2024/10/01 by Mahmudul Bari Hridoy, Hridoy, Mahmudul Bari, S M Mustaquim +1
Medicine · Social Sciences · #Applications (stat.AP) #Dengue and Mosquito Control Research #FOS: Biological sciences #FOS: Computer and information sciences #Mosquito-borne diseases and control #Populations and Evolution (q-bio.PE) #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.2410.00947
openalex publication_date 2024/10/01 · openalex created_date 2024/10/30 · openalex updated_date 2026/07/28
Bangladesh's worsening dengue crisis, fueled by its tropical climate, poor waste management infrastructure, rapid urbanization, and dense population, has led to increasingly deadly outbreaks, posing a significant public health threat. To address this, we propose a nonlinear, time-nonhomogeneous SEIR model incorporating seasonality through a novel transmission rate function. The model parameters are estimated using Bayesian inference with the Metropolis-Hastings algorithm in a Markov Chain Monte Carlo (MCMC) framework, calibrated with real-life dengue data from Bangladesh. To account for stochasticity and better assess outbreak probabilities, we extend the model to a time-nonhomogeneous continuous-time Markov chain (CTMC) framework. Our model provides new insights that can guide policymakers and offer a robust mathematical framework to better combat this crisis.