4.6 Article

Social equity-based distribution networks design for the COVID-19 vaccine

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DOI: 10.1016/j.ijpe.2022.108684

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Social equity; COVID-19; Vaccine distribution; Network design; Stochastic programming

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This study investigates the role of social equity in vaccine distribution network design problems and proposes a novel bi-objective two-stage stochastic programming model and a lexicographic goal programming approach. The findings suggest that each social equity theory has its own merits, with Rawls' theory resulting in greater coverage in rural areas, utilitarianism leading to higher vaccine allocation to social groups, and Sadr's theory performing better in terms of both allocation and cost. The insights gained from this study can help decision-makers in leveraging the right equity approach in the COVID-19 vaccine context and being better prepared for future pandemic crises.
This study aims to investigate the role of social equity in vaccine distribution network design problems. Inspired by the current COVID-19 vaccine allocation in-country context, we capture social equity-based distribution by modeling three theories: Rawls' theory, Sadr's theory, and utilitarianism. We consider various social groups based on degree of urbanization, including inhabitants of cities, towns and suburbs, and rural areas. The distribution problem is subject to, on the one hand, demand-side uncertainty characterized by the daily contamination rate and its space-time propagation that anticipate the in-need population. On the other hand, supply-side uncertainty characterized by the stochastic arrival of vaccine doses for the supply period. To tackle this problem, we propose a novel bi-objective two-stage stochastic programming model using the sample average approximation (SAA) method. We also develop a lexicographic goal programming approach where the social equity objective is prioritized, thereafter reaching an efficiency level. Using publicly available data on COVID-19 in-country propagation and the case of two major provinces in Iran as example of middle-income country, we provide evidence of the benefits of considering social equity in a model-based decision-making approach. The findings suggest that the design solution produced by each social equity theory matches its essence in social science, differing considerably from the cost-based design solution. According to the general results, we can infer that each social equity theory has its own merits. Implementing Rawls' theory brings about a greater coverage percentage in rural areas, while utilitarianism results in a higher allocation of vaccine doses to social groups compared to the Sadr and Rawls theories. Finally, Sadr's theory outperforms Rawls' in terms of both the allocation and cost perspective. These insights would help decision-makers leverage the right equity approach in the COVID-19 vaccine context, and be better prepared for any pandemic crisis that the future may unfold.

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