Time Series Analysis of Measles Incidence in Nigeria Using Surveillance Data from 2011 to 2022

Abstract

Background: Measles is a highly contagious viral disease that primarily affects children, especially in underdeveloped nations. In Nigeria, inadequate vaccine coverage has sustained measles endemicity. This study analyzed the trend and seasonality of measles in Nigeria and forecasted its trajectory from January 2023 to December 2026. Methods and Materials: Time series analysis was applied to laboratory-confirmed measles cases from the World Health Organization case-based surveillance data reported in Nigeria from January 2011 to December 2022. The analysis was conducted using Seasonal and Trend decomposition using Loess and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, with model selection determined by the Akaike Information Criterion and validated using residual diagnostics. Measles incidence forecasts for 2023 to 2026 were generated, with predictive accuracy assessed using the root mean square error and mean absolute error (MAE). Results: A total of 203,587 measles cases were reported during this period, with an average incidence of 7.5 cases per one million individuals. Seasonal peaks were consistently observed from January to March, with no discernible long-term trend. The SARIMA (3, 0, 1)(1, 1, 1)₁₂ model demonstrated the best fit for forecasting, achieving an MAE of 3.2 cases per one million population when comparing predicted and observed incidence in 2023. Forecasts suggest the seasonal patterns and magnitudes will persist through 2026, assuming all factors remain constant. Conclusion: This study highlights seasonal peaks in measles incidence from January to March in Nigeria, highlighting the urgent need for improved vaccination coverage and targeted public health interventions during peak seasons to mitigate the disease burden.