In this study, a hybrid model analysis on host factor of epidemics involving fuzzy markovian chain is presented. This hybrid model consists of stochastic approach involving markovian chain, fuzzy expert system, simulation approach and fuzzy set theory in order to obtain the system response in a more realistic manner. A stochastic model of the two state markovian-chains is applied to certain epidemics by age group. An age specific member rate and fuzzy markovian risk rate are defined and used as novel measure indices to prioritize age groups. A fuzzy expert system is used in medical diagnosis for various classifications. For simulating the process, we have taken the symptom data for the diseases from the experienced medical experts. The computation of max-min composition is assumed to describe the state of the patients (age wise) in terms of diagnosis as a fuzzy set characterized by its membership value. The analysis of age specific diagnosis of certain diseases is essential to provide the data for the planning of health services and to setting up of priorities among those services. The combination of stochastic approach and the fuzzy logic enables our computational simulation to much more faithfully portray the phenomena under study.