The files in this repository correspond to the paper "Bayesian Spatial Modelling of Geostatistical Data using INLA and SPDE methods: A Case Study Predicting Malaria Risk in Mozambique" published in Spatial and Spatio-temporal Epidemiology.
Data d.csv contains prevalence survey data for Mozambique and selected covariates in surveyed locations (altitude alt, maximum temperature temp, precipitation prec, humidity hum, population density pop and distance to nearest inland water bodies dist_aqua).
Data dp.csv specifies the locations where we wish to predict the prevalence together with values of covariates in these locations.
Code code.R contains the R code to run the analysis and visualize the results.