Performance Evaluation of In‐Duct Ultraviolet Germicidal Irradiation Air Disinfection Systems: The Role of Reduction Equivalent Dose Bias

The COVID‐19 pandemic highlighted the importance of effective air disinfection technologies to mitigate the spread of airborne pathogens. In‐duct ultraviolet germicidal irradiation (UVGI) systems may be a viable solution. System performance should be validated using biodosimetry, as per several existing standards. These tests yield the kill rates of a surrogate organism and its reduction equivalent dose (RED), with the intent that the RED be extrapolated to a predicted kill rate of a target pathogen of interest, such as SARS‐CoV‐2. However, this extrapolation requires adjustments to account for potential bias between the surrogate RED and the target RED (called the RED bias). Overlooking this mismatch can lead to inaccurate claims of the actual inactivation performance against the target. This study uses computational fluid dynamics modeling to analyze the UV dose distribution and resulting RED bias in in‐duct UVGI systems. The results showed that, when MS2, a UV‐resistant organism, is used as a surrogate to predict SARS‐CoV‐2 inactivation efficiency, the RED bias ranged from 1.14 to 1.46 within the studied cases, suggesting that the SARS‐CoV‐2 log inactivation can be overestimated by as much as 46%. This study also explores the combined variable (CV) approach as a more accurate method for predicting pathogen inactivation, offering an alternative to the RED bias approach. Both the RED bias approach and the CV approach were effective in improving the accuracy of performance predictions. This study underscores the need for the industry to incorporate considerations of the RED bias phenomenon in the future development of performance evaluation guidance to avoid overestimation of the treatment performance and safeguard public health.