A data-driven dynamical system model for assessing targeted interventions against brucellosis in Tanzania.

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Tác giả: Guttorm Alendal, Zachariah Makondo, Nyimvua Shaban Mbare, Eunice Mureithi, Innocent Sosoma

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: England : Comparative immunology, microbiology and infectious diseases , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 182768

Brucellosis remains a critical public health and economic concern in Tanzania, particularly in regions with high livestock-human interaction. This paper developed a data-driven dynamical system model to evaluate targeted interventions for controlling brucellosis transmission. The model integrated human, animal, and environmental components, emphasizing public health education and domestic animal management practices. Data from ten regions namely Dodoma, Morogoro, Manyara, Arusha, Mara, Kagera, Shinyanga, Mwanza, Tanga, and Singida, collected between January 2021 and May 2024 were used for parameter estimation. The model was fitted to observed data using a Markov Chain Monte Carlo (MCMC) method with the Adaptive Metropolis algorithm, while a graph-theoretic approach derived the effective reproduction number (R
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