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Cost-effectiveness analysis

Cost-effectiveness analysis. November 2002 Aude Lenders, CESSE – ULB. Cost-Effectiveness Analysis . Introduction Results Presentation Benefit indicators Short-term versus long-term Cost variations Effectiveness variations Conclusions. 1. Introduction.

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Cost-effectiveness analysis

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  1. Cost-effectiveness analysis November 2002 Aude Lenders, CESSE – ULB

  2. Cost-Effectiveness Analysis • Introduction • Results • Presentation • Benefit indicators • Short-term versus long-term • Cost variations • Effectiveness variations • Conclusions

  3. 1. Introduction • Cost-effectiveness analysis spreadsheet: • Inputs: • Population exposure per scenario (« Instantaneous benefit ») as an output from EURANO or from the Extrapolation module. • Programme : set of noise reduction measures (=scenario) + implementation schedule (within a 10-years period). • Parameters : lifetime, costs, discount rates

  4. Outputs: • Net Present value of the Benefits = Number of persons who have gained a noise reduction thanks to the measures applied. [Persons*years]  “Effectiveness” • People exposed to noise above 60dB(A) • Annoyed people • Weighted people (f factor) • Net Present Value of the Costs in Euros • Efficiency = Present Benefits / Present Costs

  5. Benefit Function • PB = Net Present Value of S Benefits of each measure • S Interactions between measures • S For each year of the modeled period Interpolation of EURANO output: evolution of the benefits when supplementary units of the measure are implemented.

  6. Cost Function • PC = Net Present Value of Investment years 1 to 10 • Maintenance during lifetime of the measure • Removal at the end of the lifetime

  7. 700’000 Best efficiency Persons > 60dB Worst efficiency 14’000’000 Costs without windows insulation 2. Results

  8. b) Two indicators for the benefits : same results Same results for different indicators

  9. Variations in the ranking of the programmes Third indicator : number of people weighted (noise level and noise reduction) Same ranking of the programmes for ≠ weightings Uncertainties : the costs of the measures

  10. c) Two different approaches

  11. d) Costs variation according to the number of freight wagons (-25%)

  12. d) Variation according to the ratio “number of wagons/ km urban areas”

  13. e) Benefits variation:% freight trains & distribution of people

  14. Conclusions • Despite these small variations, all the graphs have generally the same appearance the results seem reliable. • Further study : • Other noise reducing measures • Other scenarios (combination of measures)

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