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<big>[http://www.ustream.tv/channel/decision-analysis-and-risk-management LIVE FEED FROM LECTURES]</big>
<big>[http://www.ustream.tv/channel/decision-analysis-and-risk-management LIVE FEED FROM LECTURES]</big>



Revision as of 08:32, 21 March 2011

LIVE FEED FROM LECTURES

Decision analysis and risk management (DARM) is a course taught in the | University of Eastern Finland (UEF) for Master's (MSc) Degree Programme in General Toxicology and Environmental Health Risk Assessment ToxEn.

NOTE! On this page, there was a list of related further education courses in Kuopio (in Finnish).

Aims of the course

  • To give a good overview of modern assessment methods by;
    • utilizing modern web-workspaces for learning, while;
    • avoiding overlaps with other courses in the ToxEn MSc program,

In the course:

The student will learn about the fundamentals of decision analysis, the connections between societal decision-making and risk assessment, and the role of risk management in a broader societal context. The student will learn to apply the scientific method and falsification in the context of risk assessment, and know how to build an assessment based on the requirements of risk management.     

Course details

  • Name: Decision analysis and risk management          
  • Abbreviation: DARM
  • ECTS-credits: 6
  • Home page of the course: http://en.opasnet.org/w/Darm
  • Degree Programme: ToxEn, Environment health risk assessment
  • Teaching Language: English, with Finnish accent
  • Offered for Students in Other Universities (JOO-opintoja): Yes

Contacts

  • Organising Departments: Department of environmental science (in collaboration with the National Institute for Health and Welfare, THL)          
  • Course Director: Jukka Juutilainen     
  • Teachers: Jouni Tuomisto, Mikko Pohjola, Marko Tainio     
  • Contact Persons email: mikko.pohjola(at)thl.fi     
  • Registration for the Course: Wossikka     

Teaching / Learning Methods

  • Lectures and discussions 60 h
  • Calculation exercises 9 h
  • Independent assessment study
    • Decision analysis study (group work) 50 h
    • Risk management study (individual work) 40 h
  • Web-Based Learning 30 %

Lectures

See the Content and schedule table for timing, locations, topics and links to materials. One lecture and classroom exercise session is approximately three hours.

Study materials include e.g. PowerPoint files, scanned articles or book chapters, web-sites and web-documents. Due to copy-right reasons, some of the materials are distributed through a password protected HEANDE-page. Passwords to HEANDE will be distributed during the lectures. In the end of the page there are some more links for further information. Even more can be found at: Decision analysis and risk management - background information.

Case study exercise

For the case study description and instructions, see the case study exercise page

Note! Self-organised group work requires on-line computers.

Evaluation

Scale: 0 (Fail) – 5 (Excellent)

Evaluation is based on:

  • Case study exercise (2/3)
  • Completion of calculation exercises (1/3)
  • Active participation during lectures will be taken into account while deciding final grades

For non-ToxEn students it is also possible to accomplish only certain parts of the course: lectures (3 ECTS), case study exercise part 1 (2 ECTS), or case study exercise part 2 (1 ECTS). Partial accomplishments will be graded only on a fail/pass scale.

Content and schedule

Schedule and contents of the course.
  • Each row is a three-hour block of lectures, exercises, discussions, or organised group work.
  • Changes in content are likely, but the dates and locations presented here are more or less fixed.
  • Abbreviations: DA = decision analysis, RM = risk management, RA = risk assessment, RC = risk communication.
Date Time Lecturer Lecture room Topics Material
28.2. 10-13 Jouni, Mikko, Marko S22 Introduction to the course
  • introduction to decision analysis: video , slides
  • introduction to case study exercise and course evaluation: video, slides
  • Introduction to the swine flu story: video, slides
3.3. 9-12 Jouni, Mikko, Marko S31 Introduction to risk management
3.3. 13-16 Jouni, Mikko, Marko S23 Swine flu story: risks and their management: video, slides whiteboard
  • independent exploration
    • Beginning of the pandemic
    • preparedness in Finland and elsewhere
  • mini-presentations and discussion
  • summary
4.3. 9-12 Mikko, Marko MC9 Introduction to using Opasnet
  • Introduction to Opasnet
  • Demonstration of structure, content and functionalities
  • Exercises
    • user accounts
    • DA study plan page
    • RM report page
    • browsing and searching
    • commenting and discussing
4.3. 13-16 Jouni, Marko S24 Introduction to probability theory video Dennis Lindley: Philosophy of statistics

Lindley, a backup file

8.3. 9-12 Jouni S22 Introduction to probability theory. video slides
  • Bayes' rule. Updating probability. Examples: red balls, narcolepsy test.

Decision analysis (continued). slides

9.3. 9-12 Jouni S22 Decision analysis (continued). slides; sorry, no video
  • Concepts: decisions, objectives, optimization, uncertainty, decision trees
  • Influence diagrams, Bayesian belief nets.

Swine flu case as a decision problem: what are the relevant decisions, outcomes and questions in the case?

  • Purpose of assessment: Why it is done
10.3. 9-12 Marko S24 Modeling and Monte Carlo simulation
  • Computer modeling video
    • Why?
  • Approximation
    • When data is not available
  • Monte Carlo simulation
    • When and why to use?
  • Common uncertainty distributions video
    • Normal distribution is not the only option

Swine flu story (autumn - winter 2009): First deaths of swine flu (threat was real). Problems with implementation: long queues in health centers. Clear-cut case falls apart. False alarm? Disease was milder than thought.

11.3. 8-11 Marko MC9 Calculation exercise.
  • Case: Mortality due to PM2.5 in Kuopio
Pope et al. 2002
16.3. 9-12 Jouni, Marko S22
  • Probabilistic models video slides
Gibbs sampling Bayesian network Hierarchical Bayes model
17.3. 9-12 Jouni, Marko MC4 Calculation exercise of calibration and PM risks with Opasnet R Tuomisto et al: PM expert elicitation
18.3. 13-16 Jouni S24 Overall view of different models video slides

Why do we do modelling?

  • Producing result from rationale.
    • Deterministic, heuristic, and probabilistic estimates.
    • Functional, differential, logical, and probabilistic relations.
    • Other relations (neural networks).

First drafts of DA study plans. Brief presentations by students of and discussions about the first DA study plan drafts.

21.3. 11-14 Jouni, Marko, Mikko S24 Decision making under uncertainty

Swine flu story: Use of adjuvants. How similar is the same? Can/Should be aim at zero risk? Benefit-risk comparisons.

Further information from sensitivity analysis (Frey et al. 2004)
22.3. 9-12 Jouni, Mikko, Marko S24 Decision-making under uncertainty (continued). Value of information, Value of information analysis.
  • Assessment performance? Quality of evidence? Impacts of uncertainty in decision-making. Hindsight. (Mikko)
25.3. 9-12 Marko S24, MC9 Calculation exercise.
  • To be decided
29.3. 9-12 Jouni, Mikko S4069 Full drafts of DA study plans. Presentations by students of and discussions about study plans. Apply the model to assess the case based on your own research plan. Defend your plan in plenary.
  • Are plans executable? What outputs are expected? Do they serve the intended needs?
  • What should the model do? How should the results be used?
  • The core of a model can go through technical check: does it work?
  • The assessment should link to the outside world: does it produce useful info, is it convincing to users?
30.3. 9-12 Mikko, Jouni S24 Risk management (theory). What is managed, who is responsible, what is included? Traditional paradigm.
  • Look from decision-maker's point of view: needs, communication, and assessment all included.
  • What is the role of decision analysis and modeling in RM?
  • Openness: RA, RM, RC are not totally separate.
  • Performance: Context about what we actually aim to achieve. How do we know if we succeeded?
  • Developing risk management options.
  • Development of risk assessment questions.
  • Science-policy interface. Why it does not exist.

Opasnet and other web-based decision support systems.

31.3. 9-12 Jouni, Mikko S23 Trialogue, collective learning

Swine flu story: Secret connections to drug industry? Narcolepsy.

1.4. 9-12 Jouni, Mikko MC9 Inference rules. Scientific method as open discussion. Falsification.
  • Do we need pre-peer-review?
7.4. 13-16 Mikko S4069

Discussion: Lectures of concepts

Structuring of discussions in practice and theory

  • Ready-made texts: discussions and organisation
  • Homework: evaluate relevance - validity of arguments. Discuss in groups the next day.
  • Build a structured discussion out of this in groups.
  • Possibly utilise group writing tools?

Swine flu story (autumn 2010): Vaccination campaign halted. THL remains silent about possible risks. Narcolepsy analysis. Impacts of openness. How methods learned should be applied now? Why openness is needed?

8.4. 9-12 Mikko S22 Swine flu story (January 2011): Publishing of narcolepsy results and apologies. Searching for the guilty.
11.4. 9-12 Jouni, Mikko S24 Final seminar: Presentations (exercise parts one and two), discussions, and summary of perspectives to the case.
12.4. 8-11 Jouni, Mikko S24 Final seminar (cont'd).

Wrap-up and course feedback.

Help and guidance

Topic Contact
General arrangements User:Jouni, User:Mikko Pohjola
Case study exercises: content User:Jouni
Case study exercises: technical User:Teemu R
Calculation exercises User:Marko

Help requests or other comments can be posted on the course web-page or the exercise web-page by using the comment boxes on the end of the pages (no user account / log in required) or on the discussion pages.

See also

Links to additional DA materials

Links to additional RM materials

General information sources on AH1N1 influenza (Swine flu)

Links to information on specific topics

(current headings intended as first guidance, can be modified as seen reasonable)

Beginning and expansion of the global H1N1 Pandemic

Preparation, decision and promotion of H1N1 vaccination in Finland

Campaigning against H1N1 vaccination in Finland

The development of H1N1 influenza in Finland

Implementation of the vaccination campaign in Finland

Suspected connections between THL and the producer Pandemrix vaccine (GlaxoSmithKline)

Pandemrix vaccine - composition, testing, alternatives etc.

Emergence of narcolepsy cases in Finland and elsewhere

Suspected connections between Pandemrix vaccinations and narcolepsy

Halting of vaccination campaign

THL narcolepsy study, results, and publication

Searching for the guilty

EMA statement on suspected connection between Pandemrix and narcolepsy

Reoccurence of swine flu in Finland and elsewhere



Background information about other Decision analysis and risk management study programs in Europe and in USA is provided here: Decision analysis and risk management - background information

NOTE! On this page, there was a list of related further education courses in Kuopio (in Finnish).

Keywords

Risk assessment. Decision analysis. Bayesian theory. Open assessment. Risk management. Societal decision making.     

References

Related files

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