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  • 标题:Probabilistic Modelling of COVID-19 Dynamic in the Context of Madagascar
  • 本地全文:下载
  • 作者:Angelo Raherinirina ; Tsilefa Stefana Fandresena ; Aimé Richard Hajalalaina
  • 期刊名称:Open Journal of Modelling and Simulation
  • 印刷版ISSN:2327-4018
  • 电子版ISSN:2327-4026
  • 出版年度:2021
  • 卷号:9
  • 期号:3
  • 页码:211-230
  • DOI:10.4236/ojmsi.2021.93014
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:We propose a probabilistic approach to modelling the propagation of the coronavirus disease 2019 (COVID-19) in Madagascar, with all its specificities. With the strategy of the Malagasy state, which consists of isolating all suspected cases and hospitalized confirmed case, we get an epidemic model with seven compartments: susceptible (S), Exposed (E), Infected (I), Asymptomatic (A), Hospitalized (H), Cured (C) and Death (D). In addition to the classical deterministic models used in epidemiology, the stochastic model offers a natural representation of the evolution of the COVID-19 epidemic. We inferred the models with the official data provided by the COVID-19 Command Center (CCO) of Madagascar, between March and August 2020. The basic reproduction number R0 and the other parameters were estimated with a Bayesian approach. We developed an algorithm that allows having a temporal estimate of this number with confidence intervals. The estimated values are slightly lower than the international references. Generally, we were able to obtain a simple but effective model to describe the spread of the disease.
  • 关键词:Modified SEIR Model;COVID-19 Madagascar;Basic Reproduction Number;Markov Chain Continuous Time
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