Modeling suspected malaria cases in Papua province with second order Besag-York-Mollie 2 spatial regression

The number of malaria cases in Indonesia has increased in recent years. The highest malaria cases in Indonesia are in the eastern region, namely Papua Province, where in 2021 there were 86,022 cases. This study aims to model suspected malaria cases in Papua using the Integrated Nested Laplace Approx...

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Bibliographic Details
Main Authors: Kirana Azzahra, Ro'fah Nur Rachmawati, Muhamad Syazali
Format: Article
Language:English
Published: FoundAE 2024-08-01
Series:International Journal of Applied Mathematics, Sciences, and Technology for National Defense
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Online Access:https://journal.foundae.com/index.php/JAS-ND/article/view/433
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Summary:The number of malaria cases in Indonesia has increased in recent years. The highest malaria cases in Indonesia are in the eastern region, namely Papua Province, where in 2021 there were 86,022 cases. This study aims to model suspected malaria cases in Papua using the Integrated Nested Laplace Approximation (INLA) approach. Modelling is carried out with two different orders to see the difference in determining the best results. The results showed that second-order spatial modelling provides better results than first order modelling because the RMSE value is smaller than the first-order model. Based on these results, it is concluded that the INLA approach with second-order spatial modelling is effective for analysing and predicting suspected malaria cases in Papua. Therefore, these results can be used as a reference in developing malaria control strategies in the region.
ISSN:2986-0776
2985-9352