Parameter Estimation Using INLA for Disease Mapping of Leptospirosis in Bantul Indonesia

Abstract

Agriculture sector is recognized as one important factor for an increased risk of leptospirosis in Bantul, Indonesia. From January to July 2010, there were 70 patients of leptospirosis with 43 patients engaged in agriculture. The aim of this study was to determine the impact of agricultural sector on the disease mapping of leptospirosis in district level. A structured additive regression model was used for statistical analysis associated with agricultural area and agricultural livelihood. In addition, a random effect that captures the spatial heterogeneity in the study region was also included in this study. Model estimation and predictive inference was carried out through the implementation of computer code in the R-INLA package, which makes use of the Integrated Nested Laplace Approximation.