Temporal Dynamics and Predictive Modelling of Tuberculosis Mortality Trends: A Comparative Analysis of Ghana, Nigeria and Côte d’Ivoire
DOI:
https://doi.org/10.29327/2565368.4.1-2Keywords:
Tuberculosis, ARIMA models, Temoral dynamics, ForecastingAbstract
Tuberculosis (TB) remains a major global health challenge, particularly in sub-Saharan Africa where the burden of disease is disproportionately high (Corbett, Marston, Churchyard, & De Cock, 2006). This study investigates the temporal dynamics and predictive modelling of TB mortality in Ghana, Nigeria, and Côte d’Ivoire using data obtained from the World Bank’s open data portal. Autoregressive Integrated Moving Average (ARIMA) models were employed to analyze past trends and forecasts were done in country-specific contexts. The results revealed divergent patterns: Ghana’s TB mortality showed relative stability with ARIMA(1,2,3) model, Nigeria exhibited heightened variability with ARIMA(2,2,3), while Côte d’Ivoire indicated a steady decline in mortality under ARIMA(4,1,1). These findings demonstrate the usefulness of ARIMA models in capturing mortality dynamics, identifying high-risk periods, and guiding timely allocation of resources. The study concludes that predictive modelling offers a valuable tool for supporting evidence-based TB interventions, aligning with WHO’s End TB Strategy by 2035.
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