The management of airflow distribution is crucial in preventing respiratory infections like COVID-19, with ventilation metrics serving as key indicators to assess airborne infection risks and evaluate the effectiveness of air distribution systems. This chapter examines the correlation between ventilation metrics and airborne infection risk, proposing new indices to measure the efficacy of infection control strategies within these systems. Alongside traditional metrics such as age of air (AoA), air change effectiveness (ACE), and contaminant removal effectiveness (CRE), this chapter introduces air utilization effectiveness (AUE) and contaminant dispersion index (CDI) as innovative indices. Computational fluid dynamics (CFD) simulations are carried out in hospital wards and classrooms to apply different ventilation strategies, compute these indices, and evaluate airborne infection risk. A three-stage correlation analysis, using statistical methods, is developed to validate these ventilation indices. The results support the combined use of AUE and CDI as a comprehensive indicator of airborne infection risk, with CDI particularly emphasized for local risk assessment, regardless of factors like the influence of air distribution, airflow rates, infectiousness levels, room configurations, and occupant distributions. This chapter makes a significant contribution to enhancing control measures against the airborne spread of respiratory diseases by optimizing air distribution strategies.