Focus on Healthcare/Disinfection: GUV Inactivation Constants: What’s the Point?

Troy Cowan IUVA Healthcare/UV Working Group facilitator
[email protected]

First, the good news. NIST ¹ and IUVA’s Healthcare/GUV Working Group are holding a workshop on GUV Inactivation Constants formulation and development, March 18-20, in Washington, DC. The purpose is to develop an action plan to nail down what it takes to get credible, reliable values for inactivation constants. Watch www.iuva.org for the latest updates, developments and registration information.

What’s the point? Why are inactivation constants that important? It’s all about how we predict how effective GUV can be. Here’s some background:

• The scientific community has recognized since the early 1900s ² that UV-C is truly germicidal (hence, the acronym GUV). In addition, germicidal action varies by wavelength, and germicidal action can be scientifically quantified.
• GUV light “inactivates” ³ microorganisms by damaging nucleic acids, preventing microorganism replication (if it can’t replicate, it can’t cause infection). ⁴
• Inactivation is measured by how much of a pathogen’s population is unable to reproduce after receiving a given ‘dose’ of particular GUV wavelength. ⁵ This is shown either as a percent reduction (e.g., 99.9%) or in scientific logarithmic notation (e.g., 3-log₁₀, aka ‘3 log kill’). ⁶
• Observed values are specific to the pathogen exposed, the GUV wavelength used, the amount of the GUV energy applied and the experimental conditions and equipment.

The general practice for over the last 100 years makes use of a well-defined, mathematical equation to model how much inactivation results from varying dose. ⁷ While this has enabled our understanding of GUV disinfection processes to be good, it needs to be much better so GUV applications can be scaled to where they are common in our daily lives.

The idealized formula provides for calculating an Inactivation Constant for a given pathogen and wavelength, based on the dose delivered and the inactivation results. In this formula, ‘N’ is the viable pathogen population after treatment, ‘N₀’ is the original pathogen population and ‘D’ is the delivered dose of GUV at the specified wavelength, resulting in ‘k’, the calculated Inactivation Constant.

-[ln(N/N₀)] / D = k ⁸

The formula also can be rearranged so that if the value for ‘k’ is known (the Inactivation constant) for a given pathogen/wavelength combination, and the inactivation results to achieve (i.e., ‘ln(N/N₀)’ or the ‘log kill’) are known, then we should be able to back-calculate the GUV dose required (i.e., ‘D’).

-[ln(N/N₀)] / k = D

Desired results divided by inactivation constant gives us the dose needed to get the desired inactivation results for that pathogen… Simple, right? Not quite.

The data doesn’t always behave the way we hope. In 2021, Masjoudi et al. published a review of 244 different papers and studies, tabulating inactivation data on ~873 pathogens. It was the most extensive compilation of inactivation data then available. ⁹ The pathogen data varied widely, making it difficult to use for design or regulatory purposes. For example,“MS2” (i.e., Bacteriophage MS2, strain ATTC 15977-B1), had 28 data entries from treatments with 254 nm GUV with reported 3-log₁₀ dosage values. ¹⁰ A basic statistical review of these MS2 data showed the following (with notes from this column’s author in italics):

• Dosage values ranged from 7.4 to 106 mJ/cm², an almost 90-unit swing. Are those results indicative of a process under control?
• The average dose was 58.7 mJ/cm², inferring delivery of that dose results in a 50/50 chance of achieving or not achieving the desired 3-log₁₀ Is that good enough?
• A regulator typically looks for a 95% probability of hitting the mark (e.g., 3-log₁₀). The data implies this requires a dose of ~96 mJ/cm² (average + two std. deviations), a 63% increase to the average. That big of a jump could be costly. Isit really necessary?

Those questions can’t be answered, given the widely divergent data; therefore, we need to do better if device designs are to be credible.

How can the variability be overhauled? One approach is to focus on the factors that influence variability, ¹¹ such as:

• variations and deficiencies in experimental methods, which could include overestimating UV absorbance, inaccurate calculation of the dose amount and inaccurate radiometry measurements; ¹²
• the high degree of complexity in each experiment, including pathogen strain selection and preparation of the medium; culturing procedures processing; equipment setup, calibration and operation; the actual testing; characterization of the results; and data analysis with regression and curve-fitting models; and ¹³
• the multiple correction and adjustment factors to the radiometer readings, feeding into multiple regression models being force-fit through the origin on a relatively small number of data points, making the resulting inactivation ‘curves’ hard to justify as a credible representation for the pathogen, as a whole. ¹⁴

And, any one of these could lead to observable differences in the final calculated dosage values between data sets. How do we fix that?

Steps already are underway to mitigate some of these factors. These steps include the following:

• To improve accuracy and repeatability on GUV measurement, ANSI/IES-approved standards now are in place or in development for measuring output of most GUV sources (e.g., low-pressure Hg bulbs of various shapes, LEDs and excimers) and whole GUV devices. ¹⁵
• For calibration of UV-C detectors (e.g., radiometers and dosimeters), a CIE standard is being developed for calibration of UV-C detectors.
• To improve the experimental processes, ASHRAE standards are being put in place to improve how to measure inactivation in the air and on surfaces. ¹⁶ A separate standard also has been developed specifically for measuring surface inactivation in healthcare patient and operating rooms. ¹⁷

Even so, the problem remains: Reported inactivation constants are influenced by the experimental conditions to the extent that it is “… difficult to transfer the inactivation rate constants with certainty to [the] design of practical inactivation devices.” ¹⁸

Part of the problem appears to be the intent of the inactivation studies – to produce “a definitive theoretical model that can predict the ultraviolet susceptibility of microbes,” ¹⁹ as opposed to developing criteria for device design and use. Maybe we need to revisit the intent – not worry so much about the definitive model, and instead focus on how much inactivation is required for device design.

How much inactivation (i.e., ‘efficacy’) is needed? FIFRA regulations, as enforced by EPA, avoid specifying a minimum efficacy; instead, they require scientific evidence to back up efficacy claims. Without that evidence, the labeling is deemed “false or misleading.” Per FIFRA, that is “labeling is false or misleading in any particular, including both pesticidal and non-pesticidal claims.” ²⁰ What EPA does specify is a definition for “low level disinfectant” (used in regulating chemical disinfectants), which is, at minimum, a 3-log₁₀ reduction in the target pathogen. ²¹ That’s also the same reduction goal found in the recent ANSI/HSI patient and operating whole room disinfection standard. ²²

So, What’s the Point?

There is a substantial need for a community review, discussion and consensus building on measurement protocols, results interpretation and standards for GUV inactivation constants, with considerable focus on variable UV wavelength, microorganism, media and experimental conditions. Maybe action could be taken to determine what it takes to get reproducible 3-log₁₀ inactivation values now, so the industry can field good devices.

Let’s discuss it at the GUV Inactivation Constants Workshop, March 18-20, in Washington, DC.

 References

1. The National Institute of Standards and Technology, US Dept. of Commerce; see the review paper by Poster et al. J Res Natl Inst Stan 126:126014. https://doi.org/10.6028/jres.126.014, for a review of NIST and IUVA engagements on UV technologies for public health, including the first NIST-IUVA jointly held workshop in January 2020.
2. W. Kowalski, Ultraviolet Germicidal Irradiation Handbook, (2009), ISBN 978-3-642-01998-2, e-ISBN 978-3-642-01999-9 DOI 10.1007/978-3-642-01999-9. Table 1.2, pg 3
3. Ibid., Glossary
4. US EPA, “Ultraviolet Disinfection Guidance Manual for the Long Term 2 Enhanced Surface Water Treatment Rule,” EPA 815-R-06-007, Nov 2006, https://www.epa.gov/system/files/documents/2022-10/ultraviolet-disinfection-guidance-manual-2006.pdf, last accessed 27 Oct 2024, Section 2.3
5. L. Li, R. Nissly, , et al, “Inactivation of HCoV-NL63 and SARS-CoV-2 in Aqueous Solution by 254 nm UV-C,” Manuscript_63e829c366c0bd1768d6294992600543, © 2023 published by Elsevier., https://www.sciencedirect.com/science/article/pii/S1011134423001094, Eq. (1), pg 8
6. US EPA, “Ultraviolet Disinfection Guidance Manual…”, Section 2.3.4
7. E. Blatchley, B Petri, and Sun, “SARS-CoV-2 Ultraviolet Radiation Dose-Response Behavior,” Journal of Research of the National Institute of Standards and Technology. Volume 126, Article No. 126018 (2021) https://doi.org/10.6028/jres.126.018
8. Ibid. Section 2
9. M. Masjoudi1, M. Mohseni1, and J. Bolton, “Sensitivity of Bacteria, Protozoa, Viruses, and Other Microorganisms to Ultraviolet Radiation,” Journal of Research of the National Institute of Standards and Technology, Volume 126, Article No. 126021 (2021) https://doi.org/10.6028/jres.126.021
10. Ibid, Article pgs 48-54
11. Six Sigma Development Solutions, Inc., “What Is The Taguchi Method in Quality Control?,” re: Item 2, “Identify Key Factors,” https://sixsigmadsi.com/what-is-the-taguchi-method-in-quality-control/, last accessed 29 October 2024
12. Blatchley, et al, pg. 3
13. Li, et al, Section 2
14. Ibid., Section 3.5
15. T. Cowan, “Communicate, Collaborate, Consolidate & Educate -C3E”, UV Solutions, 2023, Qtr 4, https://bluetoad.com/publication/?m=59678&i=810341&p=8&ver=html5, last accessed 29 October 2024, pg 7
16. Ibid
17. Ibid
18. Li, et al, Section 4, pg. 15
19. W. Kowalski, W. Bahnfleth & M. Hernandez, “A Genomic Model for the Prediction of Ultraviolet Inactivation Rate Constants for RNA and DNA Viruses,” https://www.researchgate.net/publication/228572269, last accessed 29 October 2024, Introduction
20. US Code of Federal Regulations 40 CFR 156.10 “Labeling requirements,” (a) (5) “False or misleading statements.” https://www.ecfr.gov/current/title-40/chapter-I/subchapter-E/part-156, last accessed 1 November 2024
21. EPA, “Guidance for Products Adding Residual Efficacy Claims,” Table 1, https://www.epa.gov/pesticide-registration/guidance-products-adding-residual-efficacy-claims, last accessed 1 November, 2024
22. Healthcare Standards Institute, ANSI-HSI 2000-2023 Healthcare UV Germicidal Light Whole-Room Surface Disinfection,” https://webstore.ansi.org/standards/ansi/ansihsi20002023?srsltid=AfmBOorBztZ6tDjeA65-_xjfNU_2CruDVpvEg4zHIb8qEa3IlzEelAjz