Determine the short term trend of a surveillance time series

Fits a quasi-Poisson regression over a moving window of recent observations of a surveillance sts object. It sets the alarm slot to 1 for time points with a significant increasing trend, and to 0 otherwise. The method is based upon a published analytics strategy by Benedetti (2019) <doi:10.5588/pha.19.0002>. This function was frozen on 2024-06-24 and operates on sts objects.

Usage

short_term_trend_sts_v1(sts, control = list(w = 5, alpha = 0.05))

Arguments

sts

Data object of type sts.

control

Control object, a named list with several elements.

w

Length of the window that is being analyzed.

alpha

Significance level for change in trend.

Value

sts object with the alarms slot set to 0/1 if not-increasing/increasing.

See also

Neither package vignette covers this function. It is the surveillance::sts form of the deprecated `csfmt_rts_data_v1` trend method of short_term_trend, whose help page carries the only worked example of that method.

Examples

d <- cstidy::nor_covid19_icu_and_hospitalization_csfmt_rts_v1
d <- d[granularity_time=="isoyearweek"]
sts <- surveillance::sts(
  observed = d$hospitalization_with_covid19_as_primary_cause_n, # weekly number of cases
  start = c(d$isoyear[1], d$isoweek[1]), # first week of the time series
  frequency = 52
)
x <- csalert::short_term_trend_sts_v1(
  sts,
  control = list(
    w = 5,
    alpha = 0.05
  )
)
plot(x)