Statistical Model for the Occurrence of Typhoid Fever in Takum, Taraba State, Nigeria: An Arima Model Approach

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Stephen Mathew
Danjuma Idi

Abstract

This study analyzes Typhoid Fever incidence at General Hospital Takum from 2012 to 2021 using ARIMA model. The initial data was non-stationary, necessitating differencing to achieve stationarity. The ARIMA (4,1,1) model, selected based on AIC, AICC, and BIC criteria, showed parameters within stationarity and invertibility constraints. Diagnostic tests validated the model's robustness, with Box-Ljung (Chi-Square = 6.7435, p = 0.7598), Shapiro-Wilk (W = 0.9754, p = 0.1213), and ARCH-LM (Chi-Square = 5.8762, p = 0.8176) results supporting its adequacy. Forecasts for the next 24 months indicate a significant upward trend in Typhoid Fever cases. The study recommends among others a regular update to the model with new data to ensure accuracy, consideration of additional variables that may influence Typhoid Fever trends, and implementation of targeted public health interventions based on forecasted trends to mitigate the rising incidence.

Keywords:
Typhoid; Diagnostic; ARIMA; Stationarity; Box-Ljung; Forecasting

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How to Cite
Mathew, S., & Idi, D. (2024). Statistical Model for the Occurrence of Typhoid Fever in Takum, Taraba State, Nigeria: An Arima Model Approach. ALSYS, 4(6), 722-741. https://doi.org/10.58578/alsys.v4i6.3580

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