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

Professor Ehab Ahmed Frah

Advances and Applications in Statistics2026https://doi.org/10.17654/0972361726012article
ABDC C
Weight
0.50

What the paper says

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

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https://doi.org/https://doi.org/10.17654/0972361726012

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@article{professor2026,
  title        = {{DEPLOYING THE SARIMA MODEL TO ANALYZE HISTORICAL AND FORECASTED TRENDS IN MOSQUITO PROLIFERATION ACROSS KHARTOUM STATE}},
  author       = {Professor Ehab Ahmed Frah},
  journal      = {Advances and Applications in Statistics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.17654/0972361726012},
}

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

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.