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Uncertainty and Sensitivity Analyses of a Dynamic Economic Evaluation Model for Vaccination Programs

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Listed:
  • Radboud J. Duintjer Tebbens

    (Delft University of Technology, Department of Mathematics, Delft, the Netherlands, rduintje@hsph.harvard.edu, Kids Risk Project, Harvard School of Public Health, Boston, Massachusetts)

  • Kimberly M. Thompson

    (Kids Risk Project, Harvard School of Public Health, Boston, Massachusetts, Massachusetts Institute of Technology, Sloan School of Management, Cambridge, Massachusetts)

  • M. G. Myriam Hunink

    (Department of Epidemiology and Biostatistics and Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands)

  • Thomas A. Mazzuchi

    (Department of Engineering Management and Systems Engineering, The George Washington University, Washington, DC, Delft University of Technology, Department of Mathematics, Delft, the Netherlands)

  • Daniel Lewandowski

    (Delft University of Technology, Department of Mathematics, Delft, the Netherlands)

  • Dorota Kurowicka

    (Delft University of Technology, Department of Mathematics, Delft, the Netherlands)

  • Roger M. Cooke

    (Delft University of Technology, Department of Mathematics, Delft, the Netherlands)

Abstract

With public health policy increasingly relying on mathematical models to provide insights about the impacts of potential policy options, the demand for uncertainty and sensitivity analyses that explore the implications of different assumptions in a model continues to expand. Although analysts continue to develop methods to meet the demand, most modelers rely on a single method in the context of their assessments and presentations of results, and few analysts provide results that facilitate comparisons between uncertainty and sensitivity analysis methods. Methods vary in their degree of analytical difficulty and in the nature of the information that they provide, and analysts should communicate results with a note that not all methods yield the same insights. The authors explore several sensitivity analysis methods to test whether the choice of method affects the insights and importance rankings of inputs from the analysis. They use a dynamic cost-effectiveness model of a hypothetical infectious disease as the basis to perform 1-way and multi-way sensitivity analyses, design of experiments, and Morris' method. They also compute partial derivatives as well as a number of probabilistic sensitivity measures, including correlations, regression coefficients, and the correlation ratio, to demonstrate the existing methods and to compare them. The authors find that the magnitudes and rankings of sensitivity measures depend on the selected method(s) and make recommendations regarding the choice of method depending on the complexity of the model, number of uncertain inputs, and desired types of insights from the sensitivity analysis.

Suggested Citation

  • Radboud J. Duintjer Tebbens & Kimberly M. Thompson & M. G. Myriam Hunink & Thomas A. Mazzuchi & Daniel Lewandowski & Dorota Kurowicka & Roger M. Cooke, 2008. "Uncertainty and Sensitivity Analyses of a Dynamic Economic Evaluation Model for Vaccination Programs," Medical Decision Making, , vol. 28(2), pages 182-200, March.
  • Handle: RePEc:sae:medema:v:28:y:2008:i:2:p:182-200
    DOI: 10.1177/0272989X07311752
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    References listed on IDEAS

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    1. Peter Doubilet & Colin B. Begg & Milton C. Weinstein & Peter Braun & Barbara J. McNeil, 1985. "Probabilistic Sensitivity Analysis Using Monte Carlo Simulation," Medical Decision Making, , vol. 5(2), pages 157-177, June.
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    Citations

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    Cited by:

    1. Salacinska, K. & El Serafy, G.Y. & Los, F.J. & Blauw, A., 2010. "Sensitivity analysis of the two dimensional application of the Generic Ecological Model (GEM) to algal bloom prediction in the North Sea," Ecological Modelling, Elsevier, vol. 221(2), pages 178-190.
    2. Radboud J. Duintjer Tebbens & Mark A. Pallansch & Dominika A. Kalkowska & Steven G. F. Wassilak & Stephen L. Cochi & Kimberly M. Thompson, 2013. "Characterizing Poliovirus Transmission and Evolution: Insights from Modeling Experiences with Wild and Vaccine‐Related Polioviruses," Risk Analysis, John Wiley & Sons, vol. 33(4), pages 703-749, April.
    3. Radboud J. Duintjer Tebbens & Mark A. Pallansch & Konstantin M. Chumakov & Neal A. Halsey & Tapani Hovi & Philip D. Minor & John F. Modlin & Peter A. Patriarca & Roland W. Sutter & Peter F. Wright & S, 2013. "Review and Assessment of Poliovirus Immunity and Transmission: Synthesis of Knowledge Gaps and Identification of Research Needs," Risk Analysis, John Wiley & Sons, vol. 33(4), pages 606-646, April.
    4. Radboud J. Duintjer Tebbens & Mark A. Pallansch & Olen M. Kew & Roland W. Sutter & R. Bruce Aylward & Margaret Watkins & Howard Gary & James Alexander & Hamid Jafari & Stephen L. Cochi & Kimberly M. T, 2008. "Uncertainty and Sensitivity Analyses of a Decision Analytic Model for Posteradication Polio Risk Management," Risk Analysis, John Wiley & Sons, vol. 28(4), pages 855-876, August.
    5. Radboud J. Duintjer Tebbens & Mark A. Pallansch & Konstantin M. Chumakov & Neal A. Halsey & Tapani Hovi & Philip D. Minor & John F. Modlin & Peter A. Patriarca & Roland W. Sutter & Peter F. Wright & S, 2013. "Expert Review on Poliovirus Immunity and Transmission," Risk Analysis, John Wiley & Sons, vol. 33(4), pages 544-605, April.
    6. Christian Schaetti & Mitchell G Weiss & Said M Ali & Claire-Lise Chaignat & Ahmed M Khatib & Rita Reyburn & Radboud J Duintjer Tebbens & Raymond Hutubessy, 2012. "Costs of Illness Due to Cholera, Costs of Immunization and Cost-Effectiveness of an Oral Cholera Mass Vaccination Campaign in Zanzibar," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 6(10), pages 1-10, October.
    7. Emanuele Borgonovo & William Castaings & Stefano Tarantola, 2011. "Moment Independent Importance Measures: New Results and Analytical Test Cases," Risk Analysis, John Wiley & Sons, vol. 31(3), pages 404-428, March.
    8. Kimberly M. Thompson, 2013. "Modeling Poliovirus Risks and the Legacy of Polio Eradication," Risk Analysis, John Wiley & Sons, vol. 33(4), pages 505-515, April.
    9. Anna K. Lugnér & Sido D. Mylius & Jacco Wallinga, 2010. "Dynamic versus static models in cost‐effectiveness analyses of anti‐viral drug therapy to mitigate an influenza pandemic," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 518-531, May.
    10. Joke Bilcke & Philippe Beutels, 2009. "Reviewing the Cost Effectiveness of Rotavirus Vaccination," PharmacoEconomics, Springer, vol. 27(4), pages 281-297, April.

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