Univariate and Multivariate Surveillance of Outbreaks

In many areas there is a need to monitor observations in order to detect changes in the underlying processes as quickly as possible. The theory of statistical surveillance provides the possibility of making optimal decisions about whether a change has occurred or not based on the data available at t...

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Bibliographic Details
Main Authors: Skriftserie Publications, Linus Schiöler
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.1562
http://www.hgu.gu.se/Files/nationalekonomi/Sem/101125%20Schi%C3%B6ler%20avh2.pdf
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Summary:In many areas there is a need to monitor observations in order to detect changes in the underlying processes as quickly as possible. The theory of statistical surveillance provides the possibility of making optimal decisions about whether a change has occurred or not based on the data available at the time of the decision. Surveillance can be used in many different situations. It is important that the relevant characteristics of the change are identified and that the relevant optimality criterion is used. There is a need to further develop the theory of statistical surveillance. One area where surveillance is of special interest is the detection of outbreaks of epidemic diseases. New strains of influenza virus like avian flu and swine flu have drawn much attention, but it is also important to detect the varying onset of the seasonal influenza. Outbreaks are characterized by a change from a constant incidence to an increasing one. A quick and reliable detection of epidemic outbreaks can be beneficial to society as it has the potential to prevent loss of lives and severe economic consequences. The detection of a change from a constant level to a monotonically increasing (or decreasing) regression is of interest also in other areas, for example in finance. This thesis considers outbreak detection in