A multi-objective approach to estimate parameters of compartmental epidemiological models. Application to Ebola Virus Disease epidemics.

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Ferrández, M.R. and Ivorra, Benjamin and Redondo, Juana L. and Ramos del Olmo, Ángel Manuel and Ortigosa, Pilar M. (2020) A multi-objective approach to estimate parameters of compartmental epidemiological models. Application to Ebola Virus Disease epidemics. pp. 1-48. (Submitted)

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Abstract

In this work, we propose a novel methodology to adjust parameters of compartmental epidemiological models. It is based on solving a multi-objective optimization problem that consists in fitting some of the model outputs to real observations. First, according to the available data of the considered epidemic, we define a multi-objective optimization problem where the model parameters are the optimization variables. Then, this problem is solved by considering a particular optimization algorithm called ParWASF-GA (ParallelWeighting Achievement Scalarizing Function Genetic Algorithm).
Finally, the decision maker chooses, within the set of possible solutions, the values of parameters that better suit his/her preferences. In order to illustrate the benefit of using our approach, it is applied to estimate the parameters of a deterministic epidemiological model, called Be-CoDiS (Between-Countries Disease Spread), used to forecast the possible spread of human diseases within and between countries. We consider data from different Ebola outbreaks from 2014 up to 2019. In all cases, the proposed methodology helps to obtain reasonable predictions of the epidemic magnitudes with the considered model.


Item Type:Article
Uncontrolled Keywords:Parameter estimation, Multi-objective optimization, Epidemiology, Ebola virus
Subjects:Sciences > Mathematics > Operations research
Medical sciences > Medicine > Communicable diseases
Medical sciences > Medicine > Public health
ID Code:63009
Deposited On:10 Nov 2020 16:45
Last Modified:25 Jan 2021 12:42

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