model {
 	# Likelihood
	for (i in 1:Nareas) {
		for (k in 1:Ndiseases) {
			Y[i, k] ~ dpois(mu[i, k])
			log(mu[i, k]) <- log(E[i, k]) + alpha[k] + tDelta[k,i]
  			RR[i,k] <- exp(alpha[k] + tDelta[k,i])
		}
  	}
    
	for(j in 1:Ndiseases){
		tDelta[j, 1:Nareas]~car.proper(ceros[],C[],adj[],num[],M[],sigma[j],gamma[j])
	    	gamma[j]~dunif(gamma.inf,gamma.sup)
	} 		
	for(i in 1:Nareas){ceros[i]<-0}
	gamma.inf<-min.bound(C[],adj[],num[],M[])
	gamma.sup<-max.bound(C[],adj[],num[],M[])

	# Other priors
	for (k in 1:Ndiseases) {
		alpha[k] ~ dflat()
		sigma[k] ~ dunif(0,10)
	}
}