论文标题
使用Capture-Recapture数据估计战后健康疾病的患病率
Estimating Prevalence of Post-war Health Disorders Using Capture-recapture Data
论文作者
论文摘要
由于战争和恐怖袭击而对长期公共卫生影响的有效监视仍然有限。此类健康问题通常是针对大量个人的专门报道的。为此，有效地估计了在身心健康危害风险下对人口的规模的估计。在这种情况下，多个系统估计是一种潜在的策略，最近已应用于量化未经报告的事件，允许个人之间的异质性和信息来源之间的依赖性。为了模拟这种复杂现象，开发了一种新型的三角型伯努利模型，并提出了使用基于蒙特卡洛的EM算法的估计方法。仿真结果表明，在模型错误规范化下，所提出的方法的性能优于现有竞争对手和鲁棒性。该方法用于分析美国世界贸易中心的海湾战争和9/11恐怖袭击的真实案例研究。结果提供了有趣的见解，可以帮助有效的决策和政策制定，以监视战后幸存者的健康状况。
Effective surveillance on the long-term public health impact due to war and terrorist attacks remain limited. Such health issues are commonly under-reported, specifically for a large group of individuals. For this purpose, efficient estimation of the size of the population under the risk of physical and mental health hazards is of utmost necessity. In this context, multiple system estimation is a potential strategy that has recently been applied to quantify under-reported events allowing heterogeneity among the individuals and dependence between the sources of information. To model such complex phenomena, a novel trivariate Bernoulli model is developed, and an estimation methodology using Monte Carlo based EM algorithm is proposed. Simulation results show superiority of the performance of the proposed method over existing competitors and robustness under model mis-specifications. The method is applied to analyze real case studies on the Gulf War and 9/11 Terrorist Attack at World Trade Center, US. The results provide interesting insights that can assist in effective decision making and policy formulation for monitoring the health status of post-war survivors.
