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Mathematical modeling is one of the key factors of the effective control ofnewly found infectious diseases, such as COVID-19. Our knowledge about theparameters and the course of the infection is highly limited in the beginningof the epidemic, hence computer implementation of the models have to be quickand flexible. The propensity matrix - update graph method we discuss in thispaper serves as a convenient approach to efficiently implement age structuredstochastic epidemic models. The code base we implemented for our forecastingwork is also included in the attached GitHub repository.

Propensity matrix method for age dependent stochastic infectious disease models