A hybrid model for modeling the spread of epidemics: Theory and simulation

The spread of disease is a dynamic and complex phenomenon. In the world, diseases are the effects of misery and poverty. To find how to understand epidemiological systems is essential for governments. So why, modeling is an excellent method because it simplifies the reality. Presently, models of differential equations like SIR and SEIR are the most used, but they are more difficult to apply at the world scale. In this paper we propose a hybrid model, which presents a case of modeling an epidemic spreading to several cities in a SIR compartmental model (Susceptible - Infected - Recovered). This hybrid model certifies that the population mobility, the basic reproduction number, the simulation environment and other factors greatly influence the dynamics of disease. The particular interest of our model is its hybrid nature. We modeled the spread of diseases by coupling the Agent-Based Model (ABM) and differentials equations as well as designing hybrid model by taking the simultaneous advantages of Agent-Based Models and mathematical models (ODE). Our model does not require a lot of parameters nor several hardware resources compared to general Agent-Based Models. Simulations based on 10,000 to 100,000 individuals were performed without problems.