Virus Transfer at the Skin–Liquid Interface

Pitol, Ana K.; Bischel, Heather N.; Kohn, Tamar; Julian, Timothy R.

doi:10.1021/acs.est.7b04949

Cited by 43 publications

(93 citation statements)

References 60 publications

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“…To the authors' knowledge, the only data describing viral transfer efficiency as a function of duration is within the context of skin and liquid contacts. (34) Although information regarding the relationship between contact duration and transfer efficiency may change implementation in future exposure models, transfer efficiencies for hand-to-surface contacts did not have strong linear relationships with dose in this model (Table 4).…”

Section: Limitationsmentioning

confidence: 78%

“…Microbial transfer studies have traditionally involved measuring the transfer between one contaminated surface and another uncontaminated surface. (23)(24)(34)(35) The direction of transfer has been shown to affect transfer efficiency within a hand-to-food context and in some hand-tosurface contexts. (36)(37) The effect of using the same transfer efficiency distributions used for hand-to-surface versus surface-to-hand transfers in this study is unknown.…”

Section: Limitationsmentioning

confidence: 99%

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Modeling the role of fomites in a norovirus outbreak

Canales

Reynolds

Wilson

et al. 2019

Journal of Occupational and Environmental Hygiene

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Norovirus accounts for a large portion of the gastroenteritis disease burden, and outbreaks have occurred in a wide variety of environments. Understanding the role of fomites in norovirus transmission will inform behavioral interventions, such as hand washing and surface disinfection. The purpose of this study was to estimate the contribution of fomite-mediated exposures to infection and illness risks in outbreaks. A simulation model in discrete time that accounted for hand-to-porous surfaces, hand-to-nonporous surfaces, hand-to-mouth, -eyes, -nose, and hand washing events was used to predict 17 hrs of simulated human behavior. Norovirus concentrations originated from monitoring contamination levels on surfaces during an outbreak on houseboats. To predict infection risk, two dose-response models (fractional Poisson and 2F1 hypergeometric) were used to capture a range of infection risks. A triangular distribution describing the conditional probability of illness given an infection was multiplied by modeled infection risks to estimate illness risks. Infection risks ranged from 70.22% to 72.20% and illness risks ranged from 21.29% to 70.36%. A sensitivity analysis revealed that the number of hand-tomouth contacts and the number of hand washing events had strong relationships with modelpredicted doses. Predicted infection risks ranged from 21.29% to 70.36%, overlapping with leisure setting and environmental attack rates reported in the literature. In the outbreak associated with the viral concentrations used in this study, attack rates ranged from 50% to 86%. This model suggests that fomites may have accounted for 25% to 82% of illnesses in this outbreak.Fomite-mediated exposures may contribute to a large portion of total attack rates in outbreaks involving multiple transmission modes. The findings of this study reinforce the importance of frequent fomite cleaning and hand washing, especially when ill persons are present.

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Section: Limitationsmentioning

confidence: 78%

Section: Limitationsmentioning

confidence: 99%

Modeling the role of fomites in a norovirus outbreak

Canales

Reynolds

Wilson

et al. 2019

Journal of Occupational and Environmental Hygiene

View full text Add to dashboard Cite

show abstract

“…In addition to lacking behavior data, there are opportunities to further improve the current model by informing it with experimentally informed mechanistic equations. The effect of the duration of a contact on the amount of microbial transfer has been explored in a transfer efficiency study within the context of skin–liquid interfaces (Pitol, Bischel, Kohn, & Julian, ). Such transfer efficiency studies could be informative in accounting for droplets that may settle or land on surfaces, later resulting in exposure through hand‐to‐surface contacts.…”

Section: Discussionmentioning

confidence: 99%

Validation of a Stochastic Discrete Event Model Predicting Virus Concentration on Nurse Hands

et al. 2019

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Understanding healthcare viral disease transmission and the effect of infection control interventions will inform current and future infection control protocols. In this study, a model was developed to predict virus concentration on nurses' hands using data from a bacteriophage tracer study conducted in Tucson, Arizona, in an urgent care facility. Surfaces were swabbed 2 hours, 3.5 hours, and 6 hours postseeding to measure virus spread over time. To estimate the full viral load that would have been present on hands without sampling, virus concentrations were summed across time points for 3.5-and 6-hour measurements. A stochastic discrete event model was developed to predict virus concentrations on nurses' hands, given a distribution of virus concentrations on surfaces and expected frequencies of hand-to-surface and orifice contacts and handwashing. Box plots and statistical hypothesis testing were used to compare the model-predicted and experimentally measured virus concentrations on nurses' hands. The model was validated with the experimental bacteriophage tracer data because the distribution for model-predicted virus concentrations on hands captured all observed value ranges, and interquartile ranges for model and experimental values overlapped for all comparison time points. Wilcoxon rank sum tests showed no significant differences in distributions of model-predicted and experimentally measured virus concentrations on hands. However, limitations in the tracer study indicate that more data are needed to instill more confidence in this validation. Next model development steps include addressing viral concentrations that would be found naturally in healthcare environments and measuring the risk reductions predicted for various infection control interventions.

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“…An important and understudied aspect of exposure assessment in the context of activities that involve contaminated liquids is the transfer of pathogens from the liquid to the skin, followed by skin to mouth transfer. Microbial organisms present in liquids in contact with the skin result in exposure both by preferential adsorption to the skin surface as well as through remaining in liquid retained in the skin [ 7 , 8 ]. As a result, the quantity of pathogens retained on the skin after liquid contact is a function of both the volume of liquid on the skin and the concentration of the agent in the liquid.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to water retention on the skin, pathogen adsorption to the skin is an important factor influencing pathogen exposures [ 7 , 8 ]. The total transfer of pathogens from liquid to skin is estimated from the sum of the pathogens adsorbed on the skin and the unadsorbed pathogens present in the liquid retained on the skin.…”

Section: Introductionmentioning

confidence: 99%

Retention of E. coli and water on the skin after liquid contact

2020

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The frequent contact people have with liquids containing pathogenic microorganisms provides opportunities for disease transmission. In this work, we quantified the transfer of bacteria—using E . coli as a model- from liquid to skin, estimated liquid retention on the skin after different contact activities (hand immersion, wet-cloth and wet-surface contact), and estimated liquid transfer following hand-to-mouth contacts. The results of our study show that the number of E . coli transferred to the skin per surface area (n [ E . coli /cm 2 ]) can be modeled using n = C (10 −3.38 + h ), where C [ E . coli /cm 3 ] is the concentration of E . coli in the liquid, and h [cm] is the film thickness of the liquid retained on the skin. Findings from the E . coli transfer experiments reveal a significant difference between the transfer of E . coli from liquid to the skin and the previously reported transfer of viruses to the skin. Additionally, our results demonstrate that the time elapsed since the interaction significantly influences liquid retention, therefore modulating the risks associated with human interaction with contaminated liquids. The findings enhance our understanding of liquid-mediated disease transmission processes and provide quantitative estimates as inputs for microbial risk assessments.

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Virus Transfer at the Skin–Liquid Interface

Cited by 43 publications

References 60 publications

Modeling the role of fomites in a norovirus outbreak

Modeling the role of fomites in a norovirus outbreak

Validation of a Stochastic Discrete Event Model Predicting Virus Concentration on Nurse Hands

Retention of E. coli and water on the skin after liquid contact

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