mem (version 1.2)

epimem: Threshold for Influenza Epidemic

Description

Function epimem is used to calculate the threshold for influenza epidemic using historical records (surveillance rates). The method to calculate the threshold is described in the Moving Epidemics Method (MEM) used to monitor influenza activity in a weekly surveillance system.

Usage

epimem(i.data, i.type = 2, i.level = 0.95, i.type.curve = 2, i.level.curve = 0.95, i.type.threshold = 5, i.level.threshold = 0.95, i.n.max = -1, i.tails = 1, i.type.boot = "norm", i.iter.boot = 10000, i.method = 2, i.param = 2.8, i.levels = c(0.40,0.90,0.975), i.seasons = 10)
## S3 method for class 'flu':
print(x, ...)
## S3 method for class 'flu':
summary(object, ...)
## S3 method for class 'flu':
plot(x, ...)

Arguments

i.data

Matrix of input data.

i.type

Type of confidence interval (general).

i.level

Level of confidence interval (general).

i.type.curve

Type of confidence interval (to calculate the modelled curve).

i.level.curve

Level of confidence interval (to calculate the modelled curve).

i.type.threshold

Type of confidence interval (to calculate the threshold).

i.level.threshold

Level of confidence interval (to calculate the threshold).

i.n.max

Number of pre-epidemic values used to calculate the threshold.

i.tails

Tails for the confidence interval to calculate the threshold.

i.type.boot

Type of bootstrap technique.

i.iter.boot

Number of bootstrap iterations.

i.method

Method to calculate the optimal timing of the epidemic.

i.param

Parameter to calculate the optimal timing of the epidemic.

i.levels

Levels of the intensity thresholds.

i.seasons

Maximum number of seasons to use.

x

An flu class item.

object

An flu class item.

...

Not used.

Value

• epimem returns an object of class flu. An object of class flu is a list containing at least the following components:
• i.data
  input data
• pre.post.intervals
  Pre/post confidence intervals (Threhold is the upper limit of the confidence interval).
• ci.length
  Mean epidemic length confidence interval.
• ci.percent
  Mean covered percentage confidence interval.
• mean.length
  Mean length.
• moving.epidemics
  Moving epidemic rates.
• mean.start
  Mean epidemic start.
• epi.intervals
  Epidemic levels of intensity.
• typ.curve
  Typical epidemic curve.
• n.max
  Effective number of pre epidemic values.

Details

Input data is a matrix containing rates that represent historical influenza surveillance data. It can start and end at any given week (tipically at week 40th), and rates can be expressed as per 100,000 inhabitants (or per consultations, if population is not available) or any other scale. Parameters i.type, i.type.threshold and i.type.curve defines how to calculate confidence intervals along the process. i.type.curve is used for calculating the typical influenza curve, i.type.threshold is used to calculate the pre and post epidemic threshold and i.type is used for any other confidende interval used in the method. All three parameters must be a number between 1 and 6: rlll{ 1 Arithmetic mean and mean confidence interval. 2 Geometric mean and mean confidence interval. 3 Median and the KC Method to calculate its confidence interval. 4 Median and bootstrap confidence interval. 5 Arithmetic mean and point confidence interval (standard deviations). 6 Geometric mean and point confidence interval (standard deviations). } Option 4 uses two more parameters: i.type.boot indicates which bootstrap method to use. The values are the same of those of the boot.ci function. Parameter i.iter.boot indicates the number of bootstrap samples to use. See boot for more information about this topic. Parameters i.level, i.level.threshold and i.level.curve indicates, respectively, the level of the confidence intervals described above. The i.n.max parameter indicates how many pre epidemic values to use to calculate the threshold. A value of -1 indicates the program to use an appropiate number of points depending on the number of seasons provided as input. i.tails tells the program to use {1} or {2} tailed confidence intervals when calculating the threshold (1 is recommended). Parameters i.method and i.param indicates how to find the optimal timing of the epidemics. See epitiming for details on the values this parameters can have.

References

Vega T., Lozano J.E. (2004) Modelling influenza epidemic - can we detect the beginning and predict the intensity and duration? International Congress Series 1263 (2004) 281-283. Vega T., Lozano J.E. (2012) Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method. Influenza and Other Respiratory Viruses, DOI:10.1111/j.1750-2659.2012.00422.x.

Examples

library(mem)

## Castilla y Leon Influenza Rates data 
data(flucyl)
## Finds the timing of the first season: 2001/2002
epi<-epimem(flucyl)
print(epi)
summary(epi)
plot(epi)