Modeling Vaccine Allocations in the COVID-19 Pandemic: A Case Study in Australia

Abstract

Timely allocation and distribution of COVID-19 vaccines on a large scale is a highly complex, dynamic, and context-specific task. The focus of this research on optimizing vaccine allocation is on the downstream part of a COVID-19 vaccine supply chain. Previous research on vaccine supply chains and pandemic supply chains has not fully incorporated the multitude of factors and underlying constraints affecting a vaccine supply chain which can be optimized to mitigate the risk of infection. An effective model is needed to conceptualize the process of the downstream vaccine supply chain to ensure efficient coordination and timely distribution of vaccines to the population. This paper develops a mathematical model to support vaccine allocation decisions based on exposure risk, susceptibility rate, and operational constraints including capacity of medical centers, vaccine stocks, and transshipment capacity. Our conceptual model integrates a centralized booking system, risk profiling and prioritization, and a vaccine distribution system, to develop an effective vaccine allocation model based on the parameters of the total population susceptible to COVID-19 and the density-based exposure risk in the catchment of each medical center. We have incorporated the possibility of transshipment between medical centers and a variety of different vaccine package sizes. Using the state of Victoria, Australia as a case study, we applied the proposed model to test different scenarios of vaccine allocation and distribution. This research proposes specific guidelines for COVID-19 vaccine distribution and makes recommendations on how healthcare providers and government entities should work together to establish more efficient logistical capabilities.