1 / 60

The Biggest Risk to Life is Birth. Birth always leads to death! We talk about premature death.

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

roster
Télécharger la présentation

The Biggest Risk to Life is Birth. Birth always leads to death! We talk about premature death.

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. RISK BENEFIT ANALYSISSpecial LecturesUniversity of KuwaitRichard WilsonMallinckrodt Professor of PhysicsHarvard UniversityJanuary 13th, 14th and 15th 2002

  2. January 13th 9 am to 2 pmWhat do we mean by Risk?Measures of RiskHow do we Calculate Risk?(a) History(b) Animal analogy(c) Event Tree

  3. Day 2. January 14th 2002Uncertainties and PerceptionTypes of UncertaintiesRole of Perception.Kahneman’s 2002 economics Nobel prizeWe will try to show his effect in classList of interesting attributesMajor differences between Public and Expert perceptions

  4. Day 3 January 15th 2003Formal Risk-benefit comparisons.Net Present ValueDecision TreeValue of InformationProbability of CausationCases:Chernobyl, TMIBhopalALAR as a pesticideResearch on particulatesSabotage and Terrorism

  5. The Biggest Risk to Life is Birth. Birth always leads to death!We talk about premature death.

  6. MEASURES of RiskSimple risk of Death (assuming no other causes)by ageby causeRisk of Injuryby causeby typeby severityPeryearlifetimeunit operationeventtonunit output

  7. 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

  8. LOLE from cigarette smokingIn USA 600 billion cigarettes made (presumably smoked)400,000 people have premature death (lung cancer, other cancers, heart)1,500,000 cigarettes per deathEach death takes about 17 years (8,935,200 minutes) off life or 6 minutes per cigaretteABOUT THE TIME IT TAKES TO SMOKE ONE(easy to remember)

  9. 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.

  10. 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

  11. 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

  12. 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

  13. Risk is different for different measures of risk.Different decision makers will use different measures depending on their constituency

  14. Annual Occupation Fatality Rates (US)

  15. 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

  16. 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)

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

  18. 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)

  19. 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)

  20. 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

  21. Note that the incremental Risk can actually be greater than the simple linearity assumption of a non-linear biological dose-response is assumed

  22. ANALOGY of animals and humansStart with Acute toxic effectsdata from paper of Rhomberg and Wolf

  23. 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.

  24. Transparency from Crouch

  25. Transparency of Allen et al.

  26. 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!

  27. Risks of New technologiesWe now want more safetyNew technologies can kill more people at once.We do not want to have ANY history of accidents.

More Related