spatstat.data (version 3.1-6)

meningitis: 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.

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))
   }