing correctnes, until the equilibrium point is reached, is an acceptable approximation of the most probable final result; the "result" of Part1 is not a result in the strict sense, it is more like the evidence that the official claim about the number of Covid-19 deaths is a nonsense -please read also 'HINTS' -point 10-b (!). The average age of genuine Covid-19 victims should be strongly lower than the official data says; with a high number of chronic conditions it matters little for further life expectancy of an individual if an actual age is 75 or only 67 instead [DuGoff -Table2], and there are few very old people in the growing U.S. population [= those at age ⩾80 have a 3.7%-share, and those at age 70-79, with its majority at age 70-74, have only a 7%-share].

INTERPRETATION: The official number of Covid-19 victims is in a vast majority “the double counting” of those who would die whatsoever in the same (or in a very close to identical) time also without Covid-19. The 2020-DIC group's construction is based on irrational mechanical assumptions resulting in the false removal of natural 2020-deaths from it; no mechanically built group can consist of only genuine victims of a new killing factor. The ex-post analysis is necessary to discover the real number of deaths due to Covid-19.

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-----ADDITIONAL IMPORTANT HINTS----- : 1) Into the basic equation/way that lets adjust shares on the right side of the table on page 5, like: [1 - (0.0027 - 0.0014)] x (75.75 + S) + (0.0027 - 0.0014) x 20 = 75.75 ...there is entered doubly simplified data, speeding up the calculations, good for small total not-relative share-deficits of lower age-subgroups. But if this total share-deficit was meaningfully bigger then important inaccuracies would appear. Then one would have first to precisely calculate a vanishing-adjusting share [starting with 0-1 age-subgroup] as it would be slightly higher than simple 'B - A' and then insert it instead of 'B - A' (although e.g. against a small '0.002700 - 0.001400' the vanishing-adjusting share would be increased only by 0.000002); also, one should then simultaneously adjust 75.75 (equally on both sides of the equation) by including the revision-result from preceding steps (C), but again, it really means for bigger share-differences while e.g. for the 15-24 age-subgrup with '0.27% - 0.14%' the partial-result will increase only by 0.001 year. /When the average age (AE) of an age-subgrour is lower that 75.75 and simultaneously there is no share-deficit in the DIC subgroup, but a surplus, and so 'S' is negative, it would be with everything included: {1 /[1 + (A - B)]} x [75.75 + C + (A - B) x AE ] = (75.75 + C + S)/. In our case being most precise would add theoretically only 1 (one) thousand of real Covid-19 deaths to the final result (...however together with including the correction 'Erratum-A' it could add practically nothing due to rounding the slightly increased value down to 1.00). 2) Congenital anomalies could be treated similar to injuries mainly at age 0-1 (cases of infant mortality). 3) The internal structure of the DIC group suggests that the influences of diminishing social activity of those in their terminal state + declining with aging levels of ACE2 expression (it not much matters if actually -please read the tip below, but the decline is confirmed by a majority of sources concerning humans) ...sum up to a more like neutralizing impact on the standart differences in illness-rates between younger adults and those at age 60+. The decisive tip is also the 01-10 age-range's share deficit (in DIC) with the stronger than 90% deprivation (as the manifestation of the whole age-structure transformation against the normal one of 2020-decedents); the deprivation seems like exhausted (and so the general transformation) with hardly any space left; even a general shares-change, resulting among others in an additional 2.5%-deprivation rise here, could increase the final revision for the CTIWCD group only by 0.01 year (concerns Part1). [/In the January-2021 CDC data shares in 35-44 and 45-54 age-subgroups are slightly higher in the DIC group]. 4) The given (p.7) 3.5%-increase in the number of injury deaths concernes unintentional ones, with suicides and assaults it is only +2.3%. 5) There is "the total rounded 12.95 value (12.7 + 0.25)" with data from January 2021. If we fully switched to the wonder.cdc.gov for-2020-data we would receive the value lower by about 0.03 year (12.18 + 0.49 + 0.25). We did not it cause to be fully fair we would also have to replace our basic 363 K with 351 K (2020-DIC size) and the analysis-result could only drop [+ in the lowered 351 number can lie reasons of the differences]. 6) The mentioned on Page 10 demographic factor in an age-subgroup of the DIC group means very little as, in fact, with an average (not a median) of an age-subgroup in a life table the usual difference is considerably smaller, and we finally based on corrected LEn fitting better to an age-structure of age-subgroups of the DIC group. 7) Page 14 -the given under the major record 'AAADP' concerns the value that should be if the DIC group was not distorted by unreal Covid-19 deaths that happened in 2020. 8) The calculations in the beginning of Page 15 are a bit simpler look at an individual; if to look at a group instead, there should be used weighted LEn, but then with 'DRI x 10' (if with an assumed constant in an age-subgroup DRI; not '10' only in the 0-1-4 and the last age-subgroups), average size in an age-subgroup (as a better measure) -for the share. The given in this fragment LEn should be like that what you will know if ask the authors. 9) The given on p.16 'm' is received by the simplest proportional way; but the exact 'm' should be yet smaller because the demographic factor (growing population) is most important, what we can see by the example of deducting deaths of infants having a stronger effect on ADC (>0.5 year) than on at-birth LE (>0.4 year); anything able to slightly overestimate the final analysis-result is allowed. 10) a) In the major record (p.16) the basic LEWIIfmS cannot be higher than 80.75. Even an absurd assumption e.g. Covid-19 chooses to kill people with an average expected 'length of life' of 89 cannot help to importantly change the final result, because further LE (LEa) corresponds to at-birth LE, so for an average 'legth of life' of 89 years LEa for still alive at an average age of just over 76 should not be 12.95 (on average), but about 20 years. b) One can ask why it is not used the average age e.g. 67 quickly in 'Part 1' (?). It is not used because solving the task is not one everything-matching Part/stage, but a process with continuous improvement till all fits, one to the other -any lowering the average age requires LEa to immediately go up and the DIC group to be strongly reduced to a subgroup being the reference. 11) Upper p.17 -a potential distortion of R3 when referred to LEWIIfmS, if we have little diminished LEa, can have only an insignificant influence on the result. 12) a) Potential differences concerning the prevalences of different-separate chronic conditions can very little influence the final result, what can be checked by enterings into the main record LE-data assuming extreme theoretical variants e.g. 50 % of the DIC group having Alzheimer, the diminishing effect of which on LEa is stronger than that of other conditions [DuGoff]. b) Hopes to increase the final result of the analysis by assuming a yet higher prevalence in the DIC group of a chronic condition of a considerably lower agerage age of death (e.g. obesity, although the number of deaths attributed to it is very small -concerns mainly extreme obesity) are empty ones; this condition would have to be correlated with illness rates (as if the increased prevalence would be invisible in the whole DIC group then could be important only in a separated very small subgroup -like few %), what would simultaneously shorten ADC making the small 'loophole' (0.78) diminish more and so the final result. 13) Real Covid-19 victims should be of a worse than age-average state of health; but even any theoretical assuming (theoretical as the number of conditions is not visibly increased) the average pre-infectious age-health-state to be bad in the whole DIC group (regardless those already being in their terminal state) still WOULD NOT ABLE TO INCREASE our small analysis-result by an indeed important value (by more than very few %), because it would additionally require a big positive distortion of R3 with LEWIIfmS in Part1, while e.g. a bigger positive distortion is impossible with the comparative data of the lower (67) against the higher (75) age, and with the strongly increased number of conditions a negative (not a positive) distortion appears for the lower age (/with taking into account an increase, with aging, in the number of conditions/) [DuGoff]. ...//[It can be a text-fragment is not 100% clear due to not an unequivocal word used, ...e.g. 'medium' instead of 'middle'(time) -p.11.]// -----ERRATUM and DEVELOPMENT-----: A) The share of deaths (without injuries) at age ⩽1 was 0.74% (not 0.76%) in 2019; this mistake overestimates the final result by a petty value. B) On page 11: for the 25-34 age-subgroup there is pasted DRI as 84.6 when it should be 83.0; but it would be yet more precise if this DRI was next corrected up to 83.8 and that for the 35-44 age-subgroup from 84.6 to 83.3, but they are not as the differences in DRI between neighbouring subgroups are there very small, and all these imperfections together mean virtually nothing as influence the final result by many times less than 0.01 year. C) In the beginning of 'Part 1c' there is a shift-error -more (by %) people get into their terminal state being at an ADVANCED (not at a younger) age. D) In the end of Part 2 (about CTIWCD and ACE2) there is given 76.75 as ADC instead of 76.8, "... = 75.95 plus the sum..." while it should be: "...= 76.0 plus the sum...", and there is "in a subgroup composed of Ns people" unnecessarily -as for a final very small subgroup, and so with the strongly diminished average age, 'final revisions'-ADC visibly rises (/these are typo errors, matching to an older Version). E) Compared again average ages of age-subgroups of the DIC group with those of corresponding subgroups of the comparative group (all deaths, but this time without injuries), show up to be, on average, more like equal [it does not change our result]. F) 'Part 2' must be partly back-CORRECTED, plain lowering the average age of real Covid-19 victims is not fully efficient in removing natural 2020-deaths. The equilibrium is the situation when the sum of a current average age and average LEa is equal a timely-LEWIIfmS (the distance = 0). With the average age falling significantly under 70 the distance strongly diminishes. The final result should change only little, what we check by approximating 'the very late sum of much diminished average age and average LEa' and 'timely-LEWIIfmS' one to another (and the potential effect of 'final revisions')

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