Abstract
Decisions regarding the best use of scarce health resources become increasingly complex in developing countries due to high disease incidence, poor healthcare system infrastructure, and other societal factors. We develop a resource allocation model for the design of an Indoor Residual Spraying (IRS) program for malaria prevention in developing countries. Due to the seasonal nature of malaria risk factors, the model addresses dynamic resource allocation based on the risk characteristics. Using the model as a framework, a decision support tool for IRS operations is constructed. With a small numerical example we demonstrate the value of the tool for evaluating complexities and tradeoffs in the allocation of limited resources for an IRS program and the impact of heuristic decision making.
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Acknowledgements
We would like to acknowledge the work of Georgia Tech students Michele Cataldi, Christina Cho, Cesar Gutierrez, Jeff Hull, Phillip Kim, and Andrew Park, who developed the initial model and study from which the current decision support tool and model were created. Additionally, we would like to acknowledge Hannah Smalley and Mallory Soldner for their work in the development of the decision support tool and a related case study. This research is supported in part by Andrea L. Laliberte, the Harold R. and Mary Anne Nash Endowment, the Claudia L. and J. Paul Raines Endowment, and Richard and Charlene Zalesky.
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Griffin, J., Keskinocak, P., Swann, J. (2013). Allocating Scarce Healthcare Resources in Developing Countries: A Case for Malaria Prevention. In: Denton, B. (eds) Handbook of Healthcare Operations Management. International Series in Operations Research & Management Science, vol 184. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5885-2_20
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