Center for Advanced Study of Informatics in Public Health, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
J Biomed Inform. 2013 Jun;46(3):444-57. doi: 10.1016/j.jbi.2013.02.003. Epub 2013 Mar 14.
Early detection and accurate characterization of disease outbreaks are important tasks of public health. Infectious diseases that present symptomatically like influenza (SLI), including influenza itself, constitute an important class of diseases that are monitored by public-health epidemiologists. Monitoring emergency department (ED) visits for presentations of SLI could provide an early indication of the presence, extent, and dynamics of such disease in the population. We investigated the use of daily over-the-counter thermometer-sales data to estimate daily ED SLI counts in Allegheny County (AC), Pennsylvania. We found that a simple linear model fits the data well in predicting daily ED SLI counts from daily counts of thermometer sales in AC. These results raise the possibility that this model could be applied, perhaps with adaptation, in other regions of the country, where commonly thermometer sales data are available, but daily ED SLI counts are not.
疾病爆发的早期检测和准确特征描述是公共卫生的重要任务。表现出流感样症状的传染病(SLI),包括流感本身,构成了公共卫生流行病学家监测的重要疾病类别。监测急诊科(ED)就诊的 SLI 表现可以提供有关此类疾病在人群中存在、程度和动态的早期迹象。我们研究了使用日常非处方体温计销售数据来估计宾夕法尼亚州阿勒格尼县(AC)的每日 ED SLI 计数。我们发现,简单的线性模型在从 AC 的体温计销售日常计数预测每日 ED SLI 计数方面拟合数据良好。这些结果表明,该模型可能适用于其他地区,在这些地区,通常可以获得体温计销售数据,但不存在每日 ED SLI 计数。