Computational Medicine Issues

This chapter first introduces a Discrete-Time Markov Chain Process aimed to predict the spread of a disease in a region, based on the census of the subjects: S, susceptible; Ia, Active infected; In, Inactive infected; Na Subject dead by natural causes; Nm Subject killed by the disease. Later, is introduced a Continuous-Time Markov Chain Process to predict the spread of a disease based on different census of the subjects: S, number of susceptible individuals; I, number of infected individuals; and R number of recovery individuals. Both methods are known to be effective in issuing early warnings for serious respiratory infections. Both cases are exemplified and discussed.