Population size estimation based on the capture-recapture experiment is an interesting problem in various fields including epidemiology, criminology, demography, etc. In many real-life scenarios, there exists inherent heterogeneity among the individuals and dependency between capture and recapture attempts. A novel trivariate Bernoulli model is considered to incorporate these features, and the Bayesian estimation of the model parameters is suggested using data augmentation. Simulation results show robustness under model misspecification and the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse real case studies on epidemiological surveillance. The results provide interesting insight on the heterogeneity and dependence involved in the capture-recapture mechanism. The methodology proposed can assist in effective decision-making and policy formulation.

翻译：根据抓捕-抓获实验得出的人口规模估计是各个领域的一个令人感兴趣的问题,包括流行病学、犯罪学、人口学等。在许多现实生活中,个人之间有着固有的异质性,在抓捕和抓捕尝试之间也存在依赖性。认为一种新颖的三变伯努利模型可以纳入这些特征,建议采用数据扩增方法对模型参数进行巴伊西亚估计。模拟结果显示模型的特性不准确,而且拟议方法的性能优于现有竞争者。该方法用于分析流行病学监测的实际案例研究。结果对抓捕-抓捕机制所涉及的异质性和依赖性提供了有趣的洞察力。拟议方法有助于有效的决策和政策制定。