This study aims to estimate the parameters of a stochastic exposed-infected epidemiological model for the transmission dynamics of notifiable infectious diseases, based on observations related to isolated cases counts only. We use the setting of hidden multi-chain Markov models and adapt the Baum-Welch algorithm to the special structure of the multi-chain. From the estimated transition matrix, we retrieve the parameters of interest (contamination rates, incubation rate, and isolation rate) from analytical expressions of the moments and Monte Carlo simulations. The performance of this approach is investigated on synthetic data, together with an analysis of the impact of using a model with one less compartment to fit the data in order to help for model selection.

翻译：本研究旨在仅基于隔离病例数观测数据，估计法定传染病传播动力学随机暴露-感染流行病学模型中的参数。我们采用隐多链马尔可夫模型框架，并将包姆-韦尔奇算法适配至该多链结构的特殊性质。通过估计得到的转移矩阵，利用矩的解析表达式与蒙特卡洛模拟，反推出目标参数（包括感染率、潜伏期转化率及隔离率）。本研究基于合成数据验证了该方法的有效性，同时分析了使用少一个仓室的模型拟合数据对模型选择的影响。