Abstract
Personalized medicine has been progressively implemented in several diagnostic and therapeutic patients' algorithms, based on the common assumption that tailoring interventions, practices, and/or therapies to individual patients' clinical, biological, epidemiological, and genetic characteristics would optimize their effectiveness and reduce adverse effects. The potential benefit of the precision medicine approach has been recently considered for possible implementation in the field of infection prevention and control. The commentary explores available evidence and assesses possible future scenarios where, through advanced modeling approaches, we would be able to provide personalized prediction algorithms identifying at-risk patients who deserve the implementation of tailored preventive measures.