Amanda Marie Wilson

Interests

Research

risk assessment, environmental infectious disease transmission, occupational health

Teaching

risk assessment, environmental infectious disease transmission, occupational health

Courses

Scholarly Contributions

Journals/Publications

• Abney, S. E., Wilson, A. M., Ijaz, M. K., McKinney, J., Reynolds, K. A., & Gerba, C. P. (2022). Minding the matrix: The importance of inoculum suspensions in finger transfer efficiency. Journal of Applied Microbiology.
• Kerton, K. R., Wilson, A. M., Cabrera, N. L., Daniela, L., Reynolds, K. A., Joyce, L., & Beamer, P. (2022). Risk perceptions of drinking bottled vs. tap water in a low-income Latinx community in Nogales, Arizona. BMC Public Health.
• King, M., Wilson, A. M., Weir, M. H., Lopez-Garcia, M., Proctor, J., Hiwar, W., Khan, A., Fletcher, L. A., Sleigh, P. A., Clifton, I., Dancer, S. J., Wilcox, M., Reynolds, K. A., & Noakes, C. J. (2021). Modeling fomite-mediated SARS-CoV-2 exposure through personal protective equipment doffing in a hospital environment. Indoor Air. doi:10.1111/ina.12938
• Lee, S., Wilson, A. M., Cooksey, E., Boccelli, D., & Verhougstraete, M. (2022). Exploring vulnerable nodes, impactful viral intrusion sites, and viral infection risk reductions offered by chlorine boosters in municipal drinking water networks. Journal of Water Resources Planning and Management.
• Lowe, A. A., Ravi, P., Gerald, L. B., & Wilson, A. M. (2021). The changing job of school nurses during the COVID-19 pandemic: a media content analysis. Annals of Work Exposures and Health.
• Wilson, A. M., Canter, K., Abney, S. E., Gerba, C. P., Myers, E., Hanlin, J., & Reynolds, K. A. (2022). An application for relating Legionella shower monitoring results to estimated health outcomes. Water Research.
• Wilson, A. M., Martin, S. L., Verhougstraete, M., Kendall, A. D., Zimmer-Faust, A. G., Rose, J. B., Bell, M. L., & David, H. W. (2022). Explaining seasonal Bacteriodes thetaiotaomicron and Escherichia coli concentrations in Michigan watersheds for informing microbial risk assessments. Microbiology Spectrum.
• Wilson, A. M., Mussio, I., Chilton, S., Gerald, L. B., Jones, R. M., Drews, F. A., LaKind, J. S., & Beamer, P. I. (2022). A Novel Application of Risk-Risk Tradeoffs in Occupational Health: Nurses' Occupational Asthma and Infection Risk Perceptions Related to Cleaning and Disinfection during COVID-19. International journal of environmental research and public health, 19(23).
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  Nurses face the risk of new onset occupational asthma (OA) due to exposures to cleaning and disinfection (C&D) agents used to prevent infections in healthcare facilities. The objective of this study was to measure nurses' preferences when presented with simultaneous OA and respiratory viral infection (e.g., COVID-19) risks related to increased/decreased C&D activities.
• Wilson, A. M., Ogunseye, O. O., DiGioia, O., Gerald, L. B., & Lowe, A. A. (2022). Barriers to COVID-19 Intervention Implementation in K-5 Classrooms: A Survey of Teachers from a District with Mask Mandates despite a Statewide Mask Mandate Ban. International journal of environmental research and public health, 19(14).
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  The study objective was to characterize K-5 teachers' risk perceptions and experiences with CDC COVID-19 classroom guidance in an Arizona school district with a mask mandate, conflicting with a statewide mask mandate ban.
• Wilson, A. M., Sleeth, D. K., Schaefer, C., & Jones, R. M. (2022). Transmission of Respiratory Viral Diseases to Health Care Workers: COVID-19 as an Example. Annual review of public health.
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  Health care workers (HCWs) can acquire infectious diseases, including coronavirus disease 2019 (COVID-19), from patients. Herein, COVID-19 is used with the source-pathway-receptor framework as an example to assess evidence for the role of aerosol transmission and indirect contact transmission of viral respiratory infectious diseases. Evidence for both routes is strong for COVID-19 and other respiratory viruses, but aerosol transmission is likely dominant for COVID-19. Key knowledge gaps about transmission processes and control strategies include the distribution of viable virus among respiratory aerosols of different sizes, the mechanisms and efficiency by which virus deposited on the facial mucous membrane moves to infection sites inside the body, and the performance of source controls such as face coverings and aerosol containment devices. To ensure that HCWs are adequately protected from infection, guidelines and regulations must be updated to reflect the evidence that respiratory viruses are transmitted via aerosols. Expected final online publication date for the , Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
• Wilson, A. M., Victory, K. R., Reynolds, K. A., Cabrera, N. L., Larson, D., Latura, J., Sexton, J. D., Burgess, J. L., & Beamer, P. (2022). Measured and modeled comparisons of chemical and microbial contaminants in tap, bottled and vended water in a U.S.-Mexico Border community. Environmental Science & Technology: Water.
• King, M. F., Wilson, A. M., López-García, M., Proctor, J., Peckham, D. G., Clifton, I. J., Dancer, S. J., & Noakes, C. J. (2021). Why is mock care not a good proxy for predicting hand contamination during patient care?. The Journal of hospital infection, 109, 44-51.
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  Healthcare worker (HCW) behaviours, such as the sequence of their contacts with surfaces and hand hygiene moments, are important for understanding disease transmission.
• King, M. F., Wilson, A. M., Weir, M. H., López-García, M., Proctor, J., Hiwar, W., Khan, A., Fletcher, L. A., Sleigh, P. A., Clifton, I., Dancer, S. J., Wilcox, M., Reynolds, K. A., & Noakes, C. J. (2021). Modeling fomite-mediated SARS-CoV-2 exposure through personal protective equipment doffing in a hospital environment. Indoor air.
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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.
• Wilson, A. M., & Jones, R. M. (2021). Exploring spatial averaging of contamination in fomite microbial transfer models and implications for dose. Journal of exposure science & environmental epidemiology.
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  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.
• Wilson, A. M., Aviles, N., Petrie, J. I., Beamer, P. I., Szabo, Z., Xie, M., McIllece, J., Chen, Y., Son, Y. J., Halai, S., White, T., Ernst, K. C., & Masel, J. (2021). Quantifying SARS-CoV-2 Infection Risk Within the Google/Apple Exposure Notification Framework to Inform Quarantine Recommendations. Risk analysis.
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  Most early Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, ≥15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long postexposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes' theorem. We capture a 10-fold range of risk using six infectiousness values, 11-fold range using three Bluetooth attenuation bins, ∼sixfold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and ∼11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.
• Wilson, A. M., Jones, R. M., Lugo Lerma, V., Abney, S. E., King, M. F., Weir, M. H., Sexton, J. D., Noakes, C. J., & Reynolds, K. A. (2021). Respirators, face masks, and their risk reductions via multiple transmission routes for first responders within an ambulance. Journal of occupational and environmental hygiene, 18(7), 345-360.
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  First responders may have high SARS-CoV-2 infection risks due to working with potentially infected patients in enclosed spaces. The study objective was to estimate infection risks per transport for first responders and quantify how first responder use of N95 respirators and patient use of cloth masks can reduce these risks. A model was developed for two Scenarios: an ambulance transport with a patient actively emitting a virus in small aerosols that could lead to airborne transmission (Scenario 1) and a subsequent transport with the same respirator or mask use conditions, an uninfected patient; and remaining airborne SARS-CoV-2 and contaminated surfaces due to aerosol deposition from the previous transport (Scenario 2). A compartmental Monte Carlo simulation model was used to estimate the dispersion and deposition of SARS-CoV-2 and subsequent infection risks for first responders, accounting for variability and uncertainty in input parameters (i.e., transport duration, transfer efficiencies, SARS-CoV-2 emission rates from infected patients, etc.). Infection risk distributions and changes in concentration on hands and surfaces over time were estimated across sub-Scenarios of first responder respirator use and patient cloth mask use. For Scenario 1, predicted mean infection risks were reduced by 69%, 48%, and 85% from a baseline risk (no respirators or face masks used) of 2.9 × 10 ± 3.4 × 10 when simulated first responders wore respirators, the patient wore a cloth mask, and when first responders and the patient wore respirators or a cloth mask, respectively. For Scenario 2, infection risk reductions for these same Scenarios were 69%, 50%, and 85%, respectively (baseline risk of 7.2 × 10 ± 1.0 × 10). While aerosol transmission routes contributed more to viral dose in Scenario 1, our simulations demonstrate the ability of face masks worn by patients to additionally reduce surface transmission by reducing viral deposition on surfaces. Based on these simulations, we recommend the patient wear a face mask and first responders wear respirators, when possible, and disinfection should prioritize high use equipment.
• Wilson, A. M., Kaur, K., Jones, R. M., & Kelly, K. E. (2021). Feasibility of a High-Volume Filter Sampler for Detecting SARS-CoV-2 RNA in COVID-19 Patient Rooms. Annals of work exposures and health.
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  Aerosolization of SARS-CoV-2 by COVID-19 patients can put healthcare workers and susceptible individuals at risk of infection. Air sampling for SARS-CoV-2 has been conducted in healthcare settings, but methods vary widely and there is need for improvement. The objective of this study was to evaluate the feasibility of using a high-volume filter sampler, BioCapture z720, to detect SARS-CoV-2 in COVID-19 patient rooms in a medical intensive care unit, a dedicated COVID-19 ward, and at nurses' stations. In some locations, the BioSpot-VIVAS, known for high efficiency in the collection of virus-containing bioaerosols, was also operated. The samples were processed for SARS-CoV-2 RNA with multi-plex nested polymerase chain reaction. One of 28 samples collected with the high-volume filter sampler was positive for SARS-CoV-2; all 6 samples collected with BioSpot-VIVAS were negative for SARS-CoV-2. The high-volume filter sampler was more portable and less intrusive in patient rooms than the BioSpot-VIVAS, but limits of detection remain unknown for this device. This study will inform future work to evaluate the reliability of these types of instruments and inform best practices for their use in healthcare environments for SARS-CoV-2 air sampling.
• Wilson, A. M., King, M. F., López-García, M., Clifton, I. J., Proctor, J., Reynolds, K. A., & Noakes, C. J. (2021). Effects of patient room layout on viral accruement on healthcare professionals' hands. Indoor air, 31(5), 1657-1672.
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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.
• Wilson, A. M., King, M., Lopez-Garcia, M., Clifton, I. J., Proctor, J., Reynolds, K. A., & Noakes, C. J. (2021). Integrating CFD and exposure modeling for estimating viral exposures at the air-surface interface. AIAA, Session: Special Session: CFD and COVID-19. doi:10.2514/6.2021-2740
• Wilson, A. M., Verhougstraete, M. P., Beamer, P. I., King, M. F., Reynolds, K. A., & Gerba, C. P. (2021). Frequency of hand-to-head, -mouth, -eyes, and -nose contacts for adults and children during eating and non-eating macro-activities. Journal of exposure science & environmental epidemiology, 31(1), 34-44.
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  Hand-to-face contacts are important for estimating chemical and microbial exposures. Few studies describe children's hand-to-eye or -nose contacts or adults' hand-to-face contacts. The study objective was to characterize hand-to-head (mouth, eyes, nose, and other) contacts for children in a daycare and adults in multiple locations. Macro-activities and sequences of hand-to-face contacts were recorded for 263 people observed for 30 min each. Statistically significant differences between locations, males and females, adults and children, and during eating and non-eating macro-activities were evaluated. Discrete Markov chains were fit to observed contact sequences and compared among adults and children during eating and non-eating macro-activities. No significant differences in contact frequency were observed between males and females with the exception of hand-to-nose contacts. Children tended to touch the mouth, eyes, and nose more frequently than adults during non-eating macro-activities. Significant differences in contact frequency were observed between locations. Transitional probabilities indicated that children make repetitive mouth, eye, and nose contacts while adults frequently transition to contacts of the head other than the mouth, eyes, or nose. More data are needed to evaluate the effect of age on adults' contact frequencies and to confirm lack of statistically significant differences between adults and children during eating macro-activities.
• Wilson, A. M., Verhougstraete, M. P., Donskey, C. J., & Reynolds, K. A. (2021). An agent-based modeling approach to estimate pathogen exposure risks from wheelchairs. American journal of infection control, 49(2), 206-214.
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  Contributions of contaminated wheelchairs to nosocomial pathogen transmission are relatively unknown. Our aim was to develop a model predicting pathogen exposures for patients utilizing wheelchairs and estimate exposure reduction potential of wheelchair disinfection between rides.
• Wilson, A. M., Weir, M. H., Bloomfield, S. F., Scott, E. A., & Reynolds, K. A. (2021). Modeling COVID-19 infection risks for a single hand-to-fomite scenario and potential risk reductions offered by surface disinfection. American journal of infection control, 49(6), 846-848.
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  We used a quantitative microbial risk assessment approach to relate log disinfection reductions of SARS-CoV-2 bioburden to COVID-19 infection risks. Under low viral bioburden, minimal log reductions may be needed to reduce infection risks for a single hand-to-fomite touch to levels lower than 1:1,000,000, as a risk comparison point. For higher viral bioburden conditions, log reductions of more than 2 may be needed to achieve median infection risks of less than 1:1,000,000.
• Wilson, A. M., Weir, M. H., King, M. F., & Jones, R. M. (2021). Comparing approaches for modelling indirect contact transmission of infectious diseases. Journal of the Royal Society, Interface, 18(182), 20210281.
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  Mathematical models describing indirect contact transmission are an important component of infectious disease mitigation and risk assessment. A model that tracks microorganisms between compartments by coupled ordinary differential equations or a Markov chain is benchmarked against a mechanistic interpretation of the physical transfer of microorganisms from surfaces to fingers and subsequently to a susceptible person's facial mucosal membranes. The primary objective was to compare these models in their estimates of doses and changes in microorganism concentrations on hands and fomites over time. The abilities of the models to capture the impact of episodic events, such as hand hygiene, and of contact patterns were also explored. For both models, greater doses were estimated for the asymmetrical scenarios in which a more contaminated fomite was touched more often. Differing representations of hand hygiene in the Markov model did not notably impact estimated doses but affected pathogen concentration dynamics on hands. When using the Markov model, losses due to hand hygiene should be handled as separate events as opposed to time-averaging expected losses. The discrete event model demonstrated the effect of hand-to-mouth contact timing on the dose. Understanding how model design influences estimated doses is important for advancing models as reliable risk assessment tools.
• Contreras, R. D., Wilson, A. M., Garavito, F., Sexton, J. D., Reynolds, K. A., & Canales, R. A. (2020). Assessing virus infection probability in an office setting using stochastic simulation. Journal of occupational and environmental hygiene, 17(1), 30-37.
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  Viral infections are an occupational health concern for office workers and employers. The objectives of this study were to estimate rotavirus, rhinovirus, and influenza A virus infection risks in an office setting and quantify infection risk reductions for two hygiene interventions. In the first intervention, research staff used an ethanol-based spray disinfectant to clean high-touch non-porous surfaces in a shared office space. The second intervention included surface disinfection and also provided workers with alcohol-based hand sanitizer gel and hand sanitizing wipes to promote hand hygiene. Expected changes in surface concentrations due to these interventions were calculated. Human exposure and dose were simulated using a validated, steady-state model incorporated into a Monte Carlo framework. Stochastic inputs representing human behavior, pathogen transfer efficiency, and pathogen fate were utilized, in addition to a mixed distribution that accounted for surface concentrations above and below a limit of detection. Dose-response curves were then used to estimate infection risk. Estimates of percent risk reduction using mean values from baseline and surface disinfection simulations for rotavirus, rhinovirus, and influenza A infection risk were 14.5%, 16.1%, and 32.9%, respectively. For interventions with both surface disinfection and the promotion of personal hand hygiene, reductions based on mean values of infection risk were 58.9%, 60.8%, and 87.8%, respectively. This study demonstrated that surface disinfection and the use of personal hand hygiene products can help decrease virus infection risk in communal offices. Additionally, a variance-based sensitivity analysis revealed a greater relative importance of surface concentrations, assumptions of relevant exposure routes, and inputs representing human behavior in estimating risk reductions.
• King, M. F., López-García, M., Atedoghu, K. P., Zhang, N., Wilson, A. M., Weterings, M., Hiwar, W., Dancer, S. J., Noakes, C. J., & Fletcher, L. A. (2020). Bacterial transfer to fingertips during sequential surface contacts with and without gloves. Indoor air, 30(5), 993-1004.
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  Bacterial transmission from contaminated surfaces via hand contact plays a critical role in disease spread. However, the fomite-to-finger transfer efficiency of microorganisms during multiple sequential surface contacts with and without gloves has not been formerly investigated. We measured the quantity of Escherichia coli on fingertips of participants after 1-8 sequential contacts with inoculated plastic coupons with and without nitrile gloves. A Bayesian approach was used to develop a mechanistic model of pathogen accretion to examine finger loading as a function of the difference between E coli on surfaces and fingers. We used the model to determine the coefficient of transfer efficiency (λ), and influence of swabbing efficiency and finger area. Results showed that λ for bare skin was higher (49%, 95% CI = 32%-72%) than for gloved hands (30%, CI = 17%-49%). Microbial load tended toward a dynamic equilibrium after four and six contacts for gloved hands and bare skin, respectively. Individual differences between volunteers' hands had a negligible effect compared with use of gloves (P 
• Pearce-Walker, J., Bright, K. R., Canales, R. A., Wilson, A. M., & Verhougstraete, M. (2020). Managing leafy green safety from adenoviruses and enteroviruses in irrigation water. Agricultural Water Management, 240, 106272. doi:10.1016/j.agwat.2020.106272
• Wilson, A. M., Abney, S. E., King, M., Weir, M. H., Lopez-Garcia, M., Sexton, J. D., Dancer, S., Proctor, J., Noakes, C. J., & Reynolds, K. A. (2020). COVID-19 and non-traditional mask use: How do various materials compare in reducing the infection risk for mask wearers?. Journal of Hospital Infection, 105, 640-642. doi:10.1016/j.jhin.2020.05.036
• Wilson, A. M., King, M. F., López-García, M., Weir, M. H., Sexton, J. D., Canales, R. A., Kostov, G. E., Julian, T. R., Noakes, C. J., & Reynolds, K. A. (2020). Evaluating a transfer gradient assumption in a fomite-mediated microbial transmission model using an experimental and Bayesian approach. Journal of the Royal Society, Interface, 17(167), 20200121.
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  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, 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 PFU cm) 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.
• Wilson, A. M., Reynolds, K. A., Jaykus, L. A., Escudero-Abarca, B., & Gerba, C. P. (2020). Comparison of estimated norovirus infection risk reductions for a single fomite contact scenario with residual and nonresidual hand sanitizers. American journal of infection control, 48(5), 538-544.
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  The purpose of this study was to relate experimentally measured log human norovirus reductions for a nonresidual (60% ethanol) and a residual (quaternary ammonium-based) hand sanitizer to infection risk reductions.
• Canales, R. A., Reynolds, K. A., Wilson, A. M., Fankem, S. L., Weir, M. H., Rose, J. B., Abd-Elmaksoud, S., & Gerba, C. P. (2019). Modeling the role of fomites in a norovirus outbreak. Journal of occupational and environmental hygiene, 16(1), 16-26.
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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 hr 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 F 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-to-mouth contacts and the number of hand washing events had strong relationships with model-predicted doses. Predicted illness risks overlapped 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.
• Canales, R. A., Wilson, A. M., Sinclair, R. G., Soto-Beltran, M., Pearce-Walker, J., Molina, M., Penny, M., & Reynolds, K. A. (2019). Microbial study of household hygiene conditions and associated Listeria monocytogenes infection risks for Peruvian women. Tropical medicine & international health : TM & IH, 24(7), 899-921.
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  To develop an exposure and risk assessment model to estimate listeriosis infection risks for Peruvian women.
• Wilson, A. M., Reynolds, K. A., & Canales, R. A. (2019). Estimating the effect of hand hygiene compliance and surface cleaning timing on infection risk reductions with a mathematical modeling approach. American journal of infection control, 47(12), 1453-1459.
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  Quantitative tools are needed to relate infection control interventions to infection risk reductions.
• Wilson, A. M., Reynolds, K. A., Verhougstraete, M. P., & Canales, R. A. (2019). Validation of a Stochastic Discrete Event Model Predicting Virus Concentration on Nurse Hands. Risk Analysis, 39(8), 1812-1824.
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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.
• Canales, R. A., Wilson, A. M., Pearce-Walker, J. I., Verhougstraete, M. P., & Reynolds, K. A. (2018). Methods for Handling Left-Censored Data in Quantitative Microbial Risk Assessment. Applied and environmental microbiology, 84(20).
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  Data below detection limits, left-censored data, are common in environmental microbiology, and decisions in handling censored data may have implications for quantitative microbial risk assessment (QMRA). In this paper, we utilize simulated data sets informed by real-world enterovirus water data to evaluate methods for handling left-censored data. Data sets were simulated with four censoring degrees (low [10%], medium [35%], high [65%], and severe [90%]) and one real-life censoring example (97%) and were informed by enterovirus data assuming a lognormal distribution with a limit of detection (LOD) of 2.3 genome copies/liter. For each data set, five methods for handling left-censored data were applied: (i) substitution with LOD/[Formula: see text], (ii) lognormal maximum likelihood estimation (MLE) to estimate mean and standard deviation, (iii) Kaplan-Meier estimation (KM), (iv) imputation method using MLE to estimate distribution parameters (MI method 1), and (v) imputation from a uniform distribution (MI method 2). Each data set mean was used to estimate enterovirus dose and infection risk. Root mean square error (RMSE) and bias were used to compare estimated and known doses and infection risks. MI method 1 resulted in the lowest dose and infection risk RMSE and bias ranges for most censoring degrees, predicting infection risks at most 1.17 × 10 from known values under 97% censoring. MI method 2 was the next overall best method. For medium to severe censoring, MI method 1 may result in the least error. If unsure of the distribution, MI method 2 may be a preferred method to avoid distribution misspecification. This study evaluates methods for handling data with low (10%) to severe (90%) left-censoring within an environmental microbiology context and demonstrates that some of these methods may be appropriate when using data containing concentrations below a limit of detection to estimate infection risks. Additionally, this study uses a skewed data set, which is an issue typically faced by environmental microbiologists.
• Sexton, J. D., Wilson, A. M., Sassi, H. P., & Reynolds, K. A. (2018). Tracking and controlling soft surface contamination in health care settings. American journal of infection control, 46(1), 39-43.
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  Study objectives were to track the transfer of microbes on soft surfaces in health care environments and determine the efficiency of an Environmental Protection Agency (EPA)-registered soft surface sanitizer in the health care environment.
• Wilson, A. M., Reynolds, K. A., Sexton, J. D., & Canales, R. A. (2018). Modeling Surface Disinfection Needs To Meet Microbial Risk Reduction Targets. Applied and environmental microbiology, 84(18).
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  Nosocomial viral infections are an important cause of health care-acquired infections where fomites have a role in transmission. Using stochastic modeling to quantify the effects of surface disinfection practices on nosocomial pathogen exposures and infection risk can inform cleaning practices. The purpose of this study was to predict the effect of surface disinfection on viral infection risks and to determine needed viral reductions to achieve risk targets. Rotavirus, rhinovirus, and influenza A virus infection risks for two cases were modeled. Case 1 utilized a single fomite contact approach, while case 2 assumed 6 h of contact activities. A 94.1% viral reduction on surfaces and hands was measured following a single cleaning round using an Environmental Protection Agency (EPA)-registered disinfectant in an urgent care facility. This value was used to model the effect of a surface disinfection intervention on infection risk. Risk reductions for other surface-cleaning efficacies were also simulated. Surface reductions required to achieve risk probability targets were estimated. Under case 1 conditions, a 94.1% reduction in virus surface concentration reduced infection risks by 94.1%. Under case 2 conditions, a 94.1% reduction on surfaces resulted in median viral infection risks being reduced by 92.96 to 94.1% and an influenza A virus infection risk below one in a million. Surface concentration in the equations was highly correlated with dose and infection risk outputs. For rotavirus and rhinovirus, a >99.99% viral surface reduction would be needed to achieve a one-in-a-million risk target. This study quantifies reductions of infection risk relative to surface disinfectant use and demonstrates that risk targets for low-infectious-dose organisms may be more challenging to achieve. It is known that the use of EPA-registered surface disinfectant sprays can reduce infection risk if used according to the manufacturer's instructions. However, there are currently no standards for health care environments related to contamination levels on surfaces. The significance of this research is in quantifying needed reductions to meet various risk targets using realistic viral concentrations on surfaces for health care environments. This research informs the design of cleaning protocols by demonstrating that multiple applications may be needed to reduce risk and by highlighting a need for more models exploring the relationship among microbial contamination of surfaces, patient and health care worker behaviors, and infection risks.

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• Lowe, A. A., Ravi, P., Gerald, L. B., & Wilson, A. M. (2023. The Changing Job of School Nurses during the COVID-19 Pandemic: A Media Content Analysis of Contributions to Stress(pp 101-117).
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  School nurses and unlicensed assistive personnel (UAPs) are essential to the health and wellness of school children. However, most US schools do not have a full-time licensed nurse. During the COVID-19 pandemic, school nurses and UAPs have been integral in ensuring that the health needs of students were met. They have seen a marked increase in their responsibilities included implementing COVID-19 mitigation strategies, screening for symptoms, testing students and staff, conducting contact tracing and data collection, and ensuring the implementation of rapidly changing COVID-19 guidelines and protocols for schools. The objective of this study was to explore COVID-19 occupational changes and their contributions to stress among school nurses and UAPs through a content analysis of local and national media articles. A Google search of articles published between February 2020 and September 2021 was conducted using the following search terms: 'school nurse', 'COVID-19', 'health aide', 'stress', and 'experiences'. A search was also conducted in Nexis Uni. Articles were included if the topic discussed school nurses or UAPs and COVID-19. All articles that examined nurses in other settings were excluded from the review. We examined topics and themes temporally (from February 2020 to September 2021) and spatially (i.e. the frequency by US state). Overall, 496 media articles discussing school nurses and COVID-19 were included in our review. The highest volume of articles was from September 2021 (22%, 111/496). Other months with relatively high volume of articles included August 2020 (9%, 43/496), January 2021 (10%, 47/496), February 2021 (9%, 44/496), and August 2021 (8%, 39/496). These larger article volumes coincided with notable COVID-19 events, including returning to school in the fall (August 2020 and August 2021), school nurses assisting with vaccine rollouts among adults in the USA (January/February 2021), concerns regarding the delta variant (August/September 2021), and vaccine rollouts for children ages 12-15 (September 2021). The representation of articles spatially (national, state, regional, or local) was 66 (13%) articles at national level, 217 (44%) state level, 25 (5%) regional level, and 188 (38%) local news at the city and/or village level. Pennsylvania had the highest frequency of articles, but when standardized to the state population, Alaska had the highest rate of media per 100 000 people. Three major themes were identified in our analysis: (i) safety; (ii) pandemic-related fatigue/stress; and (iii) nursing shortage/budget. The most represented theme for articles before September 2021 was that of safety. Over time, the themes of pandemic-related fatigue/stress and nursing shortage/budget increased with the most notable increase being in September 2021. The COVID-19 pandemic has resulted in new occupational risks, burdens, and stressors experienced by school nurses and UAPs. School nurses play a critical role in disease surveillance, disaster preparedness, wellness and chronic disease prevention interventions, immunizations, mental health screening, and chronic disease education. Furthermore, they provide a safety net for our most vulnerable children. Given that school nurses were already over-burdened and under-resourced prior to the pandemic, characterization of these new burdens and stressors will inform emergency preparedness resources for school health personnel during future pandemics or outbreaks.