Why is mock care not a good proxy for predicting hand contamination during patient care?

King, Marco‐Felipe; Wilson, Amanda M.; López‐García, Martín; Proctor, Jessica; Peckham, Daniel; Clifton, Ian; Dancer, Stephanie J.; Noakes, Catherine

doi:10.1016/j.jhin.2020.11.016

Cited by 8 publications

(8 citation statements)

References 28 publications

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“…For example, Fedorenko et al (2020) demonstrated that MS2 and PhiX174, non‐enveloped enteric viruses, in evaporated saliva microdroplets on a glass surface only reduced by approximately 1 log 10 over a 14‐hour period for a range of relative humidities 26 . By comparison, observed mock care episodes used to inform simulated behaviors in this study ranged from 0.6 to 11.7 minutes 17 …”

Section: Methodsmentioning

confidence: 59%

“…For each probability matrix, behavior states included entrance into patient room, exit from patient room, use of alcohol gel, hand‐to‐equipment contact, hand‐to‐far‐patient surface contact, hand‐to‐near‐patient surface contact, hand‐to‐patient contact, doffing of gloves, donning of gloves, and hand‐to‐hygiene surface contact. Categories of surfaces matching these surface type designations for categorizing observed behaviors have been described previously by King et al 17 Transitional probability matrices were altered so that exit from patient room was an absorbing state and the probability of an “entrance into patient room” event after the initial entrance was zero.…”

Section: Methodsmentioning

confidence: 99%

“…The potential for fomite contamination spread via hand‐to‐surface contacts, especially for HCPs, has been a long‐recognized mechanism of nosocomial disease transmission 13,14 . The frequency and sequence of contacts with different surface types, 15,16 for different care types during simulated vs. actual procedures, 16,17 and the effect of these differences on microbial exposures have been explored 18 . However, it is unknown how spatial differences between patient rooms may affect deposition patterns, hand‐to‐surface behaviors of healthcare professionals, and subsequent exposures.…”

Section: Introductionmentioning

confidence: 99%

“…A secondary objective was to demonstrate how a calibrated microbial transfer model can be utilized in exposure modeling. To meet these objectives, an integrated exposure model composed of a finite volume Navier‐Stokes computational fluid dynamics (CFD) model using Lagrangian particle tracking, 19 a human behavior model informed by real‐world data, 17 and a viral transfer model calibrated for representation of transfer of enteric viruses 20 was developed.…”

Section: Introductionmentioning

confidence: 99%

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Effects of patient room layout on viral accruement on healthcare professionals' hands

et al. 2021

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Healthcare professionals (HCPs) are exposed to highly infectious viruses, such as norovirus, through multiple exposure routes. Understanding exposure mechanisms will inform exposure mitigation interventions. The study objective was to evaluate the influences of hospital patient room layout on differences in HCPs' predicted hand contamination from deposited norovirus particles. Computational fluid dynamic (CFD) simulations of a hospital patient room were investigated to find differences in spatial deposition patterns of bioaerosols for right‐facing and left‐facing bed layouts under different ventilation conditions. A microbial transfer model underpinned by observed mock care for three care types (intravenous therapy (IV) care, observational care, and doctors' rounds) was applied to estimate HCP hand contamination. Viral accruement was contrasted between room orientation, care type, and by assumptions about whether bioaerosol deposition was the same or variable by room orientation. Differences in sequences of surface contacts were observed for care type and room orientation. Simulated viral accruement differences between room types were influenced by mostly by differences in bioaerosol deposition and by behavior sequences when deposition patterns for the room orientations were similar. Differences between care types were likely driven by differences in hand‐to‐patient contact frequency, with doctors' rounds resulting in the greatest predicted viral accruement on hands.

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Section: Methodsmentioning

confidence: 59%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effects of patient room layout on viral accruement on healthcare professionals' hands

et al. 2021

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“…By assigning each surface category a numerical value from 1 to 5, where Equipment = 1, Patient = 2, Hygiene areas = 3, Near‐bed surfaces = 4, and Far‐bed surfaces = 5, HCW sequential contact of surfaces can be modeled in terms of weighted probabilities. 14 More information regarding the observation of these behaviors and analysis of sequences of events can be seen in King et al 20 …”

Section: Methodsmentioning

confidence: 99%

Modeling fomite‐mediated SARS‐CoV‐2 exposure through personal protective equipment doffing in a hospital environment

et al. 2021

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Self‐contamination during doffing of personal protective equipment (PPE) is a concern for healthcare workers (HCW) following SARS‐CoV‐2‐positive patient care. Staff may subconsciously become contaminated through improper glove removal; so, quantifying this exposure is critical for safe working procedures. HCW surface contact sequences on a respiratory ward were modeled using a discrete‐time Markov chain for: IV‐drip care, blood pressure monitoring, and doctors’ rounds. Accretion of viral RNA on gloves during care was modeled using a stochastic recurrence relation. In the simulation, the HCW then doffed PPE and contaminated themselves in a fraction of cases based on increasing caseload. A parametric study was conducted to analyze the effect of: (1a) increasing patient numbers on the ward, (1b) the proportion of COVID‐19 cases, (2) the length of a shift, and (3) the probability of touching contaminated PPE. The driving factors for the exposure were surface contamination and the number of surface contacts. The results simulate generally low viral exposures in most of the scenarios considered including on 100% COVID‐19 positive wards, although this is where the highest self‐inoculated dose is likely to occur with median 0.0305 viruses (95% CI =0–0.6 viruses). Dose correlates highly with surface contamination showing that this can be a determining factor for the exposure. The infection risk resulting from the exposure is challenging to estimate, as it will be influenced by the factors such as virus variant and vaccination rates.

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

Wilson

Jones

2021

J Expo Sci Environ Epidemiol

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Why is mock care not a good proxy for predicting hand contamination during patient care?

Cited by 8 publications

References 28 publications

Effects of patient room layout on viral accruement on healthcare professionals' hands

Effects of patient room layout on viral accruement on healthcare professionals' hands

Modeling fomite‐mediated SARS‐CoV‐2 exposure through personal protective equipment doffing in a hospital environment

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

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