[Construction and application of joinpoint regression model for series cumulative data].

作者：Siqing Zeng · 发表于：PubMed · 年份：2019 · DOI：10.3760/cma.j.issn.0253-9624.2019.10.024 · 被引用次数：8 · 研究领域：Data-Driven Disease Surveillance、Viral Infections and Outbreaks Research、Viral Infections and Vectors

Based on the principle of Joinpoint regression (JPR) model and the additivity of Poisson distribution, this paper constructed a JPR model for series cumulative data. The notifiable incidence number of dengue fever cases per week and weekly cumulative data in Guangdong province from 2008 to 2017 were analyzed, using (mean squared errors) MSE and (mean absolute percentage error) MAPE to evaluate different models. Except for 2015, the MSE and MAPE produced from the logarithmic linear JPR model based on weekly cumulative incidence number were smaller than those based on the weekly data. The fitting accuracy of JPR model for series cumulative data for trend analysis had been improved significantly. This model could be applied to the analysis of the trend change and the prediction of staged cumulative incidence.