campyDE: Campylobacteriosis and Absolute Humidity in Germany 2002-2011

In surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Campylobacteriosis and Absolute Humidity in Germany 2002-2011

Description

Weekly number of reported campylobacteriosis cases in Germany, 2002-2011, together with the corresponding absolute humidity (in g/m^3) that week. The absolute humidity was computed according to the procedure by Dengler (1997) using the means of representative weather station data from the German Climate service.

Usage

data(campyDE)

Format

A data.frame containing the following columns

date

Date instance containing the Monday of the reporting week.

case

Number of reported cases that week.

state

Boolean indicating whether there is external knowledge about an outbreak that week

hum

Mean absolute humidity (in g/m^3) of that week as measured by a single representative weather station.

l1.hum-l5.hum

Lagged version (lagged by 1-5) of the hum covariate.

newyears

Boolean indicating whether the reporting week corresponds to the first two weeks of the year (TRUE) or not (FALSE). Note: The first week of a year is here defined as the first reporting week, which has its corresponding Monday within new year.

christmas

Boolean indicating whether the reporting week corresponds to the last two weeks of the year (TRUE) or not (FALSE). Note: This are the first two weeks before the newyears weeks.

O104period

Boolean indicating whether the reporting week corresponds to the W21-W30 period of increased gastroenteritis awareness during the O104:H4 STEC outbreak.

Source

The data on campylobacteriosis cases have been queried from the Survstat@RKI database of the German Robert Koch Institute (https://survstat.rki.de/).

Data for the computation of absolute humidity were obtained from the German Climate Service (Deutscher Wetterdienst), Climate data of Germany, available at https://www.dwd.de.

A complete data description and an analysis of the data can be found in Manitz and Höhle (2013).

References

Manitz, J. and Höhle, M. (2013): Bayesian outbreak detection algorithm for monitoring reported cases of campylobacteriosis in Germany. Biometrical Journal, 55(4), 509-526.

Examples

# Load the data
data("campyDE")

# O104 period is W21-W30 in 2011
stopifnot(all(campyDE$O104period == (
  (campyDE$date >= as.Date("2011-05-23")) &
  (campyDE$date < as.Date("2011-07-31"))
)))

# Make an sts object from the data.frame
cam.sts <- sts(epoch=campyDE$date, observed=campyDE$case, state=campyDE$state)

# Plot the result
plot(cam.sts)

surveillance documentation built on Nov. 4, 2024, 3 a.m.