The use of a CUSUM residual chart to monitor respiratory syndromic data

Abstract

This article reports a surveillance mechanism that can be used to monitor syndromic data on respiratory syndrome. The data used for illustration are the daily counts of respiratory-syndrome visits sampled from the National Health Insurance Research Database in Taiwan. The population size is 160 000. A regression model with an autoregressive-integrated-moving-average error term is fitted to the data and then CUmulative SUM (CUSUM) residual charts are plotted to detect aberrations in the frequency of visits to a walk in clinic. Day-of-the-week, seasonal, and holiday effects are considered in the regression model. It is shown that a CUSUM residual chart can be used to detect abnormal increases in daily counts of respiratory-syndrome visits.

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