IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v4y2016i1p14-d65367.html
   My bibliography  Save this article

Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya

Author

Listed:
  • Gabriel Otieno

    (Department of Statistics and Computer Science, Moi University, P.O. Box 3900-30100, Eldoret, Kenya)

  • Joseph K. Koske

    (Department of Statistics and Computer Science, Moi University, P.O. Box 3900-30100, Eldoret, Kenya)

  • John M. Mutiso

    (Department of Statistics and Computer Science, Moi University, P.O. Box 3900-30100, Eldoret, Kenya)

Abstract

Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation) of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp) for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER) was done after ranking the strategies in order of the increasing effectiveness (total infections averted). The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control which produces health improvements in the most cost effective way for different epidemiological zones. This offers the good value for money for the public health programs and can guide in the allocation of malaria control resources for the post-2015 malaria eradication strategies and the achievement of the Sustainable Development Goals.

Suggested Citation

  • Gabriel Otieno & Joseph K. Koske & John M. Mutiso, 2016. "Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya," Mathematics, MDPI, vol. 4(1), pages 1-21, March.
  • Handle: RePEc:gam:jmathe:v:4:y:2016:i:1:p:14-:d:65367
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/4/1/14/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/4/1/14/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Erin M Stuckey & Jennifer Stevenson & Katya Galactionova & Amrish Y Baidjoe & Teun Bousema & Wycliffe Odongo & Simon Kariuki & Chris Drakeley & Thomas A Smith & Jonathan Cox & Nakul Chitnis, 2014. "Modeling the Cost Effectiveness of Malaria Control Interventions in the Highlands of Western Kenya," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-11, October.
    2. Peter M. Mwamtobe & Shirley Abelman & J. Michel Tchuenche & Ansley Kasambara, 2014. "Optimal (Control of) Intervention Strategies for Malaria Epidemic in Karonga District, Malawi," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-20, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Manuela Runge & Robert W Snow & Fabrizio Molteni & Sumaiyya Thawer & Ally Mohamed & Renata Mandike & Emanuele Giorgi & Peter M Macharia & Thomas A Smith & Christian Lengeler & Emilie Pothin, 2020. "Simulating the council-specific impact of anti-malaria interventions: A tool to support malaria strategic planning in Tanzania," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-25, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:4:y:2016:i:1:p:14-:d:65367. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.