<p>In the aftermath of a pandemic, there has been a substantial increase in the generation of infectious medical waste. This necessitates the design of effective reverse logistics supply chains to control virus transmission and promotes a sustainable waste management system. This paper focuses on optimizing the joint decisions on the location and transportation of infectious medical waste in the presence of hierarchical relations and sustainability during a pandemic. The problem is developed as a bi-level optimization model to maximize total job opportunities and minimize total costs at the first level, and minimize total infection risks at the second level. To address this complex problem, a combination of KKT conditions, the augmented ε-constraint approach, and Pareto optimization is employed. A real case from Wuhan is applied to illustrate the formulated model. The results demonstrate that the augmented ε-constraint approach significantly outperforms conventional version and linear weighted sum method in tackling the intricate issue. To establish sustainable reverse logistics supply chains for infectious medical waste, a cross-regional transportation strategy for temporary transfer points and a differentiation strategy for the establishment of disposal centers are encouraged during a pandemic. The formulated model shows potential advantages in handling uncertainties in infectious medical waste location and transportation decision-making while accommodating managers’ varying preference for multiple objectives in the context of a pandemic.</p>