Assessing and Forecasting of Epidemiological Data using Time Series Analysis

The paper gives an overview of time series modeling and forecasting, using multiplicative SARIM Amodels, with application in assessing and forecasting of epidemiological data. After general view of the mainmodels and the methodological issues used in Box-Jenkins approach, the paper presents a case study having assubject the modeling and forecasting of a time series representing the measles infections, in Great Britain, 1971-1994, quarterly recorded, and an example of intervention analysis, using as exogenous data the measles infections,and as endogenous variable the number of vaccinated persons, in the same time period. The intervention analysisproved to be a useful approach to model interrupted time series, when the time series is affected by the effect ofpopulation vaccination.