meningitis {spatstat.data} | R Documentation |
Invasive Meningococcal Disease Cases in Germany
Description
Spatial locations of cases of invasive meningococcal disease in Germany, and information on the population density.
Usage
data(meningitis)
Format
meningitis
is a list (of class "solist"
)
containing two entries,
-
cases
: a multitype point pattern (object of class"ppp"
) giving the spatial location of each case. Points are classified into types B and C according to the serotype for each case. -
kreise
: a tessellation (object of class"tess"
) giving the division of Germany into administrative districts (Kreise). Tiles are marked with a numeric estimate of the average population density.
Details
These data give the spatial locations of 636 cases of invasive meningococcal disease in Germany, together with information on the division of Germany into administrative districts, and estimates of population density in each district.
The data were extracted from the dataset imdepi
in the package
surveillance. They have been simplified and converted to
spatstat format.
The original data were analysed by
Meyer, Elias and Hoehle (2012).
The simplified data provided here were analysed in Baddeley, Davies and Hazelton (2025).
The dataset meningitis
is a list (of class "solist"
)
containing two elements, cases
and kreise
.
The first element cases
is a spatial point pattern
(object of class "ppp"
) containing 636 points giving the
locations of the cases. This is a multitype point pattern, that is,
it has marks which are categorical values, classifying each
point into type B or C, according to the serotype of each case.
According to the surveillance documentation, these data are from
cases caused by the two most common meningococcal finetypes in
Germany, ‘B:P1.7-2,4:F1-5’
(of serogroup B) and ‘C:P1.5,2:F3-3’ (of serogroup C).
The observation window for the point pattern is a polygonal
representation of the national border of Germany. Coordinates are
given in kilometres.
The second element kreise
is a tessellation (object of class
"tess"
) giving the division of Germany into administrative
districts. Each tile of the tessellation is marked by a numerical value
which is an estimate of the average population density (people per
square kilometre) in the district.
Source
Obtained from package surveillance.
IMD case reports: German Reference Centre for Meningococci at the Department of Hygiene and Microbiology, Julius-Maximilians-Universitaet Universitaet Wuerzburg, Germany (https://www.hygiene.uni-wuerzburg.de/meningococcus/). Thanks to Dr. Johannes Elias and Prof. Dr. Ulrich Vogel for providing the data.
Shapefile of Germany's districts as at 2009-01-01: German Federal Agency for Cartography and Geodesy, Frankfurt am Main, Germany, <https://gdz.bkg.bund.de/>.
References
Meyer, S., Elias, J. and Hoehle, M. (2012): A space-time conditional intensity model for invasive meningococcal disease occurrence. Biometrics, 68, 607–616. doi:10.1111/j.1541-0420.2011.01684.x
Baddeley, A., Davies, T.M. and Hazelton, M.L. (2025) An improved estimator of the pair correlation function of a spatial point process. Biometrika, to appear.
Examples
if(require(spatstat.geom)) {
plot(meningitis$cases)
plot(meningitis$kreise, do.col=TRUE, col=grey(seq(1, 0, length=32)))
## count cases in each district
qc <- with(meningitis, quadratcount(cases, tess=kreise))
}