THE OFFICIAL NUMBER OF COVID-19 DEATHS IS A MANY-FOLD OVERESTIMATION. The Math-logic Methods to Reveal the Real Number of Covid-19 Lethal Victims. The Guideline Analysis, the U.S. in 2020.

EXTENDED ABSTRACT plus SUPPLEMENT

BACKGROUND: The objective information in the CDC tables named 'Deaths involving Coronavirus' is: "xxx thousands of people died, probably infected with Covid-19". But how many of these people would for sure still live if not Covid-19? The main aim of this paper is to present a method that makes it possible to reveal the real number of lethal Covid-19 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, to chase calculations. There were used the CDC, NSC, SSA and other agencies/institutions' databases. Doubts are resolved to favor overestimation rather than underestimation of the analysis results (e.g., p. 6–7). The number of chronic conditions is considered a reliable indicator (on average) of a pre-infectious worsened health state compared with the average for a specific age. FINDINGS: Including into the 2020- official "Deaths involving coronavirus" (DIC) group was based on irrational mechanical assumptions. The structure of this group in terms of age was nearly indistinguishable from natural death patterns (adjusted by eliminating 'infant mortality' and injuries, and corrected by illness rates). Only up to 10% of those officially reported as Covid-19 victims in the U.S. in 2020 could have died from Covid-19 complicity; the rest would have died at the same or a nearly identical time regardless, because their deaths resulted from the normal age-structure of deaths in the United States, and from causes already existing before Covid-19, creating the expected average age of natural death actual in the given year (due to not-Covid-19 causes). It is also very probable that some people in the official DIC group had their death-date accelerated (forced to die in 2020, while otherwise would die much later) by wrong/harmful procedures and so the total number of those whose death was visibly accelerated could have been meaningfully bigger than 30K (of the DIC group), but they can be also in part already included in exchange for the Covid-19 deaths. With no additional 'missed risks' ('m'), the average adjusted total (at-birth) life expectancy of genuine Covid-19 victims should have been 77 or less (p.21); their otherwise further life expectancy (LEa) should have been 10 or less, not nearly 13 years, as would be assumed under an irrational mechanical approach that all decedents of the 2020-DIC group were not those who died in 2020 naturally due to "aging". The equation 'ADcs + LEa1 = timely-LEWIIfmS' (p.20+) must be fulfilled for every external burdening factor provoking premature quick deaths (/e.g. Covid-19) and its real victims must be (on average) weaker simultaneously due to their higher age and due to their worsened, against an age-average, health-state (with a strongly increased average number of chronic conditions for low mortalities) -otherwise the equilibrium never exists ...unless there is a 100%-mortality. And, if a number of chronic conditions was not a perfect reflection of a worsened health-state against the age average (or of risks) it would not mean much for an average age of 73, becauseas the result has a significant safety margin (although there would not be an initially supposed number, but calculated, using SD of LEa, lower ~14.5  -'Corrections'-f); for an average age of 67 it means yet much less, as ISD, not a number of conditions, is the main result-limiter there. ...Independently, even just the average number of chronic conditions protects the main result, which number must have been strongly increased among alive ones (but not already in a terminal state) and then really killed by the virus against the number in a comparative group of just alive ones with exactly the same age-structure (!), because Covid-19 out of infected ones at every specific age kills very few (of older ones) or very very few (of young ones) of them -usually weaker/weakest ones; the age-adjustment eliminates any meaning of older ones dying more often than younger ones from Covid-19. The CDC knew there had to be a very clear correlation between 'Covid-19 Death Risk Ratio' and a number of conditions, but in the DIC group none increase in the average number was visible (officially <3 conditions) even with limiting the list of conditions in the comparative group to the conservative CCW list (/the comparison only of the prevalence of major heart diseases shows it is not increased in the DIC group -more in 'Additional Notes' -b). If older persons have a high number of CCW-conditions then this pure number matters very much to residual life expectancy (LEa); the marginal decline in LEa increases with an additional chronic condition, when a number of conditions is low or moderate, but this decline starts with low values -first 2 conditions of 2008-CCW ones (and so approximately first 3 of current CCW ones) sum up to about 3 times less negative effect on life expectancy than the next 2 conditions (3+4) of 2008-CCW do in 75-year old ones (= approximately 4+5+6 of current CCW ones). /E.g. normally, still alive ones at age 67 and 75 with a low number (0 - 3) of current CCW-conditions should otherwise live, on average, for the next approximately 22 and 16 years respectively, but with a very high number (15 - 30) of conditions they would otherwise live, on average, for <5 years only./ [18 +CCWdata]. Natural deaths with chronic conditions (ones 100%-mortality) are, in contrast to quick premature deaths due to the infection, realization of risks originated in ones' past, with almost none predictability of a specific year of falling into one's terminal state (read also 'Additional Notes'-c, which are below). INTERPRETATION: The official number of "Covid-19 victims" is a very untrue number and means, in a vast majority, 'the double counting' of those who would die whatsoever at the same (or very close to identical) time without Covid-19. The 2020-DIC group's construction is based on irrational mechanical assumptions, resulting in natural 2020-deaths being not removed from it at all. /Please read also 'REMARKS' (below) !/

SHORTENED SUPPLEMENT: THE ALTERNATIVE METHOD (summary) -Corrected

Complete disregard of LEWIIfmS will little weaken the proof, because we can base mainly on a Population Pyramid [10] adjusted for illness rates, 'Life Table'-2019 [2], [6], [18], [20] instead ([6] is now in archive.cdc.gov: Estimated Covid-19 Burden); any average age of death for true Covid-19 victims of ⩽73 y. proves the heavy Covid-19 mortality-fallacy by ISD (defined in the essay). ...At the same time, maintaining a high age is impossible without a strongly increased average number of chronic conditions. The average measured by 'further life expectancy' (LEa) health-status at an average age of 83.0 (age range 77.0+), if one still lived, was about identical (/an age-dispersion itself increases average-LEa more here) to that at an average age of >68 while with ~13, on average, of current CCW conditions (people with 7 conditions of 2008-CCW [18] reduced by over 1/4, but next the remaining share of those with 7+ adjusted up by the whole of the earlier reduction, as those in [18] are of a much bigger age-dispersion, compared with [20: MEPS 2005]), so the big rest of the 60-<77 age-subgroup (91%) would have to be of strongly smaller average mortality (together with mortality suitably strongly decreasing within this rest with a number of conditions diminishing from 9/10 to 0 -for every age). {The %-prevalence of the high numbers of current CCW-conditions is safely taken to rise within the same age range 3.0 times, because with the rise of >2.6 times, between the 50-64 and the 75-84 age-subgroup, 5+ conditions in [20] by its %-prevalence in aged 67++ correspond to ⩽6.5+ of 2008-CCW and ~10+ of current CCW ones}. The minor sub-age-subgroup is safely taken to have only 9%, reduced from calculated -10.9%-, because in the study [18] people were of slightly worse* than age-normal health-states (*average LEa were nearly 96%). We based on the infection rates, the higher age-subgroup should then also be ~4.3 times (against the initial 3.3 times [10]) smaller than the lower one (without the share of the higher age-subgroup and so also limited to ages 60+, but <77), while those aged <60 y. happen to be killed too. {The falling in older adults with aging infection rates must decrease within the 65+ age-range too, the rates at age 95 should be approximately 0.55 of those at age 60, the distance is 35 years; the average age of alive ones at age 50-<65 is almost 57.5 and at age 65+ is almost 75; 0.74 x 0.74 = 0.55; the distance between the average ages of the two higher subgroups is much smaller, but still ≪75 years old ones must have the rates distinctly higher than ≫75 y.o. ones}. If to base on the symptomatic illness rates (declining faster), the highest age-subgroup should be ~4.5 times smaller. {For the 9% sub-age-subgroup the average LEa for those with 10+ of 2008-CCW cannot be 5, but 4 years (at most)*, because otherwise the av. number of condinions would have to be only ⩽11* there (*later confirmed by ChatGPT) -compare declines in LEa [DuGoff -Table 2]; DuGoff et col. knew about a possibility of LEa-overestimations in very small sub-subgroups. Thus if to take into account only the very weakest ones (LEa ⩽4 year) there must be very small, but very similar %-prevalences (adjusted by falling illness rates).} But for safety reasons we will initially use only '4.2 times smaller'. ... Let's base now on the age-structure of the 2020-DIC group. The share of those at age <60 is 12.15%* with their average age 50.5 {/The illness rates at age <60 are higher by almost 20%, but we initially ignore this fact (with the back-higher illness rates and true Covid-19 deaths this share should increase -the difference is explained in the essay -p.7)}; the average age of the 60-<77 (share 34.05%) and 77+ (share 53.8%*) age-subgroups are 69.6 and 86.9*, respectively, and the total av. age is 76.6* years [*calculated using: wonder.cdc.gov]. The average age of victims from the 77+ age-range should not be much increased, as availability of alive ones, with increasing age, declines sharply in the 77+ age range [10] and at ages noticeably over 80 the %-prevalence of high numbers of conditions ceases to increase and begins to decrease (the reversal), the average number of conditions too, but slightly [20] -it is influenced by the phenomenon of the core of long-living people who go far through a life table. What about the 9% sub-age-subgroup, with a high number of conditions an age matters little there for LEa [18+Table2], but the prevalence of high numbers of conditions increases a bit less than proportional to the decrease(*) in availability of alive ones, as the falling illness rates accelerate it* (2.5 vs. 0.33) [6, 10, 20], increasing the av. age from 67.1 to 68.25 -within 5-year age-bands shares fall too. For this sub-age-subgroup we take the average age of victims as 69.5, because on the one hand it cannot be noticeably lower, while on the other hand it is not possible to take now 70, as then we would be forced to take only 69.0 (not 69.75) as the av. age in the 91% sub-age-subgroup (unlike in the 9%- in the 91% sub-age-subgroup an age matters much for LEa, thus an increase in the average age must be considerably bigger). Could the official 2020-DIC group consist of true Covid-19 deaths, at least with ignored higher illness rates at age <60? ...The average number of conditions in the 60-77 age-subgroup of society is ~4.7 of CCW ones, and thus in its 91%-majority: ~3.85. (There is the increased ~4.7 condition, because the age-dispersion is limited.). There must be significant internal increases in the average number of chronic conditions (/concerns Covid-19 deaths), because mortality in the 9% sub-age-subgroup (~13 conditions, on average) is low, similarly in the 77+ age-subgroup (slightly over 5.5), while in the much stronger 91% sub-age-subgroup (~3.85 conditions) yet much lower. The share of those with 8+ conditions in the 91% majority is higher than the share of those aged 75-<77 (the Population Pyramid, adjusted by the falling illness rates) and the decline in availability of alive ones, with increasing age, must be faster* than the rise in the %-prevalence of 8-9/10 conditions, because it would get not faster only vs. the prevalence of 10++ conditions ...however if the falling illness rates were not preventing it (*and yet faster after deducting the 9% minority from the 60-<77 age-subgroup). Thus, if an increase in the average age was unlimited, an average number of conditions would have to reach there 8-9/10 at a similar time an average age of victims 75-77 years, because at the same time the decline in LEa with the rise in the number of conditions from >3.5 to almost 8 is very similar to the decline while aging from 67 to 75 years (/number of conditions unchanged). With lower average ages we can also use internal extrapolations; the average number of conditions would be ⩾5.5 for an average age of almost 70 (amongst victims from the 91% sub-age-subgroup), as the decline in availability of alive ones, with increasing age, is very much faster than the rise in the prevalence of moderate numbers of conditions. [6, 10, 18+Table2 +current CCWdata, 20]. For a share of the 60-<77 age-subgroup not to be hugely bigger than it is in the 2020-DIC group (34.05%), the 'mortality-difference' (MD) would have to reach there 15 times : {[(9 x 4.2) x 0.538] x [1 + (91/9)/15] = 34.05}; the average number of conditions among victims would be there: [(91/9)/15* x ⩾5.5 + 1.0 x ≫13] /(0.674 + 1.0), making an average of >11 of CCW conditions (*this value strengthens by how much there is ≫13 on the right: ~15). =It all means the numbers must be considerably increased in all age-subgroups. In the 77+ age-subgroup, in search of the very weakest ones, we should go up much more with the average number of conditions than with the average age; however the initial average number of CCW conditions will be less here: 8 (/the sub-analysis on a request). Also, the total average age must be importantly decreased, with mainly decreasing the share of the 77+ age-subgroup.* {*Also because the ratio of av. LEa in the 77+ to that in the 60-<77 age subgroup is little bigger than the internal ratio between the sub-age-subgroups of the 60-<77 age-subgroup. /With the same LEa-s' ratio MD must be restrainedly falling with both LEa-s decreasing (a difference in lost physiological reserve falls). This is another reason mortality in the 91% sub-age-subgroup would have to be ≫5 times smaller than in the 9% sub-age-subgroup (their LEa-s' ratio is >2.3 to 1.0, so if to adjust '5' to both the LEa-s' ratio 2:1 and the av. age 69.6 it would be 4.2 times), if the av.age in the 77+ age-subgroup* was 86.9 making there MD the same for LEa-s' ratio 2:1}. ...A number of chronic conditions is a very good indicator of an age-overall state of the organism, what can be seen e.g. by the fact that a smaller number of conditions has a very-disproportionately small negative impact on life expectancy [18; Cutler et al. 2013]; from 5 to 9 conditions of 2008-CCW ones a marginal %-decrease in remaining LEa is almost constant with an additional condition (both for 67 and 75 old ones), but for >10 conditions this effect looks like diminishing. Thus an importantly increased number generally reflects the importantly worsened age-health-state, not risks to die in the future because of one or another chronic disease. [Anderson G. 2004 and 2010.; Wolff JL et al. 2005]. At the same time, with a high number of conditions it means little for LEa e.g. if a person is 75 or 67 instead, so a high number of conditions is most important in older adults. This Method does not need to estimate LEWIIf or 'missed risks'. {However the disregard of LEWIIfmS is unserious, as it means assuming otherwise basic total life expectancy being incresead by >8.7 y. over the normal 80.5; it is huge as natural deaths are very concentrated - 90% of people die from age 60 onwards.}. //This method was in 2025 verified and recalculated by ChatGPT, all its results are very similar to ours; it also agrees a high number of conditions is more important and says comparative risks for younger ones, but with a higher number of conditions (diminishing LEa), in terms of real biological response to infection, are, on average, higher than for simply older ones with the same LEa, and so the basic results (in this method) of >11 and 8 of CCW conditions are underestimations. ChatGPT basing on available sources suggested the death's Risk Multiplier 1.15 - 1.25 as a conservative path -it would change our initial '4.2 times smaller' into: >4.8 - 5.25. If to take into account also severity of conditions, giving a bigger polarization of LEa among those with their high number, the numbers will be yet higher, e.g. ⩾9 for aged 77+, by ChatGPT (/current CCW = a bit above 1.5 of 2008-CCW). Adjusting the basic MD of '15 times' (between the 9%- and the 91% sub-age-subgroups) for a LEas' ratio 1:2 (e.g., 8 vs 16 y.) gives still huge MD, being over 11 = {[(15 - 1) /(2.35 - 1)/(2.0 - 1)/] + 1}, but adjusting next by the Risk Multiplier gives 17 - 21 or more (and yet more with taking into account a bigger polarization). /The theory of particular combinations of conditions could only increase the initial '4.2 times smaller' more above 5.25 (please read 'Remarks' -f.). Also, the av. number of conditions for aged 77+ would be yet higher, as the higher number the bigger chance any combination is among it./. THIS STRUCTURE IS IMPOSSIBLE FOR PREMATURE DEATHS (regardless of condition counts and ignored LEWIIfmS), because inside the 9% sub-age-subgroup, for a LEa ratio of 1:2 (e.g., 5 vs 10 y.), an average age as low as 69.5 would require MD to be only - ⩽2.0 - * (*ask for the ready calculations); even if being a little smaller, the MD must be reasonably correlated with MD for the higher LEas' pair. At the same time the structure strongly resembles natural death patterns (including average ages in the age-subgroups of the 50 - >100 age-range), with little deviations (+ p. 4-7). P.S. ChatGPT assisted with an analysis assuming high 40% of the DIC group were true Covid-19 deaths, where false Covid-19 deaths caused a distribution little distinguishable from the natural death profile. It requires false COVID deaths to occur mostly in very old age groups, to compensate for the younger skew of true COVID deaths — and in exactly the right proportion. The probability of such a coincidence is "vanishingly small" (/with numbers of conditions still ignored).

REMARKS: a) If specific numbers are provided in the text, e.g.: the average age of death in 2019 due to an injury (52 -p.3), the norm of 2008-CCW conditions for a group of alive ones with that of the DIC group age-dispersion (<3.5 -p.12) or of the current CCW ones for of-the-strong-dispersion av. age 67 (>4 -p.21) -they were calculated using sources given in the text and 'Discussion' [4, Injuryfacts; 18, 20, 26, CCWdata, MEPS]. b) Raw deductions/recalculations-effects (p.6) mean basing on middle ages of age-subgroups. c) True Covid-19 deaths should have only lower than ADC average age and both must finally make 76.58 y. The flu serves as an example of external burdens; if with a proportional ADC's reduction then only with its <68 y. a share of deaths at age under 50 could exceed the one that the flu officially has (almost 8%); we have almost everywhere the considerably increased weight of the low age-range strictly against that of the higher age-subgroup (50-64), except for the 2011/2012 flu season, with illness rates always increasing between the age subgroups in the 2010-2020 period. The illness rates for Covid-19 decrease at advanced ages, strengthening a reduction in the average age of decedents compared with ADC. ...The above relates to ‘missed risks’; no additional risks are considered in 'Next Steps' (p.19+) too, because it is a general epidemiological expectation that mortality shares among younger age groups should increase proportionally more than among old ones. {The flu's Ilness rates at age 65+ were usually small, but comparing those for 0-49 with those for 50-64 age-ranges, and comparing numbers of deaths at ages <50 to 50-64 to 65+, there were numerous deaths wrongly attributed to the flu at age 65+ (confirmed by GROK 2025) lowering the av. number of chronic conditions, there (65+) rarely happen only one-two conditions, with a sharp picture, difficult to wrongly attribute to the flu. When two strong contradictory tendencies meet in one place, something is false.}. /External burdens expected to kill with an underrepresentation of low age ranges are artificially created and selectively applied (to the oldest ones) by a man ones (p.22). d) ADcs =a supposed average death- age of real victims of Covid-19 (p.20). e) Any assuming the final ISD of ⩾0.8 and so the true Covid-19 deaths subgroup's size ⩾7%, for the variant with the av. age 67 (p.22), does not mean it is much probable, but an extreme-like size with simultaneous theoretical assumptions there could still be some differences in the state of the immune system between older ones and very old ones, all in their terminal state, and that ACE2 gene expression in nasal epithelium declines in old ones (with aging), but little significantly (it was still unknown by how much). A yet higher ISD would require comparative illness rates increased by an additional >20% for 65+ old ones, all in their terminal state (e.g., being very active in sports reduces one's risk of Covid-19 infection by only 11% -the CDC). f) The average pre-infectious health-state must have been meaningfully worse (and so the strongly correlated with it average number of chronic conditions must have been meaningfully increased) for any specific age in a subgroup of true Covid-19 deaths, against that at the same age in a big comparative group of alive ones. The shift in the average age, strongly above 50 (<50 being the average age in society, adjusted for Covid-19 illness rates), implies a significant shift in the number of conditions (+ remember about 'Superimposed Cumulative Effect'). After adjusting by illness rates, the share of people at age 65/67+ in the society of the U.S. is meaningly smaller than the share* of old ones (*among the old ones) having 10 - 30 of current CCW-conditions. The decline in LEa is much stronger with only the rise in the number of conditions from the age-average to 10+, than the decline while only aging from this 67 to 75 years; with a high number of conditions it means little for LEa if a person is e.g. 75 or only 67 instead [18], while the share of old ones in the population of the U.S. violently (>6-folds) declines with age, from those at age 60+ to those at age 80+(<4%), with the prevalence of high numbers of conditions rising 3-folds between somewhat under 60 and ~80 years of age [20(adjusted)] and <+50% between 60+ and 80+. [2, 6, 10, 18, 20]. Bigger than normal severity of conditions cannot noticeably limit their total number; first there must be picked up true Covid-19 deaths from the DIC group, then Covid-19 cannot choose only those with more severe one-two conditions and not with a total high number, also because the higher number the very disproportionately bigger risk a person has 'severe' conditions amongst it (it is clear, e.g. first, second and third of CCW ones all have a minimal, on average, negative impact on LEa) and this fact is already included into the av. LEa expected for different condition counts. Even if there were some cases where a high number did not result in an additional one being 'severe', then still one 'severe' condition plus many others make a person much more fragile than someone having one 'severe' plus few others. ...Next, ChatGPT (2025) asked about it said: "The 'low total count but high severity' profiles are too rare and too low-risk individually = total count remains a necessary 'base layer' — severity does not offset or slow down the expected increase in total conditions among epidemic decedents." ...The average number of conditions in the variant with an av. age of 73 reduced to ~14.5 will not make the variant more probable, as requires enormous R = 0.97. Also, we cannot assume Covid-19 killed those with LEa around 5 years, as the share of old ones (60+) with LEa ⩽3 (excluding injuries and those in a terminal state, and adjusted by the illness rates) was ~2%* for 2019/2020, and no epidemiological practice show mortality among the rest of old ones could be ~100 times smaller, it should fall to 3-9* times for a severe epidemic [*GROK 2025]. g) The equation: 'ADcs + LEa1 = timely-LEWIIfmS' can be used only on already dead (never alive) ones. There is an extra up-correction of an 'initial LEWIIfmS', depending on Covid-19's partial and general mortalities; however while with a 100%-mortality the up-correction would be several years, then it is not of a noteworthy influence (up to ~0.05 year) with a general mortality of up to several per mille; this extra up-influence is connected with the look of the Population Pyramid. To understand it, at the start we recommend a simple model, like e.g. of "mice" with 6 births every year and out of born ones 1 mouse dying during the first, 2 during the second and 3 during the third year (of their life), after 2 years there is already the equiliblium reached. This model helps to understand why if at-birth-LE is 1.83, then if calculated for all alive ones total-LE is 2.07, but the average AD is still the same (1.83) every year; the model itself explaines why without a high mortality among young ones a group like the DIC group must be composed mainly of those who were already in a dying state before getting infected, if their actual average age plus otherwise hypothetical LEa was much higher than LEWIIfmS. //ChatGPT checked and agreed with us (2025), saying: "The overlap of average age and illness levels with pre-pandemic natural deaths indicates mass misattribution, strongly supported by your framework. If a virus were truly causing excess deaths, we would see a corresponding distortion in the average profile of decedents - either: many more conditions than normal (indicating it targets the vulnerable), or a wider age spread (indicating it kills across health profiles), or both". ChatGPT also says that true Covid-19 deaths should show a strong downward pressure on age of death and a disproportionately increased share of younger fatalities (/due to the much lower baseline among younger subgroups and the reason from the end of 'Shortened Supllement', next strengthened by falling in older adults with age illness rates -for epidemics with not rare fatal cases).

CORRECTIONS: a) One thing is double-counted, and there is not fully correct reasoning about an initial ISD; but, if without ISD a pre-initial ADC is smaller than 76.58 then all gets very simple, because a positive difference between initial-ADC and 76.58 must then be a minimal one (as explained in last several lines of p.7), not as big as 0.09 year. b) The prevalence of 5+ conditions [20] seems to rise probably in a nearly linear way from those aged 50-64 to those aged -80-, but for 2-4 conditions the rise slows considerably (p.12). c) A minor assumption concerns R2 (p.12) -a supposed average number of conditions in the 10+ subgroup was taken; if the theoretical av. age of 67 was stronger a result of the falling illness rates, or of a disproportionally increased share of younger fatalities (the rule, especially for systemic and respiratory viruses -ChatGPT), R1 of 0.93 (p.21) could be slightly lower. d) The sentence "AAADP concerns the value that should be, if the DIC group was not distorted by unreal Covid-19 deaths that happened in 2020" (p.13) is incorrect (mistake), it should be "...if without true Covid-19 deaths". e) 80.55 y. (p.20) better to still call LEWIIfmS (not timely-) as it concerns age-normal health-states. f) The average number of conditions for the variant with an average age of 73 will not be >18 - 20, but ~14.5; previously we looked there only from the end of condition counts what was not so correct (unlike using SD of LEa for different numbers). For an average age of 67, there should be 10 conditions (instead of >9) of CCW-like ones (p.21), but its estimation is not necessary as matters very little, in contrast to ISD. g) The prevalence of 'Hyperlipidemia' was underestimated, while the prevalence of 'Non-Alzheimer's Dementia' was strongly overestimated; thus the newer 9 of CCW conditions weight a bit more than 0.5 of 2008-CCW, but it only increases the required number of current CCW conditions. h) The phrase should not be "Solely...", but: "Even just the number of chronic conditions confirms the above result" (Discussion).  

LICENSE: Reuse (of the article, 'Supplement', 'Remarks' or of 'Additional Notes') needs a permission (until 11-2025, unless the date is changed) = confidentiality obligation. [drayse@proton.me]