ArticleInternational journal of production economics2022
Social equity-based distribution networks design for the COVID-19 vaccine.
Article in International journal of production economics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Optimal strategies for fair vaccine allocation: integrating non-pharmaceutical interventions, regional quarantine, and social challenges in epidemic control.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- Proposal of a Vaccination Needs Index to Prioritise Municipal Interventions in Brazil.Tropical medicine & international health : TM & IH · 2026Article
- Prophylactic and therapeutic vaccine development: advancements and challenges.Molecular biomedicine · 2024Review
- Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.Naval research logistics · 2024Article
- An integrated blockchain-enabled multi-channel vaccine supply chain network under hybrid uncertainties.Scientific reports · 2024Article
- The role of hesitancy and infrastructure in the equity and efficiency of COVID-19 vaccine administration.PloS one · 2024Article
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Authors and funding
4 authors.
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Abstract
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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