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.
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 flu
print(x, ...)
# S3 method for flu
summary(object, ...)
# S3 method for flu
plot(x, ...)Data frame of input data.
Type of confidence interval (general).
Level of confidence interval (general).
Type of confidence interval (to calculate the modelled curve).
Level of confidence interval (to calculate the modelled curve).
Type of confidence interval (to calculate the threshold).
Level of confidence interval (to calculate the threshold).
Number of pre-epidemic values used to calculate the threshold.
Tails for the confidence interval to calculate the threshold.
Type of bootstrap technique.
Number of bootstrap iterations.
Method to calculate the optimal timing of the epidemic.
Parameter to calculate the optimal timing of the epidemic.
Levels of the intensity thresholds.
Maximum number of seasons to use.
An flu class item.
An flu class item.
Not used.
epimem returns an object of class flu.
An object of class flu is a list containing at least the following components:
input data
Pre/post confidence intervals (Threhold is the upper limit of the confidence interval).
Mean epidemic length confidence interval.
Mean covered percentage confidence interval.
Mean length.
Moving epidemic rates.
Mean epidemic start.
Epidemic levels of intensity.
Typical epidemic curve.
Effective number of pre epidemic values.
Input data is a data frame 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:
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). | 1 |
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.
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.
## 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)
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