Modeling the Cost Effectiveness of Malaria Control Interventions in the Highlands of Western Kenya Erin M. Stuckey 1,2 *, Jennifer Stevenson 3,4,5 , Katya Galactionova 1,2 , Amrish Y. Baidjoe 6 , Teun Bousema 3,6 , Wycliffe Odongo 4 , Simon Kariuki 4 , Chris Drakeley 3 , Thomas A. Smith 1,2 , Jonathan Cox 3 , Nakul Chitnis 1,2 1 Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland, 2 University of Basel, Basel, Switzerland, 3 Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom, 4 Centre for Global Health Research, Kenya Medical Research Institute/Centers for Disease Control and Prevention, Kisumu, Kenya, 5 Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America, 6 Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands Abstract Introduction: Tools that allow for in silico optimization of available malaria control strategies can assist the decision-making process for prioritizing interventions. The OpenMalaria stochastic simulation modeling platform can be applied to simulate the impact of interventions singly and in combination as implemented in Rachuonyo South District, western Kenya, to support this goal. Methods: Combinations of malaria interventions were simulated using a previously-published, validated model of malaria epidemiology and control in the study area. An economic model of the costs of case management and malaria control interventions in Kenya was applied to simulation results and cost-effectiveness of each intervention combination compared to the corresponding simulated outputs of a scenario without interventions. Uncertainty was evaluated by varying health system and intervention delivery parameters. Results: The intervention strategy with the greatest simulated health impact employed long lasting insecticide treated net (LLIN) use by 80% of the population, 90% of households covered by indoor residual spraying (IRS) with deployment starting in April, and intermittent screen and treat (IST) of school children using Artemether lumefantrine (AL) with 80% coverage twice per term. However, the current malaria control strategy in the study area including LLIN use of 56% and IRS coverage of 70% was the most cost effective at reducing disability-adjusted life years (DALYs) over a five year period. Conclusions: All the simulated intervention combinations can be considered cost effective in the context of available resources for health in Kenya. Increasing coverage of vector control interventions has a larger simulated impact compared to adding IST to the current implementation strategy, suggesting that transmission in the study area is not at a level to warrant replacing vector control to a school-based screen and treat program. These results have the potential to assist malaria control program managers in the study area in adding new or changing implementation of current interventions. Citation: Stuckey EM, Stevenson J, Galactionova K, Baidjoe AY, Bousema T, et al. (2014) Modeling the Cost Effectiveness of Malaria Control Interventions in the Highlands of Western Kenya. PLoS ONE 9(10): e107700. doi:10.1371/journal.pone.0107700 Editor: Georges Snounou, Universite ´ Pierre et Marie Curie, France Received February 16, 2014; Accepted August 22, 2014; Published October 7, 2014 Copyright: ß 2014 Stuckey et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the Bill and Melinda Gates Foundation, under the Malaria Transmission Consortium [grants number 45114 and 1032350] and Grand Challenge Grant [grant number OPP1024438]. NC also acknowledges support from the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science & Technology Directorate, Department of Homeland Security and Fogarty International Center, National Institutes of Health, USA. CD is supported by the Wellcome Trust [grant number 091924]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: erin.stuckey@unibas.ch Introduction Important progress has been made in the past decade in reducing malaria morbidity and mortality in Kenya, but it is not obvious which additional tools and strategies should be the next priority to include in the package of malaria control interventions in a given area to keep transmission levels low, especially given the threat of resistance of the parasite and vectors to antimalarial drugs and insecticides [1,2]. Application of mathematical models for use in simulations of malaria epidemiology and control can help estimate the impact of interventions singly and in combina- tion to support this goal. OpenMalaria, a stochastic simulation modeling platform [3], has previously been applied to Rachuonyo South District, Nyanza Province, Kenya in order to describe the epidemiology of malaria and control area and identify uncertainty in key parameters pertaining to the study area [4]. Results indicate that the OpenMalaria model, as parameterized for Rachuonyo South District, can be extended to simulate the epidemiologic and economic impact of combinations of a range of existing and potential future malaria control interventions, singly and in combination, implemented in the study area [4]. This study addresses the cost effectiveness of feasible malaria control PLOS ONE | www.plosone.org 1 October 2014 | Volume 9 | Issue 10 | e107700