Angelo Raherinirina, Tsilefa Stefana Fandresena, A. R. Hajalalaina, H. Rabetafika, R. Rakotoarivelo, Fontaine Rafamatanantsoa
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Probabilistic Modelling of COVID-19 Dynamic in the Context of 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.