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AbstractUnderstanding 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.

UA Open Access Publishing Fund ; Rapid molecular testing methods are poised to replace many of the conventional, culturebased tests currently used in fields such as water quality and food science. Rapid qPCR methods have the benefit of being faster than conventional methods and provide a means to more accurately protect public health. However, many scientists and technicians in water and food quality microbiology laboratories have limited experience using these molecular tests. To ensure that practitioners can use and implement qPCR techniques successfully, we developed a week long workshop to provide hands-on training and exposure to rapid molecular methods for water quality management. This workshop trained academic professors, government employees, private industry representatives, and graduate students in rapid qPCR methods for monitoring recreational water quality. Attendees were immersed in these new methods with hands-on laboratory sessions, lectures, and one-on-one training. Upon completion, the attendees gained sufficient knowledge and practice to teach and share these new molecular techniques with colleagues at their respective laboratories. Key findings from this workshop demonstrated: 1) participants with no prior experience could be effectively trained to conduct highly repeatable qPCR analysis in one week; 2) participants with different desirable outcomes required exposure to a range of different platforms and sample processing approaches; and 3) the collaborative interaction amongst newly trained practitioners, workshop leaders, and members of the water quality community helped foster a cohesive cohort of individuals which can advocate powerful cohort for proper implementation of molecular methods. ; This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.

Rapid molecular testing methods are poised to replace many of the conventional, culture-based tests currently used in fields such as water quality and food science. Rapid qPCR methods have the benefit of being faster than conventional methods and provide a means to more accurately protect public health. However, many scientists and technicians in water and food quality microbiology laboratories have limited experience using these molecular tests. To ensure that practitioners can use and implement qPCR techniques successfully, we developed a week long workshop to provide hands-on training and exposure to rapid molecular methods for water quality management. This workshop trained academic professors, government employees, private industry representatives, and graduate students in rapid qPCR methods for monitoring recreational water quality. Attendees were immersed in these new methods with hands-on laboratory sessions, lectures, and one-on-one training. Upon completion, the attendees gained sufficient knowledge and practice to teach and share these new molecular techniques with colleagues at their respective laboratories. Key findings from this workshop demonstrated: 1) participants with no prior experience could be effectively trained to conduct highly repeatable qPCR analysis in one week; 2) participants with different desirable outcomes required exposure to a range of different platforms and sample processing approaches; and 3) the collaborative interaction amongst newly trained practitioners, workshop leaders, and members of the water quality community helped foster a cohesive cohort of individuals which can advocate powerful cohort for proper implementation of molecular methods.

AbstractThe coronavirus disease 2019 pandemic highlighted the need for more rapid and routine application of modeling approaches such as quantitative microbial risk assessment (QMRA) for protecting public health. QMRA is a transdisciplinary science dedicated to understanding, predicting, and mitigating infectious disease risks. To better equip QMRA researchers to inform policy and public health management, an Advances in Research for QMRA workshop was held to synthesize a path forward for QMRA research. We summarize insights from 41 QMRA researchers and experts to clarify the role of QMRA in risk analysis by (1) identifying key research needs, (2) highlighting emerging applications of QMRA; and (3) describing data needs and key scientific efforts to improve the science of QMRA. Key identified research priorities included using molecular tools in QMRA, advancing dose–response methodology, addressing needed exposure assessments, harmonizing environmental monitoring for QMRA, unifying a divide between disease transmission and QMRA models, calibrating and/or validating QMRA models, modeling co‐exposures and mixtures, and standardizing practices for incorporating variability and uncertainty throughout the source‐to‐outcome continuum. Cross‐cutting needs identified were to: develop a community of research and practice, integrate QMRA with other scientific approaches, increase QMRA translation and impacts, build communication strategies, and encourage sustainable funding mechanisms. Ultimately, a vision for advancing the science of QMRA is outlined for informing national to global health assessments, controls, and policies.