hagelloch: 1861 Measles Epidemic in the City of Hagelloch, Germany

Description

Data on the 188 cases in the measles outbreak among children in the German city of Hagelloch (near T�{ue}bingen) 1861. The data were originally collected by Dr. Albert Pfeilsticker (1863) and augmented and re-analysed by Dr. Heike Oesterle (1992).

Usage

data("hagelloch")

Arguments

encoding

latin1

source

Thanks to Peter J. Neal, University of Manchester, for providing us with these data, which he again became from Niels Becker, Australian National University. To cite the data, the main references are Pfeilsticker (1863) and Oesterle (1992).

References

Pfeilsticker, A. (1863). Beitr�{ae}ge zur Pathologie der Masern mit besonderer Ber�{ue}cksichtigung der statistischen Verh�{ae}ltnisse, M.D. Thesis, Eberhard-Karls-Universit�{ae}t T�{ue}bingen. Available as http://www.archive.org/details/beitrgezurpatho00pfeigoog. Oesterle, H. (1992). Statistische Reanalyse einer Masernepidemie 1861 in Hagelloch, M.D. Thesis, Eberhard-Karls-Universit�{ae}at T�{ue}bingen.

Neal, P. J. and Roberts, G. O (2004). Statistical inference and model selection for the 1861 Hagelloch measles epidemic, Biostatistics 5(2):249-261

Examples

Run this code

data("hagelloch")

head(hagelloch.df)   # original data documented in Oesterle (1992)
head(as.data.frame(hagelloch))   # derived "epidata" object


### How the "epidata" 'hagelloch' was created from 'hagelloch.df'

stopifnot(all.equal(hagelloch,
  as.epidata(
    hagelloch.df, t0 = 0, tI.col = "tI", tR.col = "tR",
    id.col = "PN", coords.cols = c("x.loc", "y.loc"),
    f = list(
        household    = function(u) u == 0,
        nothousehold = function(u) u > 0
    ),
    w = list(
        c1 = function (CL.i, CL.j) CL.i == "1st class" & CL.j == CL.i,
        c2 = function (CL.i, CL.j) CL.i == "2nd class" & CL.j == CL.i
    ),
    keep.cols = c("SEX", "AGE", "CL"))
))


### Basic plots produced from hagelloch.df

# Show case locations as in Neal & Roberts (different scaling) using
# the data.frame (promoted to a SpatialPointsDataFrame)
coordinates(hagelloch.df) <- c("x.loc","y.loc")
plot(hagelloch.df, xlab="x [m]", ylab="x [m]", pch=15, axes=TRUE,
     cex=sqrt(multiplicity(hagelloch.df)))

# Epicurve
hist(as.numeric(hagelloch.df$tI), xlab="Time (days)", ylab="Cases", main="")


### SIR model information for population & individuals

(s <- summary(hagelloch))
plot(s, col=c("green","red","darkgray"))
stateplot(s, id=c("187"))

# Show a dynamic illustration of the spread of the infection
  animate(hagelloch,time.spacing=0.1,legend.opts=list(x="topleft"),sleep=1/100)

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