Spatial surveillance is a special case of multivariate surveillance. Thus, in this review of spatial outbreak methods, the relation to general multivariate surveillance approaches is discussed. Different outbreak models are needed for different public health applications. We will discuss methods...

Markov chains (MCs) have been used to study how the health states of patients are progressing in time. With few exceptions the studies have been based on the questionable assumptions that the MC has order m=1 and is homogeneous in time. In this paper a three-state non-homogeneous MC model is...

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,...

Robust regression is of interest in many problems where assumptions of a parametric function may be inadequate. In this thesis, we study regression problems where the assumptions concern only whether the curve is increasing or decreasing. Examples in economics and public health are given. In a...

Information about the spatial spread of epidemics can be useful for many purposes. In this paper, the spatial aspect of Swedish influenza data is analyzed with the main aim of finding patterns that could be useful for statistical surveillance of the outbreak, i.e. for detecting an increase in...

A regression may be constant for small values of the independent variable (for example time), but then a monotonic increase starts. Such an “outbreak” regression is of interest for example in the study of the outbreak of an epidemic disease. We give the least square estimators for this...

The volatility of asset returns are important in finance. Different likelihood based methods of statistical surveillance for detecting a change in the variance are evaluated. The differences are how the partial likelihood ratios are weighted. The full likelihood ratio, Shiryaev-Roberts, Shewhart...

A statistical surveillance system gives a signal as soon as data give enough evidence of an important event. We consider on-line surveillance systems for detecting changes in influenza incidence. One important feature of the influenza cycle is the start of the influenza season, and another one...

Outbreaks, defined as changes from a constant level to a monotonic trend, are of interest in connection with epidemic diseases but also in financial and other contexts. It is important to detect the onset of the outbreak as soon as possible to allow timely action to be taken. New observations...