Fair allocation of potential COVID-19 vaccines using an optimization-based strategy

Abstract

The fair allocation of resources among multiple stakeholders in any area is a complex challenge for decision-making. This paper presents an optimization strategy for the allocation of COVID-19 vaccines, when they are available, through different fairness schemes (social welfare, Nash, Rawlsian justice, and social welfare II scheme). The applicability of the proposed model is illustrated using the case study of Mexico, including the states of the country as stakeholders. We involve several parameters to guide the allocation, such as the size, risk profiles, and fraction of vulnerable groups in the population. Furthermore, different scenarios of the availability of potential COVID-19 vaccines were evaluated. The social welfare approach is the most commonly used scheme for the allocation of resources. However, we demonstrate that this scheme yields non-unique or multiple solutions (through the social welfare II approach). These social welfare approaches provide inequalities in the allocations that become critical when resources are scarce. Specifically, the social welfare scheme favors large stakeholders (greater population) in all scenarios. We also observe how the complexity of the allocation increases with the higher availability of vaccines. Hence, it is important to consider allocation schemes to identify fair solutions.

Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: A distribution case study of COVID-19 vaccine doses

“…Countries worldwide faced the greatest challenge last year brought by the coronavirus disease 2019 (COVID-19) pandemic, and the need for a vaccine has become more important than ever [75] , [76] , [77] , [78] , [79] , [80] , [81] , [82] . The fair allocation of COVID-19 vaccine distribution is encouraged by the World Health Organisation, and public health benefits must be maximized in order that health products are available and accessible to those in need [83] . However, the distribution mechanism of COVID-19 vaccine doses considered a MCDM problem because of the following issues: required inclusion of different distribution criteria, criteria that are different in significance and increase in problem complexity because of data variation amongst the included criteria.…”

Use of Mathematical Approaches for Addressing COVID-19 Pandemic — a Critical Review

“…Recently, Munguía-López and Ponce-Ortega ( 2021 ) developed a strategy for the distribution of vaccines that implements the use of distribution schemes based on the theories of justice of Social Welfare, Rawls, and Nash. With these schemes, it is intended to reach an optimal and fair solution through the evaluation of parameters related to the medical area, such as the sectors of the population affected by autoimmune diseases or the elderly (population with higher epidemiological risk).…”

Comparison of health-oriented cross-regional allocation strategies for the COVID-19 vaccine: a mathematical modelling study

“…However, under the condition of the highly infectious characteristics of SARS-CoV-2, an immunisation strategy based on reducing transmission has not been highly valued by scholars, despite it being an indispensable part of reducing the overall burden of disease in previous allocation strategies for influenza vaccines and the RTS,S malaria vaccine [ 20 , 21 ]. Incorporating correlations between the spread of the epidemic in different regions into the model from a spatial dimension to identify health-oriented vaccine allocation strategies is a high priority in the context of the current pandemic [ 22 ]. Therefore, this study used a cross-regional SEIR model that considered the interactions of epidemic evolution in different regions to explore epidemic prevention and control effects that the health-oriented vaccine allocation strategies could produce.…”