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Application of the Malaria Management Model to the Analysis of Costs and Benefits of DDT versus Non-DDT Malaria Control

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  • Matteo Pedercini
  • Santiago Movilla Blanco
  • Birgit Kopainsky

Abstract

Introduction: DDT is considered to be the most cost-effective insecticide for combating malaria. However, it is also the most environmentally persistent and can pose risks to human health when sprayed indoors. Therefore, the use of DDT for vector control remains controversial. Methods: In this paper we develop a computer-based simulation model to assess some of the costs and benefits of the continued use of DDT for Indoor Residual Spraying (IRS) versus its rapid phase out. We apply the prototype model to the aggregated sub Saharan African region. For putting the question about the continued use of DDT for IRS versus its rapid phase out into perspective we calculate the same costs and benefits for alternative combinations of integrated vector management interventions. Results: Our simulation results confirm that the current mix of integrated vector management interventions with DDT as the main insecticide is cheaper than the same mix with alternative insecticides when only direct costs are considered. However, combinations with a stronger focus on insecticide-treated bed nets and environmental management show higher levels of cost-effectiveness than interventions with a focus on IRS. Thus, this focus would also allow phasing out DDT in a cost-effective manner. Although a rapid phase out of DDT for IRS is the most expensive of the tested intervention combinations it can have important economic benefits in addition to health and environmental impacts that are difficult to assess in monetary terms. Those economic benefits captured by the model include the avoided risk of losses in agricultural exports. Conclusions: The prototype simulation model illustrates how a computer-based scenario analysis tool can inform debates on malaria control policies in general and on the continued use of DDT for IRS versus its rapid phase out in specific. Simulation models create systematic mechanisms for analyzing alternative interventions and making informed trade offs.

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  • Matteo Pedercini & Santiago Movilla Blanco & Birgit Kopainsky, 2011. "Application of the Malaria Management Model to the Analysis of Costs and Benefits of DDT versus Non-DDT Malaria Control," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-12, November.
    • Handle: RePEc:plo:pone00:0027771
    DOI: 10.1371/journal.pone.0027771
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    Cited by:

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    2. Oleg V. Pavlov & Jason M. Sardell, 2023. "Economic Origins of the Sicilian Mafia: A Simulation Feedback Model," Papers 2304.07975, arXiv.org.
    3. Randall A. Kramer & Leonard E. G. Mboera & Kesheni Senkoro & Adriane Lesser & Elizabeth H. Shayo & Christopher J. Paul & Marie Lynn Miranda, 2014. "A Randomized Longitudinal Factorial Design to Assess Malaria Vector Control and Disease Management Interventions in Rural Tanzania," IJERPH, MDPI, vol. 11(5), pages 1-16, May.
    4. Oleg V Pavlov & Evangelos Katsamakas, 2020. "Will colleges survive the storm of declining enrollments? A computational model," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-29, August.

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