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Trying to build off of last
summer’s work!
Last Summer
• Allocative optimization for South Africa model.
• 3 parameter problem – ART, PrEP, VMMC
• Solved through random sampling of the parameter space, manual
estimation of trends + a little bit of statistical analysis
• Goals:
• Find a more efficient/organized solution
• Generalize approach to higher dimensions/other models.
Generated Hypercube in Parameter Space
• 11 x 11 x 10 points sampled - DALYs
and Cost calculated for each point.
• Built surrogate model for Objective
(DALYs) and Constraint (Cost)
• Model represents DALY, Cost as a
product of univariate functions in ART,
PrEP, and VMMC. (Separation of
variables)
• Used surrogate models to solve
constrained optimization problem.
Findings
• ART has the most influence on DALYs.
• ART, PrEP have around equal influence on cost.
• Main strategy: invest in ART, remainder goes to PrEP
• Suspicious observation:
• VMMC parameter has almost no effect – did I make a mistake? (I probably
made a mistake)
Next Week
• Future work – I found additional parameters in the model:
• 8 for ART
• 1 for PrEP
• 1 for VMMC
• 1 for HCT
• Generating 1000 random points in the 11-dimension hypercube.
• Generate surrogate model using separation of variables.
• Use the same code to solve the constrained optimization.

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slides.pptx

  • 1. Trying to build off of last summer’s work!
  • 2. Last Summer • Allocative optimization for South Africa model. • 3 parameter problem – ART, PrEP, VMMC • Solved through random sampling of the parameter space, manual estimation of trends + a little bit of statistical analysis • Goals: • Find a more efficient/organized solution • Generalize approach to higher dimensions/other models.
  • 3. Generated Hypercube in Parameter Space • 11 x 11 x 10 points sampled - DALYs and Cost calculated for each point. • Built surrogate model for Objective (DALYs) and Constraint (Cost) • Model represents DALY, Cost as a product of univariate functions in ART, PrEP, and VMMC. (Separation of variables) • Used surrogate models to solve constrained optimization problem.
  • 4.
  • 5.
  • 6. Findings • ART has the most influence on DALYs. • ART, PrEP have around equal influence on cost. • Main strategy: invest in ART, remainder goes to PrEP • Suspicious observation: • VMMC parameter has almost no effect – did I make a mistake? (I probably made a mistake)
  • 7. Next Week • Future work – I found additional parameters in the model: • 8 for ART • 1 for PrEP • 1 for VMMC • 1 for HCT • Generating 1000 random points in the 11-dimension hypercube. • Generate surrogate model using separation of variables. • Use the same code to solve the constrained optimization.