Exploring spatial averaging of contamination in fomite microbial transfer models and implications for dose

ABSTRACT BACKGROUND When modeling exposures from contact with fomites, there are many choices in defining the sizes of compartments representing environmental surfaces and hands, and the

portions of compartments involved in contacts. These choices impact dose estimates, yet there is limited guidance for selection of these model parameters. OBJECTIVE The study objective was

to explore methods for representing environmental surface and hand contact areas in exposure models and implications for estimated doses. METHODS A simple scenario was used: an individual

using their hands to contact their face and two microbially contaminated environmental surfaces. Four models were developed to explore different compartmentalization strategies: (1) hands

and environmental surfaces each represented by one compartment, (2) hands represented by two compartments (fingertips vs. non-fingertip areas) while environmental surfaces were represented

by one compartment, (3) hands represented by a single compartment and environmental surfaces represented by two compartments, and (4) hands and environmental surfaces each represented by two

compartments. Sensitivity analyses were conducted to evaluate the influence of heterogeneous surface contact frequency, hand contact type, and hand dominance on dose. RESULTS Estimated

doses were greatest when hand areas and environmental surfaces were each represented by two compartments, indicating that surface area “dilutes” contaminant concentration and decreases

estimated dose. SIGNIFICANCE Model compartment designations for hands and environmental surfaces affect dose estimation, but more human behavior data are needed. IMPACT STATEMENT A common

problem for exposure models describing exposures via hand-to-surface contacts occurs in the way that estimated contamination across human skin (usually hands) or across environmental

surfaces is spatially averaged, as opposed to accounting for concentration changes across specific parts of the hand or individual surfaces. This can lead to the dilution of estimated

contaminants and biases in estimated doses in risk assessments. The magnitude of these biases and implications for the accuracy in risk assessments are unknown. We quantify differences in

dose for various strategies of compartmentalizing environmental surfaces and hands to inform guidance on future exposure model development. Access through your institution Buy or subscribe

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June 24, 2021. Download references ACKNOWLEDGEMENTS Code is accessible via: https://github.com/awilson12/dilution_model_comparison. AM Wilson was supported by the Rocky Mountain Center for

Occupational and Environmental Health (CDC/NIOSH T42/OH008414). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Rocky Mountain Center for Occupational and Environmental Health, University of

Utah, Salt Lake City, UT, USA Amanda M. Wilson & Rachael M. Jones * Department of Family and Preventive Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA Amanda

M. Wilson & Rachael M. Jones * Department of Community, Environment & Policy, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, 85721, USA Amanda M.

Wilson Authors * Amanda M. Wilson View author publications You can also search for this author inPubMed Google Scholar * Rachael M. Jones View author publications You can also search for

this author inPubMed Google Scholar CONTRIBUTIONS AW and RJ contributed to the intellectual development and writing of the manuscript. AW led coding development. CORRESPONDING AUTHOR

Correspondence to Amanda M. Wilson. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Wilson, A.M., Jones, R.M. Exploring spatial averaging of contamination in fomite microbial transfer models and implications for dose. _J Expo

Sci Environ Epidemiol_ 32, 759–766 (2022). https://doi.org/10.1038/s41370-021-00398-2 Download citation * Received: 24 June 2021 * Revised: 19 October 2021 * Accepted: 21 October 2021 *

Published: 06 November 2021 * Issue Date: September 2022 * DOI: https://doi.org/10.1038/s41370-021-00398-2 SHARE THIS ARTICLE Anyone you share the following link with will be able to read

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KEYWORDS * Fomite transmission * risk assessment * infectious disease modeling