Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China)

Abstract

The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.

Keywords: epidemic logistics; epidemic outbreak; medical waste; network design; operations research; reverse logistics.

Figure 1

Reverse logistics network for effective management of medical waste in epidemic outbreak.

Figure 2

Prediction of the tendency of the COVID-19 spread in Wuhan with SEIR method in AnyLogic simulation: (a) Curve fit with the real data; (b) Predication of the infections in two months.

Figure 3

Locations of hospitals, existing facilities, and candidates for temporary facilities in central Wuhan.

Figure 4

Pareto optimal solutions.

Figure 5

Comparison between the prediction on February 9th and the real data of the COVID-19 infections in Wuhan until February 26th.