Browsing by Author "Msuya, Rehema"

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    A two-patch model to quantify uncertainties in the transmission of brucellosis between domestic animals
    (Elsevier, 2025-09) Msuya, Rehema; Mirau, Silas; Nyerere, Nkuba; Mbalawata, Isambi
    Brucellosis, a neglected zoonotic disease, poses significant health risks to both humans and livestock. This study investigates a key factor influencing brucellosis transmission: the movement of animals in and out of communal grazing areas. We develop a Continuous Time Markov Chain (CTMC) stochastic model, building on its deterministic counterpart, to assess the impact of short-term animal movements on disease transmission dynamics. By incorporating stochasticity, the model captures the inherent variability in disease transmission and animal movements, providing deeper insights than traditional deterministic models. A multitype branching process is employed to evaluate the probabilities of disease extinction. We compute the basic reproduction number and the stochastic threshold . Numerical simulations indicate that brucellosis transmission accelerates when domestic animals spend more time in high-risk communal grazing areas. Additionally, the results suggest a high probability of disease extinction when animals moves out of high-risk area. Conversely, when animals from both patches increase their time in high-risk zones, the likelihood of disease extinction diminishes. This study underscores the importance of implementing strategic movement controls and targeted interventions in high-risk areas to mitigate outbreaks and enhance disease management.
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    The role of temporary displacement of domestic animals in brucellosis control
    (Elsevier, 2025-10-27) Msuya, Rehema; Mirau, Silas; Nyerere,Nkuba; Mbalawata, Isambi
    Brucellosis is one of the most prevalent zoonotic diseases worldwide, with significant impacts on human health, animal productivity, and the economy. Animal movement is a key factor influencing its transmission; however, the understanding of how such movements shape disease dynamics and the effectiveness of applied control measures remains limited. This study presents an optimal control model for brucellosis transmission among domestic animals, given the uncertainty in animal movement patterns. The model incorporates and evaluates the effectiveness of different control strategies under varying movement patterns. The effective reproduction number is computed, compared with the basic reproduction number , and used to quantify the potential for brucellosis spread and the effectiveness of different control measures for different time proportions a domestic animal spends in low or high-risk patches. Global sensitivity analysis was performed using the Latin Hypercube Sampling (LHS) approach, where the Partial Rank Correlation Coefficient (PRCC) index was computed. The results show that the time spent by domestic animals in high-risk areas limits the control of brucellosis. The findings also reveal that vaccination is the most effective strategy for significantly reducing the spread of brucellosis, even when domestic animals from low-risk areas spend extended periods in high-risk zones. This underscores the pivotal role of vaccination as the cornerstone of brucellosis control and prevention efforts.