传染病症状监测系统的设计要点与方法

近十年来,症状监测作为一种新兴的公共卫生监测手段引起了普遍的关注.相对于基于病例诊断的传统公共卫生监测手段,症状监测是对临床诊断前患者相关的非特异性信息进行监测1].相关研究表明,症状监测可应用于公共危机应对(如生物恐怖事件早期发现2,3]、自然灾害传染病应急监测4]),早期探测新发传染病5],掌握疾病发病水平与流行趋势(如急性迟缓性麻痹综合征监测和流感样病例监测6,7]),以及大型体育活动与政治集会等大规模人群聚集活动公共卫生保障8,9].

The key components and method of designing syndromic surveillance

To introduce the application of generalized multifactor dimensionality reduction (GMDR) method for detecting interactions, especially gene-gene interactions for quantitative traits. Principles, basic steps as well as features of GMDR were discussed, illustrated with a practical research case. As an interaction analysis method, GMDR was model-free, available for studies on different outcome variables including continuous ones, and permitted adjustment for covariates to improve prediction accuracy. Evidences of its capacity had been supposed by research on different diseases, e.g. nicotine dependence. GMDR method was applicable to different types of samples and outcome variables, which was superior to other statistical approaches for continuous variables in some aspects.