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：本研究旨在基于仅与孤立病例计数相关的观测数据，估计须报告传染病传播动力学中随机暴露-感染流行病学模型的参数。我们采用隐多链马尔可夫模型框架，并将Baum-Welch算法适配至多链的特殊结构。通过估计得到的转移矩阵，利用矩的解析表达式和蒙特卡洛模拟反演出目标参数（感染率、潜伏率及隔离率）。基于合成数据验证该方法的性能，同时分析采用少一个分室的模型拟合数据对模型选择的影响，为模型甄选提供依据。