ESSAI DE MODÉLISATION MATHÉMATIQUE DE LA DYNAMIQUE DE TRANSMISSION DE LA MALADIE À VIRUS EBOLA DANS LA PROVINCE DU NORD-KIVU ET L'ITURI EN 2022

Introduction: Human behavior is a key element in the transmission and persistence of the ebola epidemic. Here we present the epidemiological models of its transmission. Methods: Non-deterministic models used. The derivatives d/dt gave us the variation of the model functions as a function of time t, in order to describe their evolution during the duration of the epidemic. Results: Bayes' theorem is well applicable in the modeling of ebola and in the absence of strict measures, the probability P(M) for one confirmed case to generate another is 100%. The average µ for the expected cases according to the applied model was 3072 cases and the number of observed cases (3470) is slightly higher than this average (Gaussian curve). The number of sick people doubled every 50 days and the epidemic. Conclusion: The establishment of equations to describe the epidemic in a reproducible and simulable way gives an idea of the evolution of the disease