A model of traffic impacts: Points of Dispensing as a response to a biological outbreak
Date
2016
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Publisher
University of Delaware
Abstract
A Point of Dispensing (POD) is one method to distribute medical countermeasures to a population during a biological outbreak. The POD Traffic Impact Model (POD TIM) developed in this research examines the traffic impacts of POD operations on a transportation network. The methodology utilizes a modified and enhanced travel demand forecast model based on DelDOT’s Statewide Evacuation Model in Citilabs Cube to include the choice of POD location choice based on proximity. Five patient arrival scenarios are tested using six relevant measures of effectiveness: V/C ratio, average and maximum patient queue length, average and maximum waiting times (delay), and worst time to arrive. A case study is developed based on Wilmington, Delaware under the assumptions of an aerosolized anthrax release, and five POD locations. The case study operates under several assumptions: all traffic is vehicular; 90% compliance rate; and a POD processing rate of 1000 people per hour. Results indicated that the POD choice algorithm created an uneven distribution of population between the five POD locations, with 40% at one POD and 1% at another POD. The disparity in population distribution meant that the POD TIM is insensitive to patient arrival pattern. At their busiest, PODs had maximum queues of over ten thousand people. The oversight of a parking constraint sub-model led to all patients parking their vehicles and queueing outside of PODs. In reality, parking would represent a serious concern during POD operations. In general, the PODs did not have significant traffic impacts on the surrounding networks. Recommendations for future research include updating the POD choice algorithm, implementing a parking constraint sub-model, and readdressing the patient arrival patterns.