| Summary: | Pasteurellosis remains a major problem for poultry worldwide. The disease causes high mortality in chicken, affecting the livelihood of rural poultry farmers. In this paper, both deterministic and continuous time Markov chain (CTMC) models are formulated and analyzed to study the dynamics of pasteurellosis in chicken and wild birds. The next generation matrix method is adopted to determine the basic reproduction number for the deterministic model whereas the multitype branching process is used to compute stochastic threshold for the CTMC model. The normalized forward sensitivity index method is implemented to derive sensitivity indices of model parameters. The results show that the per capita recruitment rate of susceptible chicken and its infection rate due to direct contact are the most positive sensitive parameters, whereas the consumption rate of susceptible chicken by humans and the disease induced death rate are the most negative sensitive parameter. This suggests that infectious chicken drive the disease. Thus efforts on vaccinating and treating susceptible and infectious chicken respectively, will reduce the number of pasteurellosis cases in both chicken and wild bird populations. Numerical simulations for the CTMC stochastic model indicate that the solutions of CTMC stochastic model are relatively close to the solutions of the deterministic model. The probability of pasteurellosis extinction is high when it emerges from infectious birds unlike if it emerges from infectious chicken or P. multocida bacteria. Thus, any intervention that focuses on reducing the number of infectious chicken at the beginning of pasteurellosis outbreak is essential for reducing the transmission of pasteurellosis in chicken and wild birds.
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