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AUTHOR(S): Theodor D. Popescu, Adriana Alexandru, Marilena Ianculescu
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TITLE Assessing and Forecasting of Epidemiological Data using Time Series Analysis |
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ABSTRACT The paper gives an overview of time series modeling and forecasting, using multiplicative SARIMA models, with application in assessing and forecasting of epidemiological data. After general view of the main models and the methodological issues used in Box-Jenkins approach, the paper presents a case study having as subject 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 analysis proved to be a useful approach to model interrupted time series, when the time series is affected by the effect of population vaccination. |
KEYWORDS Time series analysis, modeling, forecasting, intervention analysis, Box-Jenkins approach, epidemiological data, case study |
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Cite this paper Theodor D. Popescu, Adriana Alexandru, Marilena Ianculescu. (2019) Assessing and Forecasting of Epidemiological Data using Time Series Analysis. International Journal of Mathematical and Computational Methods, 4, 37-42 |
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