Difference between revisions of "Decision analysis and risk management"

From Testiwiki
Jump to: navigation, search
(→‎Content)
(→‎Content: Monte Carlo content)
Line 105: Line 105:
 
| Marko
 
| Marko
 
| '''Monte Carlo modeling'''
 
| '''Monte Carlo modeling'''
 +
* Why Monte Carlo?
 +
* Background of the method
 +
* Monte Carlo, simulation and Monte Carlo simulation
 +
* Practical implementation of MC
 +
** Programs
 +
** Defining the probability functions
 +
** Reading the results
 +
* Monte Carlo vs. Bayes and Bootstrapping
 
|
 
|
 
|----
 
|----
 
| 17.3. PM
 
| 17.3. PM
 
| Marko
 
| Marko
−
| '''Calculation exercise'''. Connections to use of knowledge.
+
| '''Calculation exercise'''.  
 +
* Case 1: Area of the table:
 +
** Defining the model
 +
** Defining the probability functions
 +
** Reading the results
 +
* Case 2: Mortality due to PM exposure?
 +
** Ready model?
 +
* Connections to use of knowledge?
 
|
 
|
 
|----
 
|----

Revision as of 11:15, 9 February 2011



Decision analysis and risk management is a university course [1] for Master's Degree Programme in General Toxicology and Environmental Health Risk Assessment ToxEn.

Scope

What is such a good course content about decision analysis and risk management that

Result

Name
Decision analysis and risk management          
ECTS-credits
6
Abbreviation
DARM     

Content

Schedule and contents of the course.
Each row is a three-hour block of lectures, exercises, discussions, or organised group work, in total 69 hours of teaching. In addition, self-organised group work and individual learning is expected to take ca. 100 hours.
Changes are likely especially in the content, but the dates presented here are more or less fixed.
Date Lecturer Theory lectures and exercises Case study discussions and exercises
28.2. AM (10-13) Jouni, Mikko, Marko Practical introduction to course.
  • Objectives, aims, expectations.
  • Content and teaching/study methods.
  • Example from risk assessment & management study?
 Introduction to the case study and exercises
  • swine flu vaccination campaign in Finland 2009-2011: effects and side effects?
  • group work: decision analysis study plan
  • individual work: reflections on risk management options and actions
3.3. AM Jouni, Mikko, Marko Introduction to risk management. 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.
  • 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.
  • Boundaries of RA and RM
3.3. PM Jouni, Mikko, Marko Beginning of the swine flu story: How the swine flu problem emerged (spring 2009) and spread in the world.
4.3. AM Jouni, Mikko, Marko Introduction to using Opasnet
  • reading and browsing
  • modes of contribution
  • user accounts / logging in
  • basic editing
  • commenting and discussing content
4.3. PM Jouni, Mikko, Marko Swine flu story (summer 2009): Preparedness in Finland and internationally. Vaccination campaigns, counter-campaigns.
  • Should we launch a vaccination campaign?
  • Should I take vaccination? Should I not take vaccination?
8.3. AM Jouni Decision analysis: introduction
  • Purpose of assessment: Why it is done
  • Concepts: decisions, objectives, optimization, uncertainty, decision trees

Subjective probability

  • Practical exercise
  • Bayesian rule and Bayesian networks
  • Denis Lindley: Philosophy of statistics
  • Importance of exhaustiveness (coverage)
 Exercise part one begins: make a decision analysis study plan to find out good policies in this case. Which models to use, what to assess?
9.3. AM or PM Jouni Decision analysis (continued). Swine flu case as a decision problem: what are the relevant decisions, outcomes and questions in the case?
10.3. AM or PM Jouni Bayesian updating 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. AM Jouni Calculation exercise of Bayes
16.3. AM Marko Monte Carlo modeling
  • Why Monte Carlo?
  • Background of the method
  • Monte Carlo, simulation and Monte Carlo simulation
  • Practical implementation of MC
    • Programs
    • Defining the probability functions
    • Reading the results
  • Monte Carlo vs. Bayes and Bootstrapping
17.3. PM Marko Calculation exercise.
  • Case 1: Area of the table:
    • Defining the model
    • Defining the probability functions
    • Reading the results
  • Case 2: Mortality due to PM exposure?
    • Ready model?
  • Connections to use of knowledge?
18.3. PM Jouni Overall view of different models: 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 of and discussions about DA study plan drafts.
21.3. AM Jouni, Marko Decision making under uncertainty
  • Assessment performance? Quality of evidence? Impacts of uncertainty in decision-making. Hindsight.
  • Acceptability
  • Value of information
  • Analysis of model inputs, outputs, and structure
 Swine flu story: Use of adjuvants. How similar is the same? Can/Should be aim at zero risk? Benefit-risk comparisons.
22.3. AM or PM Jouni, Marko Decision-making under uncertainty (continued). Value of information, Value of information analysis.
25.3. AM or PM Marko VOI calculation exercise.
29.3. AM or PM Jouni, Mikko Full drafts of DA study plans. Presentations 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. AM or PM Mikko, Jouni 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.

Exercise part two begins: Risk management actions and options.

31.3. AM or PM Jouni, Mikko Trialogue, collective learning Swine flu story: Secret connections to drug industry? Narcolepsy.
1.4. AM or PM Jouni, Mikko Inference rules. Scientific method as open discussion. Falsification.
  • Do we need pre-peer-review?
7.4. PM Mikko

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. AM or PM Mikko Swine flu story (January 2011): Publishing of narcolepsy results and apologies. Searching for the guilty.
11.4. AM Jouni, Mikko Final seminar: Presentations (exercise parts one and two), discussions, and summary of perspectives to the case.
12.4. AM Jouni, Mikko Wrap-up and course feedback. Final seminar (cont'd).


For the case study description, see D↷.


Learning outcomes
The student will learn about the fundaments of decision analysis; and the connections between societal decision-making and risk assessment. He is able to apply the scientific method and falsification in the context of risk assessment. He also knows how to build an assessment based on the requirements of risk management.     
Learning material
Online course readings in Opasnet: http://en.opasnet.org
Degree Programme(s)
ToxEn, Environment health risk assessment     

Implementation

Time
Spring 2011     

Teaching / Learning Methods

  • Lectures 36 h
  • Tutorial 0 h
  • One-to-One Teaching 0 h
  • Group Work 30 h
  • Independent Study 96 h
  • Web-Based Learning 30 %
Additional Information on Teaching / Learning Methods
Self-organised group work requires on-line computers.
Teaching Languages
English
Additional Information on Languages
Offered for Students in Other Universities (JOO-opintoja)
YES

ASSESSMENT

Assessment is Based on
  • Participation in lectures and discussions.
  • Case study decision analysis plan in groups.
  • Case study risk management plan individually.
Additional Information
The case studies will be evaluated based on contributions in Opasnet.
Assessment
0 (Fail) – 5 (Excellent)
Additional Information

     

Prerequisites

     

Contacts

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

Further information

Keywords
Risk assessment, decision analysis, Bayesian theory, open assessment, risk management, societal decision making.     
Further Information

Rationale

Background information from other available Risk assessment study programs are provided here: Decision analysis and risk management - background information

Other relevant courses than may have supporting, similar, or overlapping content.

See also discussions about the course content. D↷

See also


Courses and course material on different topics related to risk assessment, decision analysis, and risk management.

Statistics

Exposure

Toxicology

Epidemiology and public health

Risk characterisation

Risk management

Risk and impact assessment

Decision analysis and economy

Open assessment

Miscellaneous

Related further education courses (in Finnish, organised in Kuopio)

Täydennyskoulutuskursseja DARM-kurssin aiheista järjestetään osana ERACedu-riskinarviointikoulutusta. Koulutus järjestetään yksipäiväisinä koulutuksina Kuopiossa. Koulutuksessa voi osallistua yhteen tai useampaan päivään; muiden osien käyminen ei ole välttämätöntä, mutta samassa kuussa järjestettävät koulutukset ovat aihepiiriltään lähellä toisiaan.

  1. "Mini-DARM" (5.5.2011)
    • Sikainfluenssatapauksen pohjalta toteutettu johdanto päätösanalyysiin ja riskinhallinnan perusteisiin.
  2. Päätöksenteko epävarmuuden oloissa (19.5.2011)
    • Päätösanalyysi ja -mallitus
  3. Keskustelu ja kansalaiskuuleminen päätöksenteossa: menetelmiä ja työkaluja (8.9.2011)
    • Kuinka järjestetään tehokkaasti kansalaiskuulemisia ja avointa osallistumista päätöksentekoon tai vaikutusarviointeihin?
  4. Yhteisöllinen oppiminen (29.9.2011)
    • Osallistava arviointi ja mallitus.

References


Related files

<mfanonymousfilelist></mfanonymousfilelist>

Retrieved from "http://www.opasnet.org/testiwiki/index.php?title=Decision_analysis_and_risk_management&oldid=18307"