RISK%20BENEFIT%20ANALYSIS%20Special%20Lectures%20University%20of%20Kuwait%20Richard%20Wilson%20Mallinckrodt%20Professor%20of%20Physics%20Harvard%20University%20January%2013th,%2014th%20and%2015th%202002 - PowerPoint PPT Presentation

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RISK%20BENEFIT%20ANALYSIS%20Special%20Lectures%20University%20of%20Kuwait%20Richard%20Wilson%20Mallinckrodt%20Professor%20of%20Physics%20Harvard%20University%20January%2013th,%2014th%20and%2015th%202002

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Title: RISK%20BENEFIT%20ANALYSIS%20Special%20Lectures%20University%20of%20Kuwait%20Richard%20Wilson%20Mallinckrodt%20Professor%20of%20Physics%20Harvard%20University%20January%2013th,%2014th%20and%2015th%202002


1
Handling Hazards natural and otherwise Universi
ty of Waterloo Ontario, Canada December 3rd
2010 Richard Wilson Mallinckrodt Professor of
Physics (emeritus) Harvard University
2
We always want to find a cause.. Usually to
blame some one. (often to collect money!) Come,
and let us cast lots, that we may know for whose
cause this evil is upon us and the lot fell on
Jonah Jonah 17
3
1000 years ago various jurisdictions tortured a
suspect. If he died under torture too bad If
he confessed he was guilty.
4
As late as 1950 UK common law considered Acts of
God differently from acts of man A brick falling
from the roof was an Act of God with no one to
blame UNLESS You had put up a warning sign
beware of falling bricks. Then you knew it
was dangerous
5
Perrenial conflict Rights of an individual vs
Rights of Society This conflict must be faced
not ignored Quarantine vaccination Profiling
(racial or otherwise)
6
Since about 1970 analysts do not make the
distinction Natural Hazards can be analyzed and
precursers found Prevention of adverse
consequences is similar for natural and man made
hazards
7
The Biggest Risk to Life is Birth. Birth always
leads to death! We talk about premature
death. Polls say Risk is Increasing (next
slide) but history says the opposite. What do
the polls mean?
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Note the little peak about 1918. What is it due
to? First world war? NO! Flu epidemic! On the
next slide we see the double dip in life
expectancy for France. For France flu was as bad
as the war!
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WHAT IS LIFE EXPECTANCY? An artificial construct
assuming that the probability of dying as one
ages is the same as the fraction of people dying
at the same age at the date of ones birth.
13
The specific death rate Peaks, and the life
expectancy at birth has a dip at 1919 world wide
influenza epidemic. BUT anyone born in 1919 will
not actually see this dip. Peculiarity of
definition of life expectancy
14
Half the Beijing men were teenagers. This puts
life expectancy about 15 Roman writings imply a
life expectancy of 25. Sweden started life
expectancy statistics early. Russia has been
going down since 1980
15
Risk is Calculated in Different Ways and that
influences perception and decisions. (1)
Historical data (2) Historical data where
Causality is difficult (3) Analogy with
Animals (4) Event tree if no Data exist
16
Risk is different for different measures of
risk. Different decision makers will use
different measures depending on their
constituency
17
RISK MEASURES (continued) Loss of Life Expectancy
(LOLE) Years of Life Lost (YOLL) Man Days Lost
(MDL) Working Days Lost (WDL) Public Days Lost
(PDL) Quality Adjusted Life Years
(QALY) Disability Adjusted Life Years
(DALY) Different decisions may demand different
measures
18
LOLE from cigarette smoking In USA 600 billion
cigarettes made (presumably smoked) 400,000
people have premature death (lung cancer, other
cancers, heart) 1,500,000 cigarettes per
death Each death takes about 17 years (8,935,200
minutes) off life or 6 minutes per
cigarette ABOUT THE TIME IT TAKES TO SMOKE
ONE (easy to remember)
19
Risks calculated from History seems simple.
BUT The number of people dying and the number of
persons in the risk pool often come from
different data bases. Also units are often
different
20
Forecasting the future based upn the past Weather
forecasting vs Fortune telling 1835 UK vagrancy
act fortune telling illegal Islam had a similar
restriction Scientists claim they are
different BUT 2008 Climate gate runs into the
same problem.
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Risks of New Technologies Old fashioned approach.
Try it. If it gives trouble, fix it. E.g. 1833
The first passenger railroad (Liverpool to
Manchester) killed (a member of parliament) on
the first day!
23
Risks of New technologies We now want more
safety New technologies can kill more people at
once. We do not want to have ANY history of
accidents.
24
Plot an EVENT TREE Start with an accident
initiator Consider a way of mitigation
effects What happens when that does not
work? First done for nulear power Rasmussens's
reactor safety study 1975
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We try to get each step independent of the
others. (Design a reactor that way) Then the
probabilities MULTIPLY
27
Accident frequency P1 X P2 X P3 X
P4 Flood Earthquake Sabotage (terrorism) can
couple to steps TTHIS HELPS US TO FOCUS
28
Evacuation Plan April 27th
29
1100 buses left Kiev April 27th
30
The event tree analysis SHOULD have been used by
NASA in the 1980s and it would have avoided the
Challenger disaster
31
LNG facilities Chemical refinery accidents NASA
adopt these procedures HOPEFULLY SOON Building
Industry Oil well drilling
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Annual Occupation Fatality Rates (US)
38
Epidemiology Associate Death (or other
Measure) to Postulated Cause Is it statistically
significant? Are there alternative causes
(confounders)? THINK. No case where cause is
accepted unless there is a group where death rate
has doubled. Risk Ratio (RR) gt 2
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We contrast two types of medical response to
pollutants. ACUTE TOXIC EFECT A dose within a day
causes death within a few days (causality easy to
establish) CHRONIC EFFECT lower doses repeated
give chronic effects (cancer, heart) within a
lifetime. (Causality hard to establish)
41
ANALOGY of animals and humans Rodents do not
look like people Start with Acute toxic
effects data from paper of Rhomberg and
Wolf (next slide)
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Two problems in human diseases Effect is often
delayed from the Cause then Causality is hard to
prove. Proof of an effect is at high dose we
want to know effect at low dose
44
Early Optimism Based on Poisons
There is a threshold below which nothing
happens __________ J.G. Crowther 1924
Probability of Ionizing a Cell is Linear with
Dose
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CRITICAL ISSUES FOR LINEARITY at low doses
  • THE POLLUTANT ACTS IN THE SAME WAY AS WHATEVER
    ELSE INFLUCENCES THE CHRONIC OUTCOME (CANCER)
    RATE
  • CHRONIC OUTCOMES (CANCERS) CAUSED BY POLLUTANTS
    ARE INDISTINGUISHABLE FROM OTHER OUTCOMES
  • implicit in Armitage and Doll (1954)
  • explicit in Crump et al. (1976)
  • extended to any outcome Crawford and Wilson (1996)

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  • Characteristics
  • One dose or dose accumulated in a short time
    KILLS
  • 1/10 the dose repeated 10 times DOES NOT KILL

50
Typically an accumulated Chronic Dose equal to
the Acute LD50 gives CANCER to 10 of the
population. Assumed to be proportional to
dose E.g. LD50 for radiation is about 350
Rems. At an accumulated exposure of 350 Rems
about 10 of exposed get cancer. What does that
say for Chernobyl? (more or less depending on
rate of exposure)
51
50 of all chemicals tested are carcinogenic in
rodents Scientific issue is the dose and the
risk Which are regulated is a political issue
.
52
Holiday Dinner Menu showing the natural
carcinogens that are present   Appetizers CREAM
OF MUSHROOM SOUP hydrazines CARROTS aniline,
caffeic acid CHERRY TOMATOES benzaldehyde,
caffeic acid, hydrogen peroxide, quercetin
glycosides CELERY caffeic acid, furan
derivatives, psoralens Assorted Nuts MIXED
ROASTED NUTS aflatoxin, furfural Green
Salad TOSSED LETTUCE AND ARUGULA WITH
BASIL-MUSTARD VINAIGRETTE allyl isothiocyanate,
caffeic acid, estragole, methyl
eugenol Entrees ROAST TURKEY heterocyclic
amines BREAD STUFFING (WITH ONIONS, CELERY, BLACK
PEPPER MUSHROOMS) acetaldehyde, ethyl alcohol,
benzo(a)pyrene, ethyl carbamate, furan
derivatives, furfural, hydrazines, d-limonene,
psoralens, quercetin glycosides,
safrole CRANBERRY SAUCE furan derivatives
53
OR PRIME RIB OF BEEF WITH PARSLEY SAUCE benzene,
heterocyclic amines, psoralens Vegetables BROCCOLI
SPEARS allyl isothiocyanate BAKED POTATO ethyl
alcohol, caffeic acid SWEET POTATO ethyl alcohol,
furfural Bread BOLLS WITH BUTTER acetaldehyde,
benzene, ethyl alcohol, benzo(a)pyrene, ethyl
carbamate, furan derivatives, furfural Desserts PU
MPKIN PIE benzo(a)pyrene, coumarin, methyl
eugenol, safrole APPLE PIE acetaldehyde, caffeic
acid, coumarin, estragole, ethyl alcohol, methyl
eugenol, quercetin glycosides, safrole Fruit
Tray FRESH APPLES, GRAPES, MANGOS, PEARS,
PINEAPPLE acetaldehyde, benzaldehyde, caffeic
acid, d-limonene, estragole, ethyl acrylate,
quercetin glycosides Beverages RED WINE ethyl
alcohol, ethyl carbamate COFFEE benzo(a)pyrene,
benzaldehyde, benzene, benzofuran, caffeic acid,
catechol, 1,2,5,6- dibenz(a)anthracene, ethyl
benzene, furan, furfural, hydrogen peroxide,
hydroquinone, d-limonene, 4-methyicatechol TEA ben
zo(a)pyrene, quercetin glycosides JAMINE
TEA benzyl acetate  
54
NATURALLY OCCURRING MUTAGENS AND
CARCINOGENS FOUND IN FOODS AND BEVERAGES ACETALDEH
YDE (apples, bread, coffee, tomatoes)-mutagen and
potent rodent carcinogen AFLATOXIN
(nuts)-mutagen and potent rodent carcinogen also
a human carcinogen ALLYL ISOTHIOCYANATE
(arugula, broccoli, mustard)-mutagen and rodent
carcinogen ANILINE (carrots)-rodent carcinogen
BENZALDEHYDE (apples, coffee, tomatoes)-rodent
carcinogen BENZENE (butter, coffee, roost
beef-rodent carcinogen BENZO(A)PYRENE (bread,
coffee, pumpkin pie, rolls, tea)-mutagen and
rodent carcinogen BENZOFURAN (coffee)-rodent
carcinogen BENZYL ACETATE jasmine tea)-rodent
carcinogen CAFFEIC ACID (apples, carrots,
celery, cherry tomatoes, coffee, grapes, lettuce,
mangos, pears, potatoes)-rodent carcinogen
CATECHOL (coffee)-rodent carcinogen COUMARIN
(cinnamon in pies)-rodent carcinogen
1,2,5,6-DIBENZ(A)ANTHRACENE (coffee)-rodent
carcinogen ESTRAGOLE (apples, basil)-rodent
carcinogen ETHYL ALCOHOL (bread, red wine,
rolls)-rodent and human carcinogen ETHYL
ACRYLATE (pineapple)-rodent carcinogen ETHYL
BENZENE (coffee)-rodent carcinogen ETHYL
CARBAMATE (bread, rolls, red wine)-mutagen and
rodent carcinogen FURAN AND FURAN DERIVATIVES
(bread, onions, celery, mushrooms, sweet
potatoes, rolls, cranberry sauce, coffee)- (many
are mutagens) FURFURAL (bread, coffee, nuts,
rolls, sweet potatoes)-furan derivative and
rodent carcinogen HETEROCYCLIC AMINES (roast
beef, turkey)-mutagens and rodent carcinogens
HYDRAZINES (mushrooms)-mutagens and rodent
carcinogens HYDROGEN PEROXIDE (coffee,
tomatoes)-mutagen and rodent carcinogen
HYDROQUINONE (coffee)-rodent carcinogen
D-LIMONENE (black pepper, mangos)-rodent
carcinogen 4-METHYLCATECHOL (coffee)-rodent
carcinogen METHYL EUGENOL (basil, cinnamon and
nutmeg in apple and pumpkin pies)-rodent
carcinogen PSORALENS (celery, parsley)-mutagens,
rodent and human carcinogens QUERCETIN
GLYCOSIDES (apples, onions, tea,
tomatoes)-mutagens and rodent carcinogens
SAFROLE (nutmeg in apple and pumpkin pies, black
pepper)-rodent carcinogen
55
You MUST do the best engineering calculation you
can BUT if you cannot express it simply People
with think you dont understand it AND THEY ARE
PROBABLY RIGHT
56
Example Risk of a Space Probe major risk Probe
(powered by Plutonium) reenters the earths
atmosphere burns up spreads its plutonium widely
over everyone Causes an increase in lung cancer
57
3 Steps (1) What is the probability of
reentry (2) What is the distribution of
Plutonium (3) Compare with what we know
58
Probability of probe hitting the earths
atmoshere in swing-by Orbit calculated can be
corrected. No large correction (avoiding
saboteur) 1 in 10,000,000
59
Russian workers in Ozersk --10 microCurie
Pu (measurement in skeleton) Double risk of lung
cancer) Pu in atmoshere from bomb explosions
leads to 30 picocurie in each of us 30,000 times
less lung cancer of a heavy cigarette
smoker. This multiplies the risk of the sattelite
hitting the earth (P lt10-11) (Accurate
calculation 10-14)
60
ExAMPLE OF 2 POSSIBLE TERRORIST ACTIONS GO TO
Vatican2009.ppt
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If the distribution of fiber type, size and
shape is identical in the occupational
epidemiological studies and in the
environmental samples of interest, extrapolation
to low doses is comparatively simple
63
Note that the incremental Risk can actually be
greater than the simple linearity assumption of a
non-linear biological dose-response is assumed
64
Assumptions for animal analogy with cancer A
man eating daily a fraction F of his body weight
is as likely to get cancer (in his lifetime) as
an animal eating daily the fraction f of his body
weight.
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Transparency of Allen et al.
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