We aimed to identify the factors associated with the spatial risk of HPAI. To do so, we constructed a linear model with fixed effects. We used the logarithm of the relative risk estimated through the Bayesian approach (which modelled the exponential of relative risk values through a Gaussian distribution in each statistical unit, as mentioned by Besag et al. [3] ) as the dependent variable. Separate models of HPAI outbreaks were constructed for the chicken and duck populations. Each of the two models contained 18 variables which included environmental, poultry farming, and anthropogenic factors. Multicollinearity was investigated by checking the standard errors of regression coefficients and the variance inflation factors (VIF) [6] . The density of native chickens and the density of farms with native chickens were found to be positively correlated; consequently, only the former was introduced into the analysis. Multicollinearity was finally assumed not to cause any serious problem in the model (VIF values < 5.1) [6] .