The Study of Environmental Factors is one of the first steps in our search for determining factors in infectious diseases, particularly vector-borne. These factors play a major role in exposure and the onset of infections, but also in the development and progression of the disease by interacting with the host's genetic factors. We are working on statistical methods to identify and understand the role of these factors. We work with generalized regression models (GLM, GLMM, GEE, etc.) to take into account the aspect of complex designs and non-linear distributions that can often be encountered in data (non-Gaussian traits, repeated measures , non-independence of subjects as for example in family cohorts, etc.). We also work with data visualization methods such as Principal Component Analysis (PCA), Factor Correspondence Analysis (CFA) contributing to a better understanding of the interdependence between the studied variables.