Predictive Modeling of Virus Inactivation by UV

UV254 disinfection strategies are commonly applied to inactivate pathogenic viruses in water, food, air, and on surfaces. There is a need for methods that rapidly predict the kinetics of virus inactivation by UV254, particularly emerging difficult-to-culture viruses. We conducted systematic literature review rate constants wide range Using these data characteristics, we developed evaluated linear nonlinear models predicting constants. Multiple regressions performed best (+) ssRNA dsDNA viruses, with cross-validated root mean squared relative prediction errors similar those associated experimental tested measuring mouse coronavirus marine bacteriophage; predicted were within 7% 71% constants, respectively, indicating was more accurate than virus. Finally, our several which high-quality not available. Our will be valuable or