Surveillance using the CDC Algorithm
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disProgObj 
object of class disProg (including the observed and the state chain). 
timePoint 
time point which shoud be evaluated in 
control 
control object: 
Using the reference values for calculating an upper limit, alarm is
given if the actual value is bigger than a computed threshold.
algo.cdc
calls algo.cdcLatestTimepoint
for the values
specified in range
and for the system specified in
control
. The threshold is calculated from the predictive
distribution, i.e.
mean(x) + z_{α/2} * sd(x) * √(1+1/k),
which corresponds to Equation 81 in Farrington and Andrews (2003).
Note that an aggregation into 4week blocks occurs in
algo.cdcLatestTimepoint
and m
denotes number of 4week
blocks (months) to use as reference values. This function currently
does the same for monthly data (not correct!)
survRes 

M. Höhle
Stroup, D., G. Williamson, J. Herndon, and J. Karon (1989). Detection of aberrations in the occurence of notifiable diseases surveillance data. Statistics in Medicine 8, 323329.
Farrington, C. and N. Andrews (2003). Monitoring the Health of Populations, Chapter Outbreak Detection: Application to Infectious Disease Surveillance, pp. 203231. Oxford University Press.
algo.rkiLatestTimepoint
,algo.bayesLatestTimepoint
and algo.bayes
for
the Bayes system.
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