Proper planning and execution of mass vaccination at the onset of a pandemic outbreak is important for local health departments. Mass vaccination clinics are required to be setup and run for naturally occurring pandemic outbreaks or even in response to terrorist attacks, e.g., anthrax attack. Walk-in clinics have often been used to administer vaccines. When a large percentage of a population must be vaccinated to mitigate the ill-effects of an attack or pandemic, drive-through clinics appear to be more effective because a much higher throughput can be achieved when compared to walk-in clinics. There are other benefits as well. For example, the spread of the disease can be minimized because infected patients are not exposed to uninfected patients. This research extends the simulation modeling work that was done for a mass vaccination drive-through clinic in the city of Louisville in November 2009. This clinic is the largest clinic set up in Louisville with more than 19,000 patients served, over two-thirds via ten drive-through lanes. The intent of the model in this paper is to illustrate a general tool that can be customized for a community of any size. The simulation-optimization tool will allow decision makers to investigate several interacting control variables in a simultaneous fashion; any of several criterion models in which various performance measures are either optimized or constrained, can be investigated. The model helps the decision maker determine the required number of Points of Dispense (POD) lanes, number and length of the lanes for consent hand outs and fill in, staff needed at the consent handout stations and PODs, and average user waiting time in the system.
Simulation Modelling Practice and Theory
Required Publisher’s Statement
NOTICE: this is the author’s version of a work that was accepted for publication in Simulation Modelling Practice and Theory. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Simulation Modelling Practice and Theory 37, [September 2013] https://doi.org/10.1016/j.simpat.2013.06.004
Scholarly Commons Citation
Gupta, A., Evans, G. W., & Heragu, S. S. (2013). Simulation and Optimization Modeling for Drive-Through Mass Vaccination – A Generalized Approach. Simulation Modelling Practice and Theory, 37(September 2013). Retrieved from http://commons.erau.edu/ww-management-science/1