Time Series Analysis on Infant Mortality Rates (A Case Study of Yobe State Specialist Hospital Geidam, 2014 - 2024) - Mustapha Abdullahi; Chiwa Musa Dalah (Mikailalsys Journal of Mathematics and Statistics, 2026)
This study examined the pattern and trend of infant mortality rates at Yobe State Specialist Hospital, Geidam, using retrospective secondary data from 2014 to 2024. The study aimed to analyze infant mortality patterns and forecast future trends using time series techniques. A quantitative retrospective design was adopted, and the data were analyzed using descriptive statistics and time series models, including moving averages and exponential smoothing, to identify trends, seasonal fluctuations, and forecast patterns within the study period. The findings revealed that infant mortality rates fluctuated across the years, showing both seasonal and irregular variations, with a slight downward trend toward the later years. The results suggest that improved maternal care, immunization programs, and increased public health awareness may have contributed to this decline. Forecast results indicate a gradual but continuous reduction in infant mortality if current health interventions are sustained and strengthened. The study concludes that time series analysis provides an effective framework for understanding the dynamics of infant mortality and supporting evidence-based policy decisions aimed at reducing infant deaths. The findings contribute to public health monitoring and forecasting by demonstrating the usefulness of time series techniques in assessing infant mortality trends. Practical implications include the need for state and local governments, through the Ministry of Health, to strengthen maternal and child health programs, with support from international organizations such as WHO and UNICEF.