Author(s)

Angelo Raherinirina, Tsilefa Stefana Fandresena, Aimé Richard Hajalalaina, Haja Rabetafika, Rivo Andry Rakotoarivelo, Fontaine Rafamatanantsoa

University of Fianarantsoa, Madagascar.

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.

Modified SEIR Model, COVID-19 Madagascar, Basic Reproduction Number, Markov Chain Continuous Time

Raherinirina, A. , Fandresena, T. , Hajalalaina, A. , Rabetafika, H. , Rakotoarivelo, R. and Rafamatanantsoa, F. (2021) Probabilistic Modelling of COVID-19 Dynamic in the Context of Madagascar. Open Journal of Modelling and Simulation, 9, 211-230. doi: 10.4236/ojmsi.2021.93014.