Abstract
This work presents a specific implementation of the Allard approach to the epidemiological time series analysis by ARIMA and SARIMA modeling, intended to describe and predict the epidemic behavior of Varicella in the city of Bogotá D.C. (Colombia). Model selection and preliminary forecast evaluation supported on the official accounts of Varicella incidence rate are performed and reported for the interval 2010–2015. This approach yields a SARMA(3,0,1)(1,0,1) model, whose forecasting results were evaluated against real data of the year 2016. Performance comparison with alternative models and their potential use in the support of epidemic surveillance are also discussed.
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Notes
- 1.
Colombian National Institute of Health http://ins.minsalud.gov.co.
- 2.
Sistema Nacional de Vigilancia Epidemiológica (SIVIGILA) http://www.ins.gov.co/lineas-de-accion/Subdireccion-Vigilancia/sivigila/Paginas/sivigila.aspx.
- 3.
The quotient of the new confirmed cases of disease in a particular location during an epidemiological week, divided by its total population.
- 4.
This is the interval \(\left[ -2/T, 2/T\right] \) where T is the time series length.
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Sierra, W., Argoty, C., Franco, H. (2017). Varicella Incidence Rate Forecasting in Bogotá D.C. (Colombia) by Stochastic Time Series Analysis. In: Figueroa-García, J., López-Santana, E., Villa-Ramírez, J., Ferro-Escobar, R. (eds) Applied Computer Sciences in Engineering. WEA 2017. Communications in Computer and Information Science, vol 742. Springer, Cham. https://doi.org/10.1007/978-3-319-66963-2_57
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