Logo Lanfrica

aeei1995wang/MalariaMozambique

Domain:

healthcaregeospatial

Record type:

dataset
Creator:
aee
Host:
Data and codes for the article "Bayesian Spatial Modelling of Geostatistical Data using INLA and SPDE methods: A Case Study Predicting Malaria Risk in Mozambique" # MalariaMozambique The data files in this repository are for the paper "Bayesian Spatial Modelling of Geostatistical Data using INLA and SPDE methods: A Case Study Predicting Malaria Risk in Mozambique" (sciencedirect.com). Prevalence survey data for Mozambique and selected covariates in surveyed locations (altitude alt, maximum temperature temp, precipitation perc, humidity gum, population density pop and distance to nearest inland water bodies aqua) are stored in data frame d. Data frame dp specifies the locations where we wish to predict the prevalence together with values of covariates in these locations.