AB STRACT
This research work describes a study that used measles disease data collected through
Knoema health surveillance system to evaluate univariate time series method namely;
autoregressive integrated moving average (ARIMA). The data obtained from 1980 to 2016
were used as modeling data and forecasting samples, respectively. The performances were
evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage
error (MAPE), and mean square error (MSE). A low normalized BIC of21.817 was recorded.
The accuracy of the statistical model in forecasting future measles disease proved its
effectiveness in measles disease breakout surveillance. Although the outcome of this research
work, has shown that measles outbreak in the nearest future wi II take a downward trend from
2017 to 2019, as shown in the forecasted output. It was also observed that 40.9% estimate of
the proportion of the total variation in the series (measles_!) is explained by the model. The
result of th is research work has shown that funds for measles can be diverted to other diseases
as little fund is required to facilitate measles vaccine and improve measles vaccination in the
country.
ADEGBOYEGA, O (2021). Time Series Analysis On Measles Cases In Nigeria. Afribary. Retrieved from https://track.afribary.com/works/time-series-analysis-on-measles-cases-in-nigeria-1
ADEGBOYEGA, OBAF "Time Series Analysis On Measles Cases In Nigeria" Afribary. Afribary, 11 Apr. 2021, https://track.afribary.com/works/time-series-analysis-on-measles-cases-in-nigeria-1. Accessed 05 Nov. 2024.
ADEGBOYEGA, OBAF . "Time Series Analysis On Measles Cases In Nigeria". Afribary, Afribary, 11 Apr. 2021. Web. 05 Nov. 2024. < https://track.afribary.com/works/time-series-analysis-on-measles-cases-in-nigeria-1 >.
ADEGBOYEGA, OBAF . "Time Series Analysis On Measles Cases In Nigeria" Afribary (2021). Accessed November 05, 2024. https://track.afribary.com/works/time-series-analysis-on-measles-cases-in-nigeria-1