Nowadays, various studies show that many millions of patients globally are affected by healthcare-associated infections (HAIs) or nosocomial infections each year, causing hundreds of thousands direct deaths, presenting a crucial public health problem with serious social and economic implications with a predicted increasing tendency. Biosensor systems propose today a realizable way face to standard methods for detecting bacterial infections in clinical environments, as these standard methods are time-consuming and costly, presenting many limitations. This study involves interdisciplinary scientific areas to describe a theoretical frame of a real-time digital multi-system simulation of nosocomial infections in Mixed Reality environment. The theoretical description of the technical conditions and requirements of such a system will contribute to a future implementation of a real-time 3D spatial detection, quantification and simulation with future data monitoring of nosocomial bacteria rates. The proposed simulation system is based on combined simulation methods and mainly on voxels/point clouds technology with a potential comparison and evaluation with ideal rates in a comprehensible way. This will allow healthcare specialists and political decision makers to evaluate a hospital environment sanitary by taking suitable measures.