Application of time series control charts to model and monitor the seasonality of norovirus

Jones Anderson Monteiro Siqueira; Anna Alice Garcia Caldas Nunes; Milene Silveira Ferreira; Alexandre da Costa Linhares; Edson Marcos Leal Soares Ramos; Yvone Benchimol Gabbay

doi:10.5123/S2176-62232015000200008

Authors

Jones Anderson Monteiro Siqueira Núcleo de Medicina Tropical, Universidade Federal do Pará, Belém, Pará, Brasil
Anna Alice Garcia Caldas Nunes Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brasil
Milene Silveira Ferreira Núcleo de Medicina Tropical, Universidade Federal do Pará, Belém, Pará, Brasil
Alexandre da Costa Linhares Seção de Virologia, Instituto Evandro Chagas/SVS/MS, Ananindeua, Pará, Brasil
Edson Marcos Leal Soares Ramos Instituto de Ciências Exatas e Naturais, Universidade Federal do Pará, Belém, Pará, Brasil
Yvone Benchimol Gabbay Seção de Virologia, Instituto Evandro Chagas/SVS/MS, Ananindeua, Pará, Brasil

DOI:

https://doi.org/10.5123/S2176-62232015000200008

Keywords:

Time Series, Seasonal Variation, Norovirus, Gastroenteritis

Abstract

INTRODUCTION: Time series control charts are tools that allow one to identify the nature of certain variations in a process, whether they are variations due to common causes, deemed of little importance, or to special causes. The goal of this study was to apply time series control charts to analyse the seasonality observed in norovirus infections in children admitted from May 2008 to April 2011 to a paediatric hospital in Belém City, Pará State, Amazon Region, Brazil.
MATERIALS AND METHODS: To apply the models, it was necessary to make the stationary series, which was performed by applying the first difference of monthly norovirus positivity rates. To construct the charts, Kolmogorov-Smirnov normality test was used to verify if the data were normally distributed.
RESULTS: During the three years, the highest prevalence was observed between September and October 2008 (63.6%) and February 2010 (62.1%). The study series was under statistical control, with a tendency for stability and no evidence of seasonality or cycle. No outlying values were observed, which strongly suggest that no atypical factor that could affect the stability of the series was present.
CONCLUSION: This study demonstrates the applicability of time series control charts in the seasonality analysis of several pathogens studied in the biomedical sciences, and it is the first time that this statistical method has been applied to assess the time distribution of norovirus.