Strategic planning for the optimal distribution of COVID-19 vaccines

doi:10.1016/j.seps.2023.101559

Socio-Economic Planning Sciences

Volume 87, Part A, June 2023, 101559

https://doi.org/10.1016/j.seps.2023.101559 Get rights and content

Highlights

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This approach addresses the optimal allocation of COVID-19 vaccines involving fairness concepts.
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The model includes social behavior data that can impact the distribution.
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The applicability of the model is shown using a case study of Mexico.
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The strategy allows identifying trade-off solutions.
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The optimal solutions are shown through Pareto curves.

Abstract

This work presents a multi-objective optimization strategy for fair vaccine allocation through different fairness schemes. The proposed approach considers a diverse series of parameters related to different public health data and social behaviors that influence the correct distribution of vaccines, such as corruption and crime. Simultaneously, the formulation includes prioritizing those groups with the highest risk based on the epidemiological traffic light. Furthermore, the presented strategy involves different budget constraints that allow identifying trade-off solutions through Pareto fronts. Therefore, vaccine allocations are obtained by combining fairness concepts with multi-objective optimization. The applicability of the model is illustrated using the case study of Mexico. The solution to the proposed scenarios was carried out using different justice schemes and an economic objective function. The results show the compromises between a satisfaction index and costs, which are shown through Pareto optimal solutions that allow selecting the solutions that balance the objectives. The solutions provided by the social welfare scheme suggest a greater allocation of vaccines to those states with higher epidemiological risk, which may be helpful in the first stage of vaccination. On the other hand, the Rawlsian scheme provides more balanced solutions that can be useful in situations with lower rates of infection. Finally, the Nash scheme is the one that provides the most balanced solutions, favoring to a lesser extent the areas with the highest epidemiological risk, which may be useful in the later stages of vaccination.

Keywords

Vaccines

Optimal distribution

Fair allocation

COVID-19

Data availability

Data will be made available on request.

Cited by (0)

Rogelio Ochoa-Barragan is a Ph.D. student in the Department of Chemical Engineering at the Universidad Michoacana de San Nicolás de Hidalgo. He has a M.Sc. and B.Sc. in Chemical Engineering from Universidad Michoacana de San Nicolás de Hidalgo. His main research interests include resource allocation, mathematical modeling, optimization, design, and 3d modeling.

Dr. Aurora del Carmen Munguía-López is a postdoctoral researcher in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. She holds B.Sc. and M.Sc. degrees from the Technical Institute of Celaya and a Ph.D. in Chemical Engineering from the University of Michoacan in Mexico. During her Ph.D., she was a visiting scholar in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. Her research interests include mathematical optimization, sustainability, social justice, and process modeling. Aurora is also passionate about fostering diversity, equity, and inclusion in STEM.

Dr. José María Ponce-Ortega got his Ph.D. and Master degrees in Chemical Engineering in the Institute of Technology of Celaya in Mexico in 2009 and 2003, respectively. He stayed as a postdoctoral researcher in Texas A&M University from 2011 to 2012 under the supervision of Professor Mahmoud El-Halwagi, and as visiting scholar in Carnegie Mellon University from 2006 to 2007 under the supervision of Professor Ignacio Grossmann. Dr. Ponce-Ortega is full professor at the Universidad Michoacana de San Nicolás de Hidalgo since 2012 until today, and he is member of the National Research System of Mexico (SNI II). The research interest of Dr. Ponce-Ortega is in the areas of optimization of chemical processes, sustainable design, energy, mass, water and property integration and supply chain optimization. Dr. Ponce-Ortega has published more than 213 papers, 3 books and 51 chapters of books. He also has supervised 15 Ph.D. and 35 Master graduated students. He also has had 15 funded research projects for about $US 1,000,000.00. Dr. Ponce-Ortega is member of the editorial board in the Journals Clean Technologies and Environmental Policy, and Process Integration and Optimization for Sustainability.

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