Cost-Benefit Analysis of Far-UVC Lamps for Reducing Indoor Infection Transmission in Switzerland and Germany: Insights from the CERN Airborne Model for Indoor Risk Assessment (CAiMIRA)

Abstract

Far-UVC light (wavelengths 207-230 nm) can be used directly overhead, whilst having germicidal capabilities to improve indoor air quality. This study evaluates the cost-benefit of implementing far-UVC devices in various settings in Switzerland and Germany. We used the CERN Airborne Model for Indoor Risk Assessment (CAiMIRA) to model infection risk reduction in restaurants, offices, and waiting rooms, considering factors like room size, occupancy, and ventilation rates. Three scenarios were analysed: a normal winter (22 weeks), a COVID-19-like pandemic (4-week wave), and a severe pandemic (8-week wave). Avoided infections were translated into healthcare, economic and avoided quality-adjusted life years (QALY) metrics. Costs included purchasing, installing, maintaining, and operating UV-C lamps. In Switzerland, cost-benefit ratios ranged from one franc to: 30-290 CHF during a normal winter; 65-430 CHF during a COVID-like pandemic; and 2,300-20,500 CHF during a severe pandemic. In Germany, cost benefit ratios ranged from 1 euro to: 7-226 EUR during a normal winter; 118-449 EUR during a COVID-like pandemic; and 659-18,946 EUR during a severe pandemic. Far-UVC lamps are a highly cost-effective solution for societies during normal winter and pandemic scenarios. Implementation in the settings studied should be considered as a safe and effective measure for infectious disease control.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study did not receive any funding

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

https://caimira.web.cern.ch/ Modelling done by the research team based on published data on economic costs of disease, building size, epidemiological studies and expert opinion.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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Footnotes

Contact information Matysik, Sabine <Sabine.Matysikd-fine.com>, Laurent Bächler <laurent.baechlerpourdemain.ch>, “Bohmann, Bianca” <Bianca.Bohmannd-fine.com>, “El Chamaa, Marwan” <Marwan.El.Chamaad-fine.com>, “Baumeister, Markus” <Markus.Baumeisterd-fine.com>, Daniel Staudenmann <daniel.staudenmanngmail.com>, Jasper Götting <jasper.goettingicloud.com>, “nicolas.banholzerunibe.ch” <nicolas.banholzerunibe.ch>, “Krueger, Stefan” <Stefan.Kruegerd-fine.com>, “Eu, Sungmin” Sungmin.Eud-fine.com

JEL I 18 (Government Policy • Regulation • Public Health), Q 53 (air pollution), Q 55 (technological innovation)

Data Availability

All data produced in the present work are contained in the appendix through our "setting assumptions" table

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