TY - RPRT
T1 - Monitoring Poisson time series using multi-process models
AU - Engebjerg, Malene Dahl Skov
AU - Lundbye-Christensen, Søren
AU - Kjær, Birgitte B.
AU - Schønheyder, Henrik Carl
PY - 2006/3
Y1 - 2006/3
N2 - Surveillance of infectious diseases based on routinely collected public health data
is important for at least three reasons: The early detection of an epidemic may facilitate prompt
interventions and the seasonal variations and long term trend may be of general epidemiological
interest. Furthermore aspects of health resource management may also be addressed.
In this paper we center on the detection of outbreaks of infectious diseases. This is achieved
by a multi-process Poisson state space model taking autocorrelation and overdispersion into
account, which has been applied to a data set concerningMycoplasma pneumoniae infections.
AB - Surveillance of infectious diseases based on routinely collected public health data
is important for at least three reasons: The early detection of an epidemic may facilitate prompt
interventions and the seasonal variations and long term trend may be of general epidemiological
interest. Furthermore aspects of health resource management may also be addressed.
In this paper we center on the detection of outbreaks of infectious diseases. This is achieved
by a multi-process Poisson state space model taking autocorrelation and overdispersion into
account, which has been applied to a data set concerningMycoplasma pneumoniae infections.
M3 - Report
T3 - Research Report Series
BT - Monitoring Poisson time series using multi-process models
PB - Department of Mathematical Sciences, Aalborg University
CY - Aalborg
ER -