Modeling and Forecasting of Air Quality Impact on Mortality Rates - A Case Study

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Abstract: The paper has as subject the modeling and forecasting of air quality impact on mortality rates, and present a case study, making use of time series analysis approach. After a general view on the time series models, regression and intervention models, to be used in modeling and forecasting of mortality, function of air quality, some methodological aspects of time series modeling and forecasting, based on Box-Jenkins methodology, are discussed with the emphasis on practical aspects. Finally, a case study using a multiplicative transfer function model with three exogenous variable representing ozone, daily average computed for the region, particulate matter 10 micrometers or less in diameter, daily average, and temperature mean, daily average, considered as risk factors, with the effect on mortality rate, as endogenous variable, is presented.

WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 18, 2019, Art. #19

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Theodor D. Popescu, "Modeling and Forecasting of Air Quality Impact on Mortality Rates - A Case Study," WSEAS Transactions on Systems, vol. 18, pp. 149-155, 2019, DOI:
Theodor D. Popescu. Modeling and Forecasting of Air Quality Impact on Mortality Rates - A Case Study. WSEAS Transactions on Systems. 2019;18:149-155.
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