aedseo {aedseo} | R Documentation |
This function performs automated and early detection of seasonal epidemic onsets (aedseo) on a time series dataset. It estimates growth rates for consecutive time intervals and calculates the sum of cases (sum_of_cases).
aedseo(
tsd,
k = 5,
level = 0.95,
disease_threshold = NA_integer_,
family = c("poisson", "quasipoisson")
)
tsd |
A |
k |
An integer specifying the window size for modeling growth rates. |
level |
The confidence level for parameter estimates, a numeric value between 0 and 1. |
disease_threshold |
An integer specifying the threshold for considering a disease outbreak. |
family |
A character string specifying the family for modeling. Choose between "poisson," or "quasipoisson". |
A aedseo
object containing:
'reference_time': The time point for which the growth rate is estimated.
'observed': The observed value in the reference time point.
'growth_rate': The estimated growth rate.
'lower_growth_rate': The lower bound of the growth rate's confidence interval.
'upper_growth_rate': The upper bound of the growth rate's confidence interval.
'growth_warning': Logical. Is the growth rate significantly higher than zero?
'sum_of_cases': The sum of cases within the time window.
'sum_of_cases_warning': Logical. Does the Sum of Cases exceed the disease threshold?
'seasonal_onset_alarm': Logical. Is there a seasonal onset alarm?
'converged': Logical. Was the IWLS judged to have converged?
# Create a tsibble object from sample data
tsd_data <- tsd(
observed = c(100, 120, 150, 180, 220, 270),
time = as.Date(c(
"2023-01-01",
"2023-01-02",
"2023-01-03",
"2023-01-04",
"2023-01-05",
"2023-01-06"
)),
time_interval = "day"
)
# Calculate AEDSEO with a 3-day window and a Poisson family model
aedseo_results <- aedseo(
tsd = tsd_data,
k = 3,
level = 0.95,
disease_threshold = 200,
family = "poisson"
)
# Print the AEDSEO results
print(aedseo_results)