To formulate appropriate strategies against infectious respiratory diseases like COVID-19, accurately evaluating airborne infection risk in both spatial and temporal aspects is critical. The non-uniform spread of aerosol-borne pathogens across different areas and time periods highlights the need for such precise assessment. Nevertheless, the classic Wells-Riley model and its variant, the rebreathed-fraction model, are limited to well-mixed conditions. Their incapability to assess airborne infection risk with spatial and temporal factors can lead to inaccurate estimations, either overemphasizing or downplaying the actual risk. This chapter introduces a new dilution-based approach for evaluating airborne infection risk. Through a comparative study with the Wells-Riley model and its modified version, it is evident that the proposed method represents a significant advancement over the original Wells-Riley model. It enables researchers and professionals to assess airborne infection risk with both spatial and temporal precision. Experimental tests conducted in a simulated hospital ward have provided strong evidence that the new method can effectively measure airborne infection risk from spatial and temporal viewpoints. Moreover, its user-friendly characteristic makes it a valuable tool in the design and creation of healthy built environments.