Risk AnalysisFundamental problems

Short course at Harvard School of Public Health

March 12th 2013Richard Wilson

Mallinckrodt Professor of Physics (emeritus)Harvard University

Estimating A Risk should beNeutral (VERY HARD)

The distinction between calculation and blame or action should be

maintained

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 1:7

1000 years ago various jurisdictions

tortured a suspect.

If he died under torture: too badIf he confessed he was guilty.

As late as 1950 UK common law considered Acts of God

differently from acts of manA brick falling from the roof was an

Act of Godwith no one to blame

UNLESSYou had put up a warning sign:

beware of falling bricks. Then you knew it was dangerous

In general the Courts are to decide conflicts between two parties not to

set societal standardsBUT

I and some others object when incorrect scientific statements are

made in court

Error (often disguised)It is an interesting hypothesis that:

Every cancer starts with a single hit on DNA (by radiation, fiber,etrc)

This is not directly provableBUT it is plabaly wrong to say the a

single radiati

Perennial conflict

Rights of an individual vs Rights of Society

Face the conflict do not ignoreQuarantinevaccination

Profiling (racial or otherwise)

Individuals usually and countries often want revenge

But revenge is rarely justice

Always forgive But NEVER forget

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

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?

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)

Figure 1-1. Death Rates from 1900 to 1998 for Various Age Groups: United States

10

100

1,000

10,000

100,000

20001990198019701960195019401930192019101900

Date

Dea

ths

per

10

0,0

00

per

Yea

r

> 85

75 - 84

65 - 74

55 - 64

< 1

45 - 54

35 - 44

25 - 34

15 - 24

1 - 4

5 - 14

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!

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)

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.

The specific death rate Peaks, and the life expectancy at birth

has a dip at 1919world wide influenza epidemic.

BUT anyone born in 1919 will not actually see this dip.

Peculiarity of definition of life expectancy

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

Risk is different for different measures of risk.

Different decision makers will use different measures depending

on their constituency

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)

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

Forecasting the future based upn the pastWeather forecasting vs Fortune telling

1835 UK vagrancy act: fortune telling illegalIslam had a similar restriction

Scientists claim they are differentBUT

2008 Climate gate runs into the same problem.

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.

Plot an EVENT TREEStart with an accident initiatorConsider a way of mitigation

effectsWhat happens when that does

not work?First done for nulear power:Rasmussens's reactor safety

study 1975

We try to get each step independent of the others. (Design a reactor that way)

Then the probabilities MULTIPLY

Accident frequency =P1 X P2 X P3 X P4

FloodEarthquake

Sabotage (terrorism) can couple to steps

TTHIS HELPS US TO FOCUS

Evacuation Plan April 27th

1100 buses left Kiev April 27th

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

1980s and it would have avoided the Challenger disaster

LNG facilitiesChemical refinery accidents

NASA adopt these proceduresHOPEFULLY SOON

Building IndustryOil well drilling

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 Million Man Hours

Per Million Tons ofCoal Mined

Per ThousandEmployees

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

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 Million ManHours

Per Million Tons ofCoal Mined

Per ThousandEmployees

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 h

ours

w

ork

ed Underground Mines

Surface Mines

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 D

eath

s pe

r m

illi

on to

ns o

f coa

l pr

oduc

ed Underground Mines

Surface Mines

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

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

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)

ANALOGY of animals and humans

Rodents do not look like people

Start with Acute toxic effectsdata from paper of Rhomberg and Wolf

(next slide)

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 dosewe want to know effect at low dose

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

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

Dose

Re

sp

on

se Super Linear

Linear

Hockey Stick

Hormesis

Datum

Datum

Threshold

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)

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

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)

50% of all chemicals tested are carcinogenic in rodents

Scientific issue is the dose and the risk

Which are regulated is a political issue

.

Holiday Dinner Menushowing the natural carcinogens that are present

  Appetizers

CREAM OF MUSHROOM SOUPhydrazinesCARROTS

aniline, caffeic acidCHERRY TOMATOES

benzaldehyde, caffeic acid, hydrogen peroxide, quercetin glycosidesCELERY

caffeic acid, furan derivatives, psoralensAssorted Nuts

MIXED ROASTED NUTSaflatoxin, furfural

Green SaladTOSSED LETTUCE AND ARUGULA WITH BASIL-MUSTARD VINAIGRETTE

allyl isothiocyanate, caffeic acid, estragole, methyl eugenolEntrees

ROAST TURKEYheterocyclic 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, safroleCRANBERRY SAUCE

furan derivatives

OR

PRIME RIB OF BEEF WITH PARSLEY SAUCEbenzene, heterocyclic amines, psoralens

VegetablesBROCCOLI SPEARS

allyl isothiocyanateBAKED POTATO

ethyl alcohol, caffeic acidSWEET POTATO

ethyl alcohol, furfuralBread

BOLLS WITH BUTTERacetaldehyde, benzene, ethyl alcohol, benzo(a)pyrene, ethyl carbamate, furan derivatives, furfural

DessertsPUMPKIN PIE

benzo(a)pyrene, coumarin, methyl eugenol, safroleAPPLE PIE

acetaldehyde, caffeic acid, coumarin, estragole, ethyl alcohol, methyl eugenol, quercetin glycosides, safroleFruit Tray

FRESH APPLES, GRAPES, MANGOS, PEARS, PINEAPPLEacetaldehyde, benzaldehyde, caffeic acid, d-limonene, estragole, ethyl acrylate, quercetin glycosides

BeveragesRED WINE

ethyl alcohol, ethyl carbamateCOFFEE

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

TEAbenzo(a)pyrene, quercetin glycosides

JAMINE TEAbenzyl acetate

 

NATURALLY OCCURRING MUTAGENS AND CARCINOGENSFOUND IN FOODS AND BEVERAGES

ACETALDEHYDE (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

You MUST do the best engineering calculation you can

BUT if you cannot express it simplyPeople with think you dont understand

itAND THEY ARE PROBABLY

RIGHT

Example: Risk of a Space Probe

major risk:Probe (powered by Plutonium) reenters

the earth’s atmosphereburns up

spreads its plutonium widely over everyone

Causes an increase in lung cancer

3 Steps(1) What is the probability of reentry

(2) What is the distribution of Plutonium

(3) Compare with what we know

Probability of probe hitting the earth’s atmoshere in swing-by

Orbit calculatedcan be corrected.

No large correction (avoiding saboteur)

1 in 10,000,000

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 <10^-11)(Accurate calculation 10^-14)

ExAMPLE OF 2 POSSIBLE TERRORIST ACTIONSGO TO Vatican2009.ppt

If the distribution of fiber type, size and shapeis identical in the occupational epidemiological studies and in the environmental samples of interest, extrapolation to low doses is comparatively simple

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

non-linear biological dose-response is assumed

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 of Allen et al.

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)