baseSA {flubase}R Documentation

Baseline free of influenza epidemic effects: non iterative procedure with seasonal ARIMA model

Description

This function estimates the mortality (or other indicator) baseline, free of influenza epidemics, using a non iterative procedure. The baseline is estimated from a seasonal ARIMA model fitted to the mortality time series without the epidemic periods. The periods with excess deaths associated to influenza epidemics are those periods, within the epidemic ones, where the observed mortality is above the 95 CI of fitted model.

Usage

baseSA(nod, todeath, epi, flu_year, ny, tb, te, pe, per)

Arguments

nod a vector with the number of deaths (or other indicator) by week or month
todeath a vector that contains the time index (week or month number)
epi a vector that indicates if the week or month belongs to the epidemic period, in which case epi=1. Otherwise, epi=0
flu_year a vector that indicates the flu year. It is an index for the set of 52 weeks or 12 months, that initiate at week 27 and ends at week 26 of the next civil year, or iniate at month 7 and ends at month 6 of the next civil year, depending on the time unit of data.
ny number of years in study
tb initial week (tb=48) or month (tb=12) of the fixed epidemic period
te final week (te=17) or month (te=4) of the fixed epidemic period
pe pe = 0 if the user provides the epidemic periods in the epi parameter; otherwise if pe = 1 the function uses a fixed period from week 47 to week 17 or from month 12 to month 4.
per per=52 if the data is weekly or per=12 if the data is monthly

Details

The objective of this function is to estimate a mortality baseline without the effect of influenza epidemics. With this purpose the function fits a cyclical regression model to the mortality time series after excluding the epidemic periods, i.e. the values of nod corresponding to epi=0. Then the function replaces the nod values where epi=1 by the model estimates. In the next step it fits to this new time series the seasonal ARIMA model using the auto.arima function of the forecast package. The fitted values from this new model is the mortality baseline without the effect of influenza epidemics. The function also returns the the periods with excess mortality associated to influenza epidemics, as those where the observed mortality initiate with two consecutive observations above the 95 CI of the baseline and ends with two observations bellow the 95 CI of the baseline. These periods are returned in da variable.

Value

The function will return a list

baseSA$beta0 containing the estimated mortality (or other indicator) baseline without the effect of influenza epidemics
baseSA$beta_up containg the upper 95 CI of the baseline
baseSA$da a dummy variable indicating the periods with excess deaths associated with the ocurred influenza epidemics

Note

This function needs at least 5 years data to give reliable results

Author(s)

Nunes B, Natario I and Carvalho L.

References

Nunes B, Natario I, Carvalho L. Time series methods for obtaining excess mortality. Submitted to Statistical Methods in Medical Research (2009).

Serfling RE Methods for Current Statistical Analysis of Excess Mortality Pneumonia-Influenza Deaths Public Heath Reports 1963; 78 6:494 506.

See Also

baseRM,baseIt_RM,baseIt_SA, flubase


[Package flubase version 1.0 Index]