Wolfe Mitchell I, Nolte Kurt B, Yoon Steven S
Division of HIV/AIDS Prevention, National Center for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia 30333, USA.
Emerg Infect Dis. 2004 Jan;10(1):48-53. doi: 10.3201/eid1001.020764.
Increasing infectious disease deaths, the emergence of new infections, and bioterrorism have made surveillance for infectious diseases a public health concern. Medical examiners and coroners certify approximately 20% of all deaths that occur within the United States and can be a key source of information regarding infectious disease deaths. We hypothesized that a computer-assisted search tool (algorithm) could detect infectious disease deaths from a medical examiner database, thereby reducing the time and resources required to perform such surveillance manually. We developed two algorithms, applied them to a medical examiner database, and verified the cases identified against the opinion of a panel of experts. The algorithms detected deaths with infectious components with sensitivities from 67% to 94%, and predictive value positives ranging from 8% to 49%. Algorithms can be useful for surveillance in medical examiner offices that have limited resources or for conducting surveillance across medical examiner jurisdictions.
传染病死亡人数的增加、新感染病例的出现以及生物恐怖主义,使得传染病监测成为公共卫生关注的问题。法医和验尸官认证了美国境内约20%的所有死亡病例,并且可能是有关传染病死亡信息的关键来源。我们假设一种计算机辅助搜索工具(算法)可以从法医数据库中检测出传染病死亡病例,从而减少手动进行此类监测所需的时间和资源。我们开发了两种算法,将它们应用于一个法医数据库,并根据一组专家的意见对识别出的病例进行了验证。这些算法检测出具有感染成分的死亡病例的敏感度为67%至94%,阳性预测值为8%至49%。算法对于资源有限的法医办公室进行监测或跨法医管辖区域进行监测可能是有用的。