The impact of demand uncertainty on stockpile and distribution decisions during influenza pandemic

Abstract

The main goal of public health emergency preparedness efforts is to mitigate the impact of events on the health of the population. However, decision-makers must also remain conscientious of the costs associated with these efforts. Planning is further complicated by uncertainty about the location and volume of demand that will need to be met in an emergency, the speed with which demand must be met, and the potential scarcity of needed items once an emergency occurs. To address these challenges, public health emergency planners often keep inventory stockpiles that are distributed when an event happens. Managing these stockpiles is a difficult task, and inefficient stockpile location and equipment distribution strategies can be costly both in terms of cost and public health impact. This research is motivated by challenges faced by state public health departments in creating stockpile location and equipment distribution strategies. The primary emphasis is on facemasks and respirators used by health workers during an influenza pandemic, but the approach is generalizable to other scenarios. The model proposed here uses a two-stage approach to generate a holistic solution to the problem. The first stage uses a pull distribution strategy to make stockpile location decisions. Additionally, it determines how counties should be assigned to stockpiles to minimize both storage and distribution costs. The second stage adopts a push distribution strategy to determine optimal delivery routes based on the county assignments made in stage one. This stage offers guidance for public health planners who have made location-allocation decisions but who then face a different distribution scenario than what was anticipated in the original planning phase. Recourse methods for managing demand uncertainty are also proposed. A case study of the state of Kansas is conducted using the methods introduced in the thesis. The computational results yield several significant insights into the tradeoffs and costs of various facility location-allocation and vehicle routing decisions: • For the tested range of storage and distribution cost parameters, multiple stockpile locations are preferred over a single location. • In a pull distribution system, storage costs play a greater role in location-allocation decisions than distribution costs. • In the push distribution system, finding an optimal vehicle routing plan is computationally intensive for stockpiles with a large number of assigned counties. • Efficient heuristics perform well to design recourse routing plans when realized demand is greater than expected. • In the event that planners wish to specify routes well in advance, the results of this research suggest adopting a robust routing plan based on higher-than-expected demand levels. This thesis makes three important contributions. The first is an optimization approach that considers multiple distribution strategies. This is especially relevant when stockpiling for an influenza pandemic where stockpiles need to be located significantly before the material is needed, during which time the distribution strategy may change. Second, the case study demonstrates that the proposed methods are applicable to a large-scale problem arising in practice. Finally, this research illustrates for decision-makers the tradeoffs between different stockpile management strategies and between optimal and heuristic methods.