Evaluating a transfer gradient assumption in a fomite-mediated microbial transmission model using an experimental and Bayesian approach

Abstract

Current microbial exposure models assume that microbial exchange follows a concentration gradient during hand-to-surface contacts. Our objectives were to evaluate this assumption using transfer efficiency experiments and to evaluate a model's ability to explain concentration changes using approximate Bayesian computation (ABC) on these experimental data. Experiments were conducted with two phages (MS2, Φ X174) simultaneously to study bidirectional transfer. Concentrations on the fingertip and surface were quantified before and after fingertip-to-surface contacts. Prior distributions for surface and fingertip swabbing efficiencies and transfer efficiency were used to estimate concentrations on the fingertip and surface post contact. To inform posterior distributions, Euclidean distances were calculated for predicted detectable concentrations (log 10 PFU cm −2 ) on the fingertip and surface post contact in comparison with experimental values. To demonstrate the usefulness of posterior distributions in calibrated model applications, posterior transfer efficiencies were used to estimate rotavirus infection risks for a fingertip-to-surface and subsequent fingertip-to-mouth contact. Experimental findings supported the transfer gradient assumption. Through ABC, the model explained concentration changes more consistently when concentrations on the fingertip and surface were similar. Future studies evaluating microbial transfer should consider accounting for differing fingertip-to-surface and surface-to-fingertip transfer efficiencies and extend this work for other microbial types.

Community Transmission of SARS-CoV-2 by Surfaces: Risks and Risk Reduction Strategies

“… 41 The transfer of the virus from surface-to-hand and from hand-to-mucous membranes was assumed to be proportional to the concentration of the virus on the surface and the transfer efficiency of the virus at both interfaces. 42 The probability of infection for a given dose ( P inf ) was estimated using an exponential dose–response model where D [PFU] is the infectious dose and k = 2.46 × 10 –3 [PFU] −1 is the dose–response parameter. 43 This model is based on the pooled data of studies of SARS-CoV 44 and Murine hepatitis virus (MHV-1) 45 infection in mice.…”

“… 55 Therefore, virus inoculation on hands was modeled as a function of the concentration of virus in the saliva, the volume of saliva expelled per cough, the distance between the mouth and the hand, and the right circular cone angle of the ejected particles (α in Figure S2 and Table S1 ). Transfer from surface-to-hand and from hand-to-mucous membranes was assumed proportional to the concentration of the virus on the surface and the transfer efficiency of the virus at both interfaces 42 ( Figure S1 ). The concentration of the virus on the contaminated surface was assumed to decay exponentially.…”

Community Transmission of SARS-CoV-2 by Fomites: Risks and Risk Reduction Strategies

“…The copyright holder for this this version posted November 23, 2020. ; https://doi.org/10.1101/2020.11.20.20220749 doi: medRxiv preprint 5 and the transfer efficiency of virus at both interfaces 38 . An exponential dose-response model 39 was used to estimate the probability of infection for a given dose.…”

“…The copyright holder for this this version posted November 23, 2020. ; https://doi.org/10.1101/2020.11.20.20220749 doi: medRxiv preprint 6 expelled per cough, the distance between the mouth and the hand, and the right circular cone angle of the ejected particles, ( Figure S2, Table S1). Transfer from surface-to-hand and from hand-to-mucous membranes was assumed proportional to the concentration of virus on the surface and the transfer efficiency of virus at both interfaces 38 ( Figure S1). The concentration of virus in the contaminated surface was assumed to decay exponentially 52 .…”

Integrated environment-occupant-pathogen information modeling to assess and communicate room-level outbreak risks of infectious diseases

“…To assess pathogen transmission to susceptible hosts, the models such as the environmental infection transmission system modeling framework consider the dynamics of contact and pathogen transfer between individuals via their hands and fomites, pathogen persistence in the environment, pathogen shedding, and recovery of infected individuals. Studies [ [13] , [14] , [15] ] also exploited experimentation approaches to measure the transfer of microbiomes between fomites and humans. The measured microbiological and epidemiological data can be used to assess the transmissibility of the pathogens and used in the models for risk assessment.…”