Time Series Analysis with Application in Public Health and Biomedical Data

Abstract

The paper gives a overview of time series modeling and forecasting, using multiplicative SARIMA models, with application in assessing and forecasting of epidemiological data. After presenting of the main models and the methodological issues used in Box-Jenkins approach, the paper presents two case studies having as subject the modeling and forecasting of the cumulative number of individuals infected with severe acute respiratory syndrome, or SARS, in Singapore, from 24 February to 7 May 2003, and the measles infections, in Great Britain, 1971-1994, quarterly recorded. For the last series an example of intervention analysis, using as the exogenous data the measles infections, and as endogenous variable the number of vaccinated persons, in the same time period, is presented, proved to be a useful approach, when the time series is affected by the effect of population vaccination.