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RISK BENEFIT ANALYSIS Special Lectures University of Kuwait Richard Wilson Mallinckrodt Professor of Physics Harvard University January 13th, 14th and 15th 2002

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RISK BENEFIT ANALYSISSpecial Lectures

University of KuwaitRichard Wilson

Mallinckrodt Professor of PhysicsHarvard University

January 13th, 14th and 15th 2002

January 13th 9 am to 2 pm

What do we mean by Risk?Measures of Risk

How do we Calculate Risk?(a) History

(b) Animal analogy(c) Event Tree

Day 2. January 14th 2002Uncertainties and Perception

Types of Uncertainties

Role of Perception.Kahneman’s 2002 economics Nobel prize

We will try to show his effect in classList of interesting attributes

Major differences between Public and Expert perceptions

Day 3 January 15th 2003Formal Risk-benefit comparisons.

Net Present Value Decision Tree

Value of InformationProbability of Causation

Cases:Chernobyl, TMI

BhopalALAR as a pesticide

Research on particulatesSabotage and Terrorism

The Biggest Risk to Life is Birth. Birth always leads to death!

We talk about premature death.

More risk 38 60 55 43 78Less risk 36 13 26 13 6Same amount 24 26 19 40 14Not sure 1 1 0 4 2

Table 1-1. Public Opinion Survey Comparing Risk Today to Risk of Twenty Years Ago

Q: Thinking about the actual amount of risk facing our society, would you say that people are subject to more risk today than they were twenty years ago, less risk today, or about the same amount of risk today as twenty years ago?

Top Coroprate

Executives (N=401)

Investors, Lenders (N=104)

Congress (N=47)

Federal Regulators

(N=47)

Public (N=1,488)

MEASURES of Risk

Simple risk of Death (assuming no other causes)by age

by cause

Risk of Injury by causeby type

by severity

Peryear

lifetimeunit operation

eventton

unit output

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

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)

Expectation of Life at Birth in the United States(1900-1928: Death Registration States only)

0

10

20

30

40

50

60

70

80

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Year

Exp

ecta

tion

of L

ife a

t Bir

th

Expectation of Life at Birth in the United States(1900-1928: Death Registration States only)

0

10

20

30

40

50

60

70

80

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Year

Exp

ecta

tion

of

Lif

e at

Bir

th

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 one’s

birth.

Both the specific death rate and the life expectancy at birth have a

dip at 1919world wide influenza epidemic.BUT anyone born in 1919 will

not actually see this dip.Peculiarity of definition of life

expectancy

Life Expectancy in the USA

30

35

40

45

50

55

60

65

70

75

8019

00

1908

1916

1924

1932

1940

1948

1956

1964

1972

1980

1988

1996

All Races

White

Black

Figure 1-3aLife Expectancy

0

10

20

30

40

50

60

70

80

90

100

1750 1800 1850 1900 1950 2000

France

Japan

Sweden

Russia

Papua (54)

Gambia (37)

Palasra (52)

Half the “Beijing men’ were teenagers.

This puts life expectancy about 15Roman writings imply a life

expectancy of 25.Sweden started life expectancy

statistics early.Russia has been going down

since 1980

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

Figure 1-4 Occupational Risk in Coal Mining, US

0.00

1.00

2.00

3.00

4.00

1931 1941 1951 1961 1971 1981 1991

Year

Acci

dent

al D

eath

Rat

e

Per Million ManHours

Per Million Tons ofCoal Mined

Per ThousandEmployees

Risk is different for different measures of risk.

Different decision makers will use different measures depending

on their constituency

Figure 1-5 Accidental Death Rates by Type of Coal Mine, U.S.

0.00

0.50

1.00

1.50

2.00

1931 1941 1951 1961 1971 1981 1991

Year

Acc

iden

tal D

eath

s pe

r m

illi

on m

an

hour

s w

orke

d Underground Mines

Surface Mines

Figure 2-1 Death Rates for Motor Vehicle Accidents in the United States

0

5

10

15

20

25

30

35

1925 1935 1945 1955 1965 1975 1985 1995

Year

An

nu

al D

eath

Rat

e

per 100,000 population

per 10,000 vehicles

per 1 million vehiclemiles

Accidental Death Rates by Type of Coal Mine, U.S.

0

1

2

3

4

1931 1941 1951 1961 1971 1981 1991

Year

Acc

iden

tal

Dea

ths

per

mil

lion

ton

s of

coa

l pr

odu

ced

Underground Mines

Surface Mines

Three Different Metrics of Occupational Risk in Coal Mining, United States

0.00

1.00

2.00

3.00

4.00

1931 1941 1951 1961 1971 1981 1991

Year

Acc

iden

tal D

eath

R

ate

Per M ill ion M anHours

Per Mil lion To ns ofCoal Mined

Per Thous andEmploy ees

Accide ntal De ath Rates by Type of Coal Mine, U.S.

0.00

0.50

1.00

1.50

2.00

1931 1941 1951 1961 1971 1981 1991

Year

Acc

iden

tal D

eath

s pe

r m

illio

n m

an h

ours

w

ork

ed Underg rou nd Mines

Surface Mines

Accide ntal De ath Rates by Type of Coal Mine, U.S.

0

1

2

3

4

1931 1941 1951 1961 1971 1981 1991

Year

Acc

iden

tal

Dea

ths

per

mil

lion

tons

of c

oal

prod

uced Undergroun d Mines

Surface Mines

Figure 1-3aLife Expectancy

0

10

20

30

40

50

60

70

80

90

100

1750 1800 1850 1900 1950 2000

France

Japan

Sw eden

Russia

Papua (54)

Gambia (37)

Palasra (52)

Annual Occupation Fatality Rates (US)

0

5

10

15

20

25

30

35

40

45

50

1978

1980

1982

1984

1986

1988

1990

(Year)

Death

s p

er

100,0

00

em

plo

yed

Agriculture, Forestry,Fishing

Mining

Construction

Manufacturing

Private Industry

Transportation andPublic Utilities

Wholesale & RetailTrade

Finance, Insurance,Real Estate

Services

EpidemiologyAssociate Death (or other Measure)

to Postulated CauseIs 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) > 2

Correlation ofNumber ofBrooding sSorkswith NewbornBabies

Sies, H. (1988) Nature 332, 495

A contribution to epidemiology....

Associations vs. Cause-Effect

Figure 2-7Alternative Dose-Response Models That Fit the Data

Dose

Re

sp

on

se Super Linear

Linear

Hockey Stick

Hormesis

Datum

Datum

Threshold

Annual Death Rate By Daily Alcohol Consumption

0200400600800

1000120014001600

0 0.5 1 2 3 4 5 6

Average Number of Drinks Per Day

Dea

th R

ate

(Per

100

,000

)

Alcohol-augmentedconditionsCardiovasculardiseaseAll causes

We contrast two types of medical response to pollutants.

ACUTE TOXIC EFECTA dose within a day causes death within a few days

(causality easy to establish)

CHRONIC EFFECTlower doses repeated give chronic effects

(cancer, heart) within a lifetime.(Causality hard to establish)

Characteristics• One dose or dose accumulated

in a short time KILLS

• 1/10 the dose repeated 10 times DOES NOT KILL

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)

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)

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

Note that the incremental Risk can actually be greater than the simple linearity assumption of a

non-linear biological dose-response is assumed

ANALOGY of animals and humans

Start with Acute toxic effectsdata from paper of

Rhomberg and Wolf

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.

Transparency from Crouch

Transparency of Allen et al.

Risks of New TechnologiesOld 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!

Risks of New technologiesWe now want more safety

New technologies can kill more people at once.

We do not want to have ANY history of accidents.

Design the system so that if a failure occurs there is a technology to fix it.

(called DEFENSE IN DEPTH or Factorize the technology.)

Draw an EVENT TREE following with time the possible consequences of an

initiating event. Calculate the probability

First done for Nuclear Power(Rasmussen et al. 1975)

Schematic of a nuclear power plant

Simple event tree

Final Probability for an accident with serious consequencies

P = P1 X P2 X P3 X P4

which can with care be 1/10,000,000

but without care can be 1/1,000

Simple Fault tree

ASSUMPTIONS

(1) We have drawn all possible trees with consequencies

(2) The probabilities are independent (design to make them so; look very

carefully about correlations(3) Consider carefully - with some confidentiality - actions that can artificially correlate the separate

probabilities

The event tree analysis SHOULD have been used by NASA in the

1980s and it would have avoided the Challenger disaster

The main steps of the analysis of impact pathways(Courtesy A. Rabl).

DOSE

IMPA

CT

Dose-ResponseFunction

impact(e.g., cases of asthma due to increased

concentration of particulates)

DOSE-RESPONSE FUNCTION(or exposure-response function)

cost(e.g., cost of asthma)

ECONOMIC VALUATION

DISPERSION(e.g. atmospheric dispersion model)

emission(e.g., kg/yr of particulates)

increase in concentrationat receptor sites

(e.g., µg/m3 of particulatesin all affected regions)

SOURCE(specification of site and technology)

Example: Risk of a Space Probe

major risk:Probe (powered by Plutonium) reenters the earth’s atmosphere

burns up spreads its plutonium widely over

everyoneCauses an increase in lung cancer

2 Steps(1) What is the probability of reentry

(2) What is the distribution of Plutonium

Compare with what we know