Description Usage Arguments Details Value Author(s) Source See Also Examples
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 8-1 in Farrington and Andrews (2003).
Note that an aggregation into 4-week blocks occurs in
algo.cdcLatestTimepoint
and m
denotes number of 4-week
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, 323-329.
Farrington, C. and N. Andrews (2003). Monitoring the Health of Populations, Chapter Outbreak Detection: Application to Infectious Disease Surveillance, pp. 203-231. Oxford University Press.
algo.rkiLatestTimepoint
,algo.bayesLatestTimepoint
and algo.bayes
for
the Bayes system.
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