Using a Stochastic SIR Model to Design Optimal Vaccination Campaigns via Multiobjective Optimization

A. C. S. Dusse () and R. T. N. Cardoso
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A. C. S. Dusse: Centro Federal de Educação Tecnológica de Minas Gerais
R. T. N. Cardoso: Centro Federal de Educação Tecnológica de Minas Gerais

A chapter in Trends in Biomathematics: Modeling Cells, Flows, Epidemics, and the Environment, 2020, pp 245-258 from Springer

Abstract: Abstract The design of optimal vaccination campaigns using mathematical and computational models has given concrete suggestions to politicians and other ones responsible on how it should be implemented in a better way, given a certain allowed level of infected persons within the whole population. In this paper, a multiobjective impulsive control scheme in an open-loop continuous-variable dynamic optimization procedure is proposed to cope with this problem, having the NSGA-II (Non-dominated Sorting Genetic Algorithm) as an optimization machinery and the SIR (Susceptible–Infectious–Recovered) model describing the behavior of a disease in a population, extended to analyze the effects of impulsive vaccination on the population. Furthermore, a stochastic SIR model is adapted in order to calculate the probability of eradication to each non-dominated vaccination policy came from the NSGA-II, as decision criteria. The target of the analysis is to give concrete suggestions to politicians or decision-makers how optimal vaccination campaigns should be implemented, given a certain probability of eradication or an allowed level of infected persons within the whole population.

Keywords: Planning of vaccination campaigns; Multiobjective optimization; Stochastic SIR (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-46306-9_16

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DOI: 10.1007/978-3-030-46306-9_16

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