Managing resilience and viability of supranational supply chains under epidemic control scenarios

A comprehensive model is presented to evaluate the resilience and viability of supranational supply chains under various epidemic control scenarios. The model integrates a multiplex network of socially connected individuals subjected to a probabilistic SEIRSD epidemic, as well as production configurations monitored for performance capacity. The epidemic evolution within this system depends on four primary cost factors: deployed control strategy, health policy implementation, the value of human life, and economic productivity loss due to the epidemic. These costs are adjusted for GDP differences between countries in the network and are influenced by factors such as the duration and severity of confinement, vaccination efficacy, and healthcare capacity. A Nash equilibrium analysis of SEIRSD load-based costs is employed to identify optimal control strategies. Time To Recovery (TTR) and Longitudinal Service Level (LSL) are used as metrics for assessing the resilience and viability of supply chains. The convergences and conflicts of control strategies are evaluated using TTR and LSL, providing insights into the impact of public health measures on supply chain performance. This methodology offers a framework for policymakers and supply chain managers to make informed decisions during prolonged epidemic conditions. Numerical simulations illustrate the conditions for convergence and conflict between epidemic control policies and supply chain objectives, highlighting the need for dynamic policy adjustments to ensure supply chain resilience and viability.