Evaluating the Resilience of COVID-19 Vaccine Supply Chain using Bayesian Networks

Abstract

The COVID-19 pandemic has posed a significant challenge to the COVID-19 vaccine supply chain that need to be resolved for a successful exit from the pandemic. It is essential to identify and evaluate the risks associated with the vaccine supply chain. We propose a new measure for quantifying the resilience of the vaccine supply chain in Iran. To evaluate the resilience of the vaccine supply chain, we use a Bayesian network to consider the vulnerability and recoverability indices as well as the associated disruption propagation. This approach enables managers to measure the resilience of the supply chain and identify the reasons for performance decline due to the ripple effect. Our results show that outbreak risks, lack of access to vaccine suppliers, low efficacy of the vaccine against new variants, inaccurate prediction of vaccine demand, and failure to choose the right suppliers are the risks likely to have a high impact on the disruption of the vaccine supply chain. Our approach provides a useful tool for evaluating the resilience of the vaccine supply chain and identifying the critical risks. It can be used by decision-makers to mitigate the impact of disruptions and improve overall resilience of the vaccine supply chain.

Keywords

• resilience
• risk
• vaccine supply chain
• covid-19
• bayesian network