TITLE:
Time Series Analysis on Reported Cases of Tuberculosis in Minna Niger State Nigeria
AUTHORS:
Samuel Olayemi Olanrewaju, Emmanuel Oluwatosin Ojo, Emmanuel Segun Oguntade
KEYWORDS:
Tuberculosis, Infectious, Vaccine, Stationarity, White Noise Process, Stochastic Process, Gaussian Process
JOURNAL NAME:
Open Journal of Statistics,
Vol.10 No.3,
May
30,
2020
ABSTRACT: Predicting the trend of non-seasonal data is a difficult task in Social
Science. In this research work, we used time series analysis of 144
observations on monthly basis for record of reported cases of tuberculosis patients
in Minna General Hospital, Niger State from the period of 2007-2018.
Exploratory Data Analysis (EDA: Time Plot and Descriptive Statistics),
Stationarity Test (ADF), Trend estimation (Tt),
Normality Test, and Forecast evaluation were carried out. The Augmented Dickey
Fuller test for stationarity was conducted and the result revealed that the
series are not stationary but became stationary after first difference. The
correlogram established that the ARIMA (2, 1, 3) was the best model this was
further confirmed from the result of L-jung Box. Equation for ARIMA (2, 1, 3)
was given as Xt + 0.6867Xt-1 – 0.8859Xt-2 = Et + 1.3077Et-1 - 1.2328Et-2 + 0.5788Et-3.
Which was used to predict five years likely cases of tuberculosis in Minna for
the period of 2019-2023. It was clearly shown from the projection that the
reported cases of tuberculosis reduce year by year by 7% over the period under
consideration which could be as a result of intervention from government,
health worker, and individuals. In line with these findings, we recommend that
the management of general hospital to increase awareness campaign to the public
on the causes and dangers of tuberculosis.