Time Series Analysis of Tuberculosis in Medea Province in Algeria

Abstract

Despite Algeria has been able to join the group of countries with moderate tuberculosis (TB) prevalence since the 1980s, the disease remains one of the major public health issues in the country. Over the past decade, the annual incidence rate has hovered around 55 per 100 000 people. The incidence rate remains, however, very high in some provinces. The aim of this study was to describe the temporal patterns of TB in Médéa province which records the highest incidence rate in the country. In this retrospective study, the monthly pulmonary TB (PTB) and extrapulmonary TB (EPTB) data from 2008 to 2017, extracted from the national surveillance system, were analyzed and seasonal fluctuation was examined. The Box-Jenkins approach to fit seasonal autoregressive integrated moving average (SARIMA) model to the monthly PTB and EPTB notification data from 2008 to 2016 was performed. The models were used to predict the monthly cases of PTB and EPTB for the year 2017. The models were found to be adequate. Our findings indicate that SARIMA models are useful tools for monitoring and for predicting trends of TB incidence in Médea province.

Keywords

• Algeria,biostatistics,Box-Jenkins,seasonal autoregressive integrated moving average,times series analysis,tuberculosis

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