Health analytics and disease modeling for better understanding of healthcare-associated infections

Abstract

Healthcare-associated infections (HAIs) are a growing challenge and a major cause of health concern worldwide. It is difficult to understand precisely the dynamics of spread of hospital-acquired infections owing to the usual involvement of different populations, risk factors, environments, and pathogens. Mathematical and computational models have proved to be useful tools in providing realistic representations of HAI dynamics and the means of evaluating interventions to minimize the risk of HAIs.