Research Project: Herkese Aşı : Büyük Ölçekli Aşılama Hizmetleri İçin Adil ve Verimli Lokasyon, Rotalama ve Alokasyon Modelleri
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Contributors
Funders
ID
TB.00584
Authors
Salman, Fatma Sibel
Faculty Member
Publications
Fair and effective vaccine allocation during a pandemic
(Elsevier, 2024) Kiavash, Parinaz; Salman, Fatma Sibel; Erdoğan, Güneş; Yücel, Eda; Department of Industrial Engineering; Yes; College of Engineering
This paper presents a novel model for the Vaccine Allocation Problem (VAP), which aims to allocate the available vaccines to population locations over multiple periods during a pandemic. We model the disease progression and the impact of vaccination on the spread of the disease and mortality to minimise total expected mortality and location inequity in terms of mortality ratios under total vaccine supply and hospital and vaccination centre capacity limitations at the locations. The spread of the disease is modelled through an extension of the well -established Susceptible-Infected-Recovered (SIR) epidemiological model that accounts for multiple vaccine doses. The VAP is modelled as a nonlinear mixed -integer programming model and solved to optimality using the Gurobi solver. A set of scenarios with parameters regarding the COVID-19 pandemic in the UK over 12 weeks are constructed using a hypercube experimental design on varying disease spread, vaccine availability, hospital capacity, and vaccination capacity factors. The results indicate the statistical significance of vaccine availability and the parameters regarding the spread of the disease.
