flu pandemic decision treecourses.nus.edu.sg/.../bizchucl/project_mexicanflu_2009.pdf•key...
TRANSCRIPT
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Feedback
This is the most relevant & timely problem studied.The “chance” scenarios in the decision tree are very rich and realistic. I have no issues with the logic in the tree. The key numericals are the various probabilities and the monetary aspects. I’ve played “devil’s advocate” and made changes to C1 (pop size), C11 (risk of mild pandemic) and C56-C59 (monetary aspects). Decision remains to vaccinate all but Tornado reveals that more parameters ie monetary aspects and risk are equally important. In short, like it or not, money underlies much of the decision making. This is indeed a world-class MBA Project: Well Done!
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Mexican Flu Pandemic Decision Tree
Hendra Tandi
Kaden Lao Yizhi
Lee Hwee Hoon
Michael Yee Jenn Jet
Nelson Low Kah Hock
Nguyen Thanh Hai
Team 6
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The model predicts that
• We order the H1N1 influenza vaccine before the 2nd Wave occurs and recommend that the entire population gets vaccinated.
• The expected cost savings is S$64.4 billion @ S$30,000 per Quality adjusted life years saved.
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INTRODUCTIONWhy is this a topic of interest?
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The Spanish Flu took the lives of an estimated 20 to 40 million in 1918.
Since then a major flu pandemics have occurred in predictable cycles. eg. Asian Flu (1968), Hong Kong Flu (1957)
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Exploration in the Alaskan permafrost found that the Spanish Flu was attributed to the H1N1 hybrid bird, swine and human flu.
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Current Situation
• All recorded past flu pandemics followed a predictable behaviour.
• The first wave is typically mild and lull the public into complacency.
• The 2nd wave strikes with vicious ferocity with variable outcomes and probabilities.
• 2009 saw the 1st wave of an expectedly mild Mexican Flu Pandemic. The 2nd wave is poised to strike next month during the northern winter season.
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Introduction
Current Situation• Technological Advancement:
1. Knowledge of flu pandemic behaviour2. Tamiflu and other antiviral agents3. Accurate and rapid H1N1 diagnostic kits4. Flu vaccination
• Singapore has 1.5M boxes of Tamiflu in stock and has ordered 1M doses of Flu vaccine, costing an estimated S$100M in raw material cost alone for a population of 5M.
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Decisions
1. Should the health authorities order the flu vaccine?
2. Which vaccine should they order?3. What vaccination regimen should they
recommend to the public?4. Should they test all suspect cases with the H1N1
diagnostic kit?5. Should they treat all cases of flu with Tamiflu?6. What is the expected incremental cost of each
decision?
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Uncertainties
1. Severe or Mild 2nd wave2. General risk or High risk patient3. Follow or Reject recommendations4. Side effects or No side effects of vaccination 5. Disease or No disease6. False positive or True positive7. Resistance or No resistance to Tamiflu8. Side effects or No side effects of Tamiflu9. Death, Complications or No significant morbidity
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1. Should the health authorities order the flu vaccine?
2. Which vaccine should they order?3. What vaccination regimen should they
recommend to the public?4. Should they test all suspect cases with the H1N1
diagnostic kit?5. Should they treat all cases of flu with Tamiflu?6. What is the expected incremental cost of each
decision?
Selected Decision Nodes
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1. Severe or Mild 2nd wave2. General risk or High risk patient3. Follow or Reject recommendations4. Side effects or No side effects of vaccination 5. Disease or No disease6. False positive or True positive7. Resistance or No resistance to Tamiflu8. Side effects or No side effects of Tamiflu9. Death, Complications or No significant morbidity
Chance Nodes to Consider
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DECISION TREEHow is the decision derived?
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A Glimpse of the Decision Tree
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Decision ChanceExpected payoff ( or Cost)
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Decisions
Ordering vaccine • Order vaccines
• Do not order vaccines
What to recommend• Vaccinate everybody?
• Vaccinate only high risk group?
• No specific recommendations (Singapore’s position)?
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Chance
Pandemic• Severe 2nd wave • Mild 2nd wave
Patient status• General risk patient • High risk patient
Compliance• Follow
recommendations • Reject
recommendations
Occurrence of disease• Yes• No
Disease Outcomes• Death, • Complications • No significant
morbiditySide effects of vaccination
• Yes• No
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Most cost effective decision?
• Most cost effective decision is to order the vaccine before the 2nd Wave occurs and recommend that the entire population gets vaccinated.
• The expected cost of this decision is S$42.0 billion.
• The expected cost of not ordering the vaccine is S$106.6 billion.
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SENSITIVITY ANALYSISHow valid is the decision (by the model)?
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0%
10%
20%
30%
40%
50%
60%
70%
80%
7400
0000
3540
0000
0
3.75
035E
+12
6.00
035E
+12
Prob
abili
ty
Probabilities for Decision Tree 'FLU PANDEMIC'Choice Comparison for Node 'Vaccine orders'
Vaccine A
Don't order
Dominant Strategy
Higher chance of getting lowest cost when ordering vaccine.
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Variables Analysis• Total 29 variables
• Used 2 tornado analysis to define the most significant variables:
0
5E+0
9
1E+1
0
1.5E
+10
2E+1
0
2.5E
+10
3E+1
0
3.5E
+10
4E+1
0
4.5E
+10
Risk of pandemic_mild (C11)
cost_of_life_year (C61)
% uptake of general population if vaccination reco (C6)
percentage_resistance_severe_pandemic (C43)
Complicated_convalescence_QALY (C57)
Expected Value
Tornado Graph of Decision Tree 'FLU PANDEMIC'Expected Value of Entire Model
1. Probability of mild pandemic occurring
2. Cost of life year3. Percentage of general
population will go for vaccination if recommended.
4. Percentage of population who have resistance to Tamiflu in case of severe pandemic.
5. Quality adjusted life year of complicated convalescence patients
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Probability of Mild Pandemic Occurring
0
2E+10
4E+10
6E+10
8E+10
1E+11
1.2E+11
1.4E+11
1.6E+11
1.8E+11
40.0
000%
50.0
000%
60.0
000%
70.0
000%
80.0
000%
90.0
000%
100.
0000
%
110.
0000
%
120.
0000
%
130.
0000
%
140.
0000
%
Expe
cted
Val
ue
Risk of pandemic_mild (C11)
Strategy Region of Decision Tree 'FLU PANDEMIC'Expected Value of Node 'Vaccine orders' (C390)With Variation of Risk of pandemic_mild (C11)
Vaccine A
Don't order
If mild pandemic is definitely occurring, then the number ofinfected people will be much higher even with vaccinationprogram.
More cost effective to treat the actual patients only ratherthan to recommend vaccination AND to treat.
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Despite its limitation, model is useful and applicable
Model Applicability
•A usable solution for a national-scale problem
•Key determinants:•Likelihood of a mild
pandemic•Estimated cost of life (year)•% of general population
who will go for voluntary vaccination
•% of population who are resistant to Tamiflu in the event of a severe pandemic.
•Quality adjusted life year of complicated convalescence patients
Model Extension
•Other populations with different demographic profile
•Vaccine purchase for other potential epidemic threats
•Expenses analysis for drug/vaccine production
•For insurance companies to design offering
Model Limitation
•Does not consider all factors due to software limitations
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Q&A
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A side note - How to compute
cost?
Total Cost = Cost of End Result QALY + Cost of Side Effects QALY + Cost of Tamiflu
• A measure of disease burden• Used to assess the monetary value
of a medical intervention• Derived based on the number of
years added in patient’s life with medical intervention.