Modeling suspected malaria cases in Papua province with second order Besag-York-Mollie 2 spatial regression
DOI:
https://doi.org/10.58524/app.sci.def.v2i2.433Keywords:
INLA, Disease mapping, Papua Province, Conditional Autoregressive, Spatial statisticsAbstract
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.References
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