Several methods have been proposed in open literatures for detecting changes in disease outbreak or incidence. Most of these methods are likelihood-based as well as the direct application of Shewhart, CUSUM and EWMA schemes. We use CUSUM, EWMA and EWMA-CUSUM multi-chart schemes to detect changes in disease incidence. Multi-chart is a combination of several single charts that detects changes in a process and have been shown to have elegant properties in the sense that they are fast in detecting changes in a process as well as being computationally less expensive. Simulation results show that the multi-CUSUM chart is faster than EWMA and EWMA-CUSUM multi-charts in detecting shifts in the rate parameter. A real illustration with health data is used to demonstrate the efficiency of the schemes.

中文翻译：

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用于检测疾病发病率变化的多图表方案。

在公开文献中已经提出了几种方法来检测疾病暴发或发病率的变化。这些方法大多数都是基于似然性的，以及Shewhart，CUSUM和EWMA方案的直接应用。我们使用CUSUM，EWMA和EWMA-CUSUM多图表方案来检测疾病发病率的变化。多重图表是检测过程变化的几个单个图表的组合，从某种意义上说，它们具有优雅的性能，因为它们可以快速检测过程中的变化并且在计算上更便宜。仿真结果表明，在检测速率参数变化时，multi-CUSUM图比EWMA和EWMA-CUSUM多图更快。带有健康数据的真实插图用于证明该方案的有效性。