Multivariate surveillance is of interest in many areas such as industrial production, bioterrorism detection, spatial surveillance, and financial transaction strategies. Some of the suggested approaches to multivariate surveillance have been multivariate counterparts to the univariate Shewhart,...

The spatial aspects on the Swedish influenza data are analyzed. During the influenza period, reports on laboratory diagnosed cases and influenza-like-illness are obtained from viral and microbiological laboratories and from sentinel physicians, respectively, in different regions of Sweden....

We describe and discuss statistical models of Swedish influenza data, with special focus on aspects which are important in on-line monitoring. Earlier suggested statistical models are reviewed and the possibility of using them to describe the variation in influenza-like illness (ILI) and...

The detection of a change from a constant level to a monotonically increasing (or decreasing) regression is of special interest for the detection of outbreaks of, for example, epidemics. A maximum likelihood ratio statistic for the sequential surveillance of an “outbreak” situation is...

The aim of this report is to describe if and how statistical surveillance methods for monitoring of the performance of fund managers has been used. Statistical surveillance is a methodology for on-line monitoring, in which a warning signal is given if the performance declines. Since these...

Heckman’s two-step procedure (Heckit) for estimating the parameters in linear models from censored data is frequently used by econometricians, despite of the fact that earlier studies cast doubt on the procedure. In this paper it is shown that estimates of the hazard h for approaching the...

Outbreak detection is of interest for several diseases and syndromes. The aim is to detect the progressing increase in the incidence as soon as possible after the onset of the outbreak. A semiparametric method is applied to Swedish data on tularemia and influenza. The method is constructed to...

In many situations we need a system for detecting changes early. Examples are early detection of disease outbreaks, of patients at risk and of financial instability. In influenza outbreaks, for example, we want to detect an increase in the number of cases. Important indicators might be the...

The aim of sequential surveillance is on-line detection of an important change in an underlying process as soon as possible after the change has occurred. Statistical methods suitable for surveillance differ from hypothesis testing methods. In addition, the criteria for optimality differ from...