BACKGROUND Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable...

Implicit in the idea of medical audit are two notions: the quantifying of medical practice in terms of treatment, procedures, outcomes, and complications; and the use of these data to exact some form of accountability. Therefore some sort of objective monitoring, or quality control, of practices or procedures is needed so that periods of suboptimal performance in relation to an agreed standard ...

The concepts of Bernoulli numbers B n , Bernoulli polynomials B n (x), and the generalized Bernoulli numbers B n (a, b) are generalized to the one B n (x; a, b, c) which is called the generalized Bernoulli polynomials depending on three positive real parameters. Numerous properties of these polynomials and some relationships between B n , B n (x), B n (a, b), and B n (x; a, b, c) are established.

Control charts are widely used for process monitoring. They show whether the variation is due to common causes or whether some of the variation is due to special causes. To detect large shifts in the process, Shewhart-type control charts are preferred. Cumulative sum (CUSUM) and exponentially weightedmoving average (EWMA) control charts are generally used to detect small and moderate shifts. Sh...

The input-output delay of a process is an important parameter for control design and closed-loop identification. This paper proposes new methods for estimating the delay of a transfer function model in closed-loop based on statistical change-point detection methods. A Bayesian change-point approach, a sequential probability ratio test (SPRT), and a cumulative sum (CUSUM) approach are proposed a...

This paper deals with phase II, univariate, statistical process control when a set of incontrol data is available, and when both the in-control and out-of-control distributions of the process are unknown. Existing process control techniques typically require substantial knowledge about the in-control and out-of-control distributions of the process, which is often difficult to obtain in practice...

Time series segmentation, a.k.a. multiple change-point detection, is a well-established problem. However, few solutions are designed specifically for high-dimensional situations. In this paper, our interest is in segmenting the second-order structure of a high-dimensional time series. In a generic step of a binary segmentation algorithm for multivariate time series, one natural solution is to c...

BACKGROUND Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illne...