A One-Sided MEWMA Chart for Health Surveillance

Abstract

It is often important to rapidly detect an increase in the incidence rate of a given disease or other medical condition. It has been shown that when disease counts are sequentially available from a single region, a univariate control chart designed to detect rate increases, such as a one-sided cumulative sum chart, is very effective. When disease counts are available from several regions at corresponding times, the most efficient monitoring method is not readily apparent. Multivariate monitoring methods have been suggested for dealing with this detection problem. Some of these approaches have shortcomings that have been recently demonstrated in the quality control literature. We discuss these limitations and suggest an alternative multivariate exponentially weighted moving average chart. We compare the average run-length performance of this chart with that of competing methods. We also evaluate the statistical performance of these charts when the actual increase in the disease count rate is different from the one that the chart was optimized to detect quickly. Copyright © 2008 John Wiley & Sons, Ltd.