A set of four plausible environmentalcovariates, together with wasting, low-MUAC and malaria in children wereincluded in the analysis18,34.
These were rainfall, enhancedvegetation index (EVI), mean temperature, and urbanization. Rainfall and meantemperature were derived from the monthly average grid surfaces obtained fromWorldClim database35. The EVI values were derived from theMODerate-resolution Imaging Spectroradiometer (MODIS) sensor imagery for period2007-2010 while the urbanization information was obtained from Global RuralUrban Mapping Project (GRUMP)36,37. All the environmental covariateswere extracted from 1 x 1 km spatial resolution grids. Rainfall, temperatureand EVI were summarized to compute seasonal averages corresponding to the timeof survey. Statistical methodsTheoverall aim of this study was to model the ecological comorbidity of wastingand low-MUAC with malaria parasitaemia among children aged 6-59 month inSomalia from 2007 – 2010. To achieve this, we implemented the Bayesiangeostatistical shared component model through stochastic partial differentialequation (SPDE) approach in integrated nested Laplace approximations (INLA)using R-INLA library in R project version 3.2.
3. 22–24,38,39. Therefore, we modelled twounderlying spatial risks common to: (1) wasting and malaria and (2) low-MUAC andmalaria at child level. The relative risk of each condition depends on a latentspatial component shared by each pair and a condition-specific component aftercontrolling for environmental covariates40,41. The household survey andenvironmental predictors of malnutrition and malaria were controlled atindividual, household and village level. Finally, to determine if the riskswere correlated, we performed a significant test by looking at the 2.5% and97.5% quantiles of each element of the random effect using the quintilecorrection (QC) method as implemented by Bolin and Lindgren 201242.
Further, the empirical correlation between the conditions were exploredusing correlation plots. Detailed methods on covariate selection,geostatisitcal shared component modeling, validation procedures are describedelsewhere31.