Multiobjective synthesis of robust vaccination policies

Cruz, Andre Rodrigues da; Cardoso, Rodrigo T. N.; Takahashi, Ricardo H. C.

doi:10.1016/j.asoc.2016.11.010

Cited by 12 publications

(35 citation statements)

References 21 publications

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“…This work is based on control by pulse vaccination, which means that in certain time steps, a given percentage of the susceptible individuals get vaccinated and becomes part of the recovered population, according to references [1,7,9,10,14]. This approach allows different sizes of pulse control actions at arbitrary time instants.…”

Section: Optimization Modelmentioning

confidence: 99%

“…The nondominated solutions are validated in an Individual Based Model (IBM) to study a set of interval of confidence for each optimal policy strategy. Finally, the article [10] proposed an optimization scheme, implemented with a local search procedure, and a hash table is then adopted to cope with the optimization machinery in order to prevent variability. It is also proposed a control in two parts: choosing a set of optimal permanent regimes coupled with a set of temporary regimes.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Vaccination Campaigns Using Stochastic SIR Model and Multiobjective Impulsive Control

Cardoso

Dusse²,

Adam³

2021

TCAM

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A multiobjective impulsive control scheme is proposed to give answers on how optimal vaccination campaigns should be implemented, regarding two conflicting targets: making the total number of infecteds small and the vaccination campaign as handy as possible. In this paper, a stochastic SIR model is used to better depict the characteristics of a disease in practical terms, where little influences may lead to sudden and unpredictable changes in the behavior of transmissions. This model is extended to analyze the effects of impulsive vaccinations in two phases: the transient regime control, taking into account the necessity to reduce the number of infected individuals to an acceptable level in a finite time, and the permanent regime control, that will act with fixed vaccinations to avoid another outbreak. A parallel version of NSGA-II is used as the multiobjective optimization machinery, considering both the probability of eradication and the vaccination campaign costs. The final result using the proposed framework nondominated policies that can guide for public managers to decide which is the best procedure to be taken depending on the present situation.

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Section: Optimization Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Vaccination Campaigns Using Stochastic SIR Model and Multiobjective Impulsive Control

Cardoso

Dusse²,

Adam³

2021

TCAM

Self Cite

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“…In [8] the authors formulate a bi-objective model for planning vaccination campaigns that aim at minimising both control costs and the number of infected individuals.…”

Section: Related Literaturementioning

confidence: 99%

Mass Vaccine Administration under Uncertain Supply Scenarios

Foderaro

Naldi

Nicosia

et al. 2021

Annals of Computer Science and Information Systems

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The insurgence of COVID-19 requires fast mass vaccination, hampered by scarce availability and uncertain supply of vaccine doses and a tight schedule for boosters. In this paper, we analyze planning strategies for the vaccination campaign to vaccinate as many people as possible while meeting the booster schedule. We compare a conservative strategy and q-days-ahead strategies against the clairvoyant strategy. The conservative strategy achieves the best trade-off between utilization and compliance with the booster schedule. Q-days-ahead strategies with q < 7 provide a larger utilization but run out of stock in over 30% of days.

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“…To be precise, it means that the time in the closed interval [0, T f ], being T f the final time, has to be partitioned in a set of instants previously fixed Γ = {τ 0 , ..., τ M }, such that: [4]. The time between each τ k and τ k+1 is considered as a stage of the problem.…”

Section: Behaviour Of the Model Under Influence Of Vaccinationmentioning

confidence: 99%

“…: the accumulated number of infected or the probability of eradication F 2 : the sum of vaccined people as the total cost with the campaigns (4) subject to: The multiobjective optimization model offers a whole set of optimal solutions regarding the total number of infected people as well as the costs of the campaigns. Decision-makers can then decide for one of these optimal campaigns, according to other variables like budget, media influence, society's view of the disease, guidelines by law or politics and so on.…”

Section: Multiobjective Optimization and Genetic Algorithmsmentioning

confidence: 99%

Optimal Multiobjective Pulse Vaccination Campaigns in Stochastic SIR Model

Adam¹,

Cardoso²

2020

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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This article describes the results obtained with a stochastic SIR (Susceptives-Infectives-Recovered) model with impulsive vaccination campaigns. It tries to give answers to the question of how vaccination campaigns should be implemented, regarding random influences and two main targets which conflict with each other: making the vaccination campaign as cheap and handy as possible and the total number of infected persons as small as possible or the probability of eradication as greater as possible. The target of the analysis is to compare if it is better to consider the probability of eradication before or in the multiobjective optimization procedure. Results show that pre-consider the probability of eradication will be similar to the post-considering regarding their costs and quantity of infected persons, despite being computationally harder.

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Multiobjective synthesis of robust vaccination policies

Cited by 12 publications

References 21 publications

Optimal Vaccination Campaigns Using Stochastic SIR Model and Multiobjective Impulsive Control

Optimal Vaccination Campaigns Using Stochastic SIR Model and Multiobjective Impulsive Control

Mass Vaccine Administration under Uncertain Supply Scenarios

Optimal Multiobjective Pulse Vaccination Campaigns in Stochastic SIR Model

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