memsurveillance.animated function

Creates the animated graph of the surveillance of the current season

Function memsurveillance.animated creates an animated surveillance graph for the current season.

memsurveillance.animated(
  i.current,
  i.epidemic.thresholds = NA,
  i.intensity.thresholds = NA,
  i.output = ".",
  i.animated.graph.file = T,
  i.animated.graph.file.name = "animated",
  i.fps = 2,
  i.loop = 0,
  i.remove = T,
  ...
)

Arguments

• i.current: Current season weekly rates.
• i.epidemic.thresholds: Pre and post epidemic threholds.
• i.intensity.thresholds: Intensity thresholds.
• i.output: Directory where graph is saved.
• i.animated.graph.file: If a animated gif should be produced, or just the intermediate graphics
• i.animated.graph.file.name: Name of the animated graph.
• i.fps: Number of frames per second of the animated gif.
• i.loop: Number of loops for the animated dif, 0 for Infinite.
• i.remove: Remove partial graphs.
• ...: Additional parameters parsed to memsurveillance.

Returns

memsurveillance.animated writes a gif graph of the surveillance of this season.

Details

Input data must be the current season and an object of class mem. The output graph contains the weekly rates series along with the epidemic and intensity threshols located at the exact situation where the epidemic started. If there is no epidemic yet, only the epidemic threshold is placed.

See memsurveillance for more details

Examples

# Castilla y Leon Influenza Rates data
data(flucyl)
# Data of the last season
cur <- flucyl[8]
# The model
epi <- memmodel(flucyl[1:7])
# Epidemic thresholds
e.thr <- epi$epidemic.thresholds
# Intensity threhsolds
i.thr <- epi$intensity.thresholds
# Set the working directory to whererever you want to store the graph file
setwd(".")
# uncomment to execute
# m1 <- memsurveillance.animated(cur,
#    i.animated.graph.file.name = "Animated",
#    i.epidemic.thresholds = e.thr, i.intensity.thresholds = i.thr, i.pos.epidemic = TRUE,
#    i.animated.graph.file = FALSE
# )

References

Vega T, Lozano JE, Ortiz de Lejarazu R, Gutierrez Perez M. Modelling influenza epidemic - can we detect the beginning and predict the intensity and duration? Int Congr Ser. 2004 Jun;1263:281-3.

Vega T, Lozano JE, Meerhoff T, Snacken R, Mott J, Ortiz de Lejarazu R, et al. Influenza surveillance in Europe: establishing epidemic thresholds by the moving epidemic method. Influenza Other Respir Viruses. 2013 Jul;7(4):546-58. DOI:10.1111/j.1750-2659.2012.00422.x.

Vega T, Lozano JE, Meerhoff T, Snacken R, Beaute J, Jorgensen P, et al. Influenza surveillance in Europe: comparing intensity levels calculated using the moving epidemic method. Influenza Other Respir Viruses. 2015 Sep;9(5):234-46. DOI:10.1111/irv.12330.

Lozano JE. lozalojo/mem: Second release of the MEM R library. Zenodo [Internet]. [cited 2017 Feb 1]; Available from: https://zenodo.org/record/165983. DOI:10.5281/zenodo.165983

Author(s)

Jose E. Lozano lozalojo@gmail.com