DEPLOYING THE SARIMA MODEL TO ANALYZE HISTORICAL AND FORECASTED TRENDS IN MOSQUITO PROLIFERATION ACROSS KHARTOUM STATE

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Authors: Professor Ehab Ahmed Frah
Cited by: 0

Abstract

Forecasting mosquito breeding sites is essential for guiding vector control strategies in endemic malaria and dengue regions, including Sudan. Time series models provide a valuable approach for capturing seasonal patterns and predicting fluctuations in breeding activity. Data on mosquito breeding sites in Khartoum State from 2001 to 2022 were analyzed using the Box-Jenkins methodology. After ensuring stationarity through logarithmic transformation, first differencing, and seasonal differencing, candidate SARIMA models were identified based on autocorrelation and partial autocorrelation plots. Competing models were evaluated using fit statistics, residual diagnostics, and the principle of parsimony. Among the tested specifications, SARIMA (1,1,1)(0,1,1)₁₂ emerged as the most appropriate model, achieving a stationary

Fields of Study & Subjects

Mosquito-borne diseases and control Malaria Research and Control Forecasting Techniques and Applications

Publication details

Journal / source
Advances and Applications in Statistics
Volume
93
Issue
2
Pages
183–208
Publication date
13 February 2026
Language
EN