X-Message-Number: 9468
Date: Sun, 12 Apr 1998 17:44:45 -0400 (EDT)
From: Charles Platt <>
Subject: Risk Assessment and Cryonics Growth

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Computer Simulation Shows Future Impact of Growth on Standby, 
Transport, and Perfusion Services in a Cryonics Organization 
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             For 20- and 40-year future periods 
     assuming annual growth rates ranging from 0% to 20% 
 
                       by Charles Platt
                     President, CryoCare
 
 
Summary 
 
Most cryonicists favor growth, but a minority (including 
myself) have wondered about possible penalties--such as a 
heavier case load for standby/transport teams. 
 
In addition I have wondered about the possibility of two 
cryonics members dying simultaneously, which would create 
major logistical problems. 
 
To address these concerns I have written a computer program 
that generates likely future scenarios. The results are 
reassuring, at least for my own organizaton, CryoCare. During 
the next 20 years, if there is ANY growth rate ranging from 0 
to 10 percent, generally speaking we should expect an average 
of 1 case per year and a maximum of 4 cases in any one year, 
with a 1% chance (or less) of simultaneous cases, and some 
years in which no cases occur at all. I think it's reasonable 
to expect a single standby/transport/perfusion team to manage 
this case load. 
 
These numbers do not change significantly if the median age 
of new members increases from 30 to 40. 
 
The numbers double, more or less, with a growth rate of 20 
percent, which would strain a single team to the limit over 
the next 20 years and would probably result in 2 simultaneous 
cases during that period. 
 
If a 20 percent growth rate continues over 40 years, this 
creates a major impact, including a probable maximum of 300 
cryopreservation procedures in any one year and a 50-50 
chance of any one case being simultaneous with another case. 
However, with 20 percent growth per year, by the end of a 40-
year period the cryonics organization would have expanded 
from 80 members to about 100,000 members, and would be well 
placed to afford several standby/transport/perfusion teams to 
cope with the case load. 
 
CONCLUSION: We need not be anxious about the consequences of 
moderate growth in cryonics over the next two decades at 
least. 
 
 
Details 
 
For practical purposes, bearing in mind the time required to 
complete a case and redeploy equipment, "simultaneous" cases 
are those which occur fewer than 3 days apart. Ralph Merkle 
compares the problem of calculating the probability of this 
with the well-known "birthday" problem, which asks how many 
people should be added to a room in order to reach a 50-50 
chance of any two people sharing the same birthday. However, 
our situation is more complicated because elderly people have 
a higher risk of dying than younger people. Therefore, if the 
average age of cryonics members increases over time (as is 
likely, since most people join in their middle years and then 
remain signed up after that), the risk of simultaneous death 
also increases with time, even if the number of members in an 
organization remains constant. 
 
Rather than try to figure this probability, I wrote a program 
that uses actuarial tables and birth dates to figure the 
chance of _each individual_ dying in this and future years. 
The program selects a random date for each death and notes if 
one death is followed or preceded by another within 2 days or 
less. 
 
Since the program depends on weighted random functions, it 
repeats its projections 100 times and then averages them. 
 
Initially the program was designed specifically for CryoCare, 
but it can be adapted easily for any other organization that 
is willing to supply member birth dates. I am happy to share 
the program freely, because I believe longterm planning based 
on calculated probabilities, rather than guesswork, will be 
good for cryonics generally. 
 
Results of several runs of the program are shown below. Each 
run assumes that the organization has 80 members as of 
January 1st, 1999, more than half of them aged between 40 and 
60 (the age distribution in CryoCare). The program uses 
actuarial data from Statistical Abstract of the United States 
(1997 edition) to figure the chance of death for each person 
according to his/her age. A random-number function, weighted 
with the chance of death, determines whether each individual 
dies or survives. Survivors are moved forward to the next 
year, new members are added, and the process repeats. This 
"cohort" technique is also used by federal agencies and the 
UN to project future population figures based on birth rates, 
death rates, and immigration. 
 
Caveats: 
     Age-related death rates may change in the future, if 
life expectancy increases. This would diminish the future 
case load per year. 
     Cryonicists may enjoy greater longevity than the average 
American population--although I tend to doubt this after 
seeing the high-fat/low-exercise regime enjoyed by many of my 
"immortalist" contemporaries. 
     The death-rate figures that I have used are for the U.S. 
population as a whole, including men, women, whites, and 
nonwhites; but cryonics members tend to be male and white. 
Males die younger than females, but whites live much longer 
than nonwhites. Overall, this means I have slightly 
overestimated the cryonics caseload per year. 
     I have made arbitrary assumptions about new members 
joining the organization. The median age is user-selectable, 
but the age spread either side of the median is always +/- 16 
years, conforming with a rough bell curve. 
     It is possible, of course, that I have made erroneous 
assumptions or math errors that I am unaware of. 
 
Despite these caveats, I believe this is the first time that 
anyone has attempted to model the consequences of growth, and 
the results are useful, since we can now see the _relative_ 
consequences of adjusting variables such as membership growth 
and median age of new members. 
 
Note: the tables below will not display legibly unless you 
use a monospaced font such as Courier. 
 
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     Table 1
     Simulation period: 20 years
     Median age of new members: 30 
 
     Situation at the end of the projected period: 
 
                     percent growth rate during whole period
                       0       3        6        10       20  
 
Living members        57     112      212       464     2779
 
Cryopreserved         23      24       25        28       45
 
Avg cases/year         1       1        1         1        2
 
Averaged MAXIMUM       4       4        4         4        7
cases in any year
 
% chance of the next   1       1        1         1        2
case occurring less than 3 days after the current case
 
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     Table 2
     Simulation period: 20 years
     Median age of new members: 40
 
     Situation at the end of the projected period: 
 
                     percent growth rate during whole period
                       0       3        6        10       20  
 
Living members        57     111      208       454     2724
 
Cryopreserved         23      25       28        33       65
 
Avg cases/year         1       1        1         2        3
 
Averaged MAXIMUM       4       4        4         5       11
cases in any year
 
% chance of the next   1       1        1         1        3
case occurring less than 3 days after the current case
 
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     Table 3
     Simulation period: 40 years
     Median age of new members: 30
 
     Situation at the end of the projected period: 
 
                     percent growth rate during whole period
                       0       3        6        10       20  
 
Living members        22     142      574      2836   102115
 
Cryopreserved         58      67       84       135     1139
 
Avg cases/year         1       2        2         3       28
 
Averaged MAXIMUM       5       5        7        13      184
cases in any year
 
% chance of the next   1       1        2         4       41
case occurring less than 3 days after the current case
 
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     Table 4
     Simulation period: 40 years
     Median age of new members: 40
 
     Situation at the end of the projected period: 
 
                     percent growth rate during whole period
                       0       3        6        10       20  
 
Living members        22     131      523      2651    96573
 
Cryopreserved         58      74      106       204     2009
 
Avg cases/year         1       2        3         5       50
 
Averaged MAXIMUM       5       6        9        20      328
cases in any year
 
% chance of the next   1       1        2         6       55
case occurring less than 3 days after the current case
 
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The source code for this program is heavily annotated, easy 
to understand, and was written in an extended dialect of 
BASIC that could be adapted very easily for the old Microsoft 
QuickBASIC compiler. I will email the code to anyone who 
wants it. Also I can send the compiled program as an .EXE 
file to anyone who is interested. It will run under any 
version of MS-DOS. 
 
Note that since the program was written within less than a 
day, its error trapping is rudimentary, and there aren't any 
cute little buttons or dialog boxes. 
 
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