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Compartmental mathematical modelling of dynamic transmission of COVID-19 in Rwanda

OBJECTIVES: Mathematical modelling is of interest to study the dynamics of coronavirus disease 2019 (COVID-19), and models such as SEIR (Susceptible–Exposed–Infected–Recovered) have been considered. This article describes the development of a compartmental transmission network model – Susceptible–Ex...

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Detalles Bibliográficos
Autores principales: Mpinganzima, Lydie, Ntaganda, Jean Marie, Banzi, Wellars, Muhirwa, Jean Pierre, Nannyonga, Betty Kivumbi, Niyobuhungiro, Japhet, Rutaganda, Eric, Ngaruye, Innocent, Ndanguza, Denis, Nzabanita, Joseph, Masabo, Emmanuel, Gahamanyi, Marcel, Dushimirimana, Justine, Nyandwi, Bosco, Kurujyibwami, Célestin, Ruganzu, Léon Fidèle Uwimbabazi, Nyagahakwa, Venuste, Mukeshimana, Solange, Ngendahayo, Jean Pierre, Nsabimana, Jean Paul, Niyigena, Jean De Dieu, Uwonkunda, Jeanne, Mbalawata, Isambi Sailon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827742/
https://www.ncbi.nlm.nih.gov/pubmed/36644499
http://dx.doi.org/10.1016/j.ijregi.2023.01.003
Descripción
Sumario:OBJECTIVES: Mathematical modelling is of interest to study the dynamics of coronavirus disease 2019 (COVID-19), and models such as SEIR (Susceptible–Exposed–Infected–Recovered) have been considered. This article describes the development of a compartmental transmission network model – Susceptible–Exposed–Quarantine–Infectious–Infectious, undetected–Infectious, home-based care–Hospitalized–Vaccinated–Recovered–Dead – to simulate the dynamics of COVID-19 in order to account for specific measures put into place by the Government of Rwanda to prevent further spread of the disease. METHODS: The compartments of this model are connected by parameters, some of which are known from the literature, and others are estimated from available data using the least squares method. For the stability of the model, equilibrium points were determined and the basic reproduction number [Formula: see text] was studied; R(0) is an indicator for contagiousness. RESULTS: The model showed that secondary infections are generated from the exposed group, the asymptomatic group, the infected (symptomatic) group, the infected (undetected) group, the infected (home-based care) group and the hospitalized group. The formulated model was reliable and fit the data. Furthermore, the estimated [Formula: see text] of 2.16 shows that COVID-19 will persist without the application of control measures. CONCLUSIONS: This article presents results regarding predicted spread of COVID-19 in Rwanda.