Research gaps and priorities for quantitative microbial risk assessment (QMRA).

The 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.

Meta-Analysis Addressing the Implications of Model Uncertainty in Understanding the Persistence of Indicators and Pathogens in Natural Surface Waters.

This study evaluates the impact persistence model selection has on the prediction of persistence values of interest and the identification of influential water quality and environmental factors for microorganisms in natural surface waters. Five persistence models representing first-order decay and nonlinear decay profiles were fit to a comprehensive database of 629 data sets for fecal indicator bacteria (FIB), bacteriophages, bacteria, viruses, and protozoa mined from the literature. Initial periods of minimal decay and decay rates tapering off over time were often observed, and a two-parameter model, based on the logistic probability distribution, provided the best fit to the data most frequently. First-order decay kinetics provided the best fit to less than 20% of the analyzed data. Using the best fitting models in this analysis, T90 and T99 metrics were calculated for each data set and used as the dependent variable in a variety of exploratory factor analyses. Random forest methods identified temperature and predation as some of the most important water quality factors influencing persistence, and the protozoa target type differed the most from FIB. This analysis further confirmed the interactions between temperature and predation and suggests that pH and turbidity be more frequently documented in persistence studies to further elucidate their impact on target persistence. The findings from this analysis and the calculated persistence metrics can be used to better inform quantitative microbial risk assessments and may lead to improved predictions of human health risks and water management decisions.

Global systemic risk and resilience for novel coronavirus in postpandemic era.

The ongoing pandemic has evolved and is posing diverse challenges for the world. Countermeasures for risks are needed to address both direct and indirect effects of disease on the healthcare system, economic and industrial sectors, governance, environment, transportation, energy, and communication systems. There are indicators of a forthcoming postpandemic era. The rethinking and reevaluation of policies adopted throughout the pandemic are ongoing to address cascading threats of emerging and reemerging infectious diseases. The first Special Issue introduced the topic. This second Special Issue describes international collaboration and innovation for pandemic risk and resilience, with a focus on future policy and operations of global systems toward a postandemic era.

Development and application of a dose-response model for Elizabethkingia spp.

Elizabethkingia spp. are common environmental pathogens responsible for infections in more vulnerable populations. Although the exposure routes of concern are not well understood, some hospital-associated outbreaks have indicated possible waterborne transmission. In order to facilitate quantitative microbial risk assessment (QMRA) for Elizabethkingia spp., this study fit dose-response models to frog and mice datasets that evaluated intramuscular and intraperitoneal exposure to Elizabethkingia spp. The frog datasets could be pooled, and the exact beta-Poisson model was the best fitting model with optimized parameters α  = 0.52 and ß = 86,351. Using the exact beta-Poisson model, the dose of Elizabethkingia miricola resulting in a 50% morbidity response (LD50 ) was estimated to be approximately 237,000 CFU. The model developed herein was used to estimate the probability of infection for a hospital patient under a modeled exposure scenario involving a contaminated medical device and reported Elizabethkingia spp. concentrations isolated from hospital sinks after an outbreak. The median exposure dose was approximately 3 CFU/insertion event, and the corresponding median risk of infection was 3.4E-05. The median risk estimated in this case study was lower than the 3% attack rate observed in a previous outbreak, however, there are noted gaps pertaining to the possible concentrations of Elizabethkingia spp. in tap water and the most likely exposure routes. This is the first dose-response model developed for Elizabethkingia spp. thus enabling future risk assessments to help determine levels of risk and potential effective risk management strategies.

Global Systemic Risk and Resilience for Novel Coronavirus and COVID-19.

This Special Issue is dedicated to issues and challenges related to pandemic risk and resilience, with a focus on policy and operations of global systems in the COVID-19 pandemic. The cascading effects of emerging and reemerging infectious diseases to the global economy are a critical interest. Measures to confront the ongoing pandemic are an urgent need. Data analysis at regional and global scales is helping to prioritize response and resilience across locations of high risks. The risk sciences are available for addressing human health and infection risks; the evaluation of risk management strategies and tradeoffs; risk perception as it relates to information processing and receiving risk communication; and tracking system resilience as it relates to various imposed measures.

Modeling the Dose Response Relationship of Waterborne Acanthamoeba.

This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to the pathogens. The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta-Poisson model. The HN-3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD50 of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free-living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free-living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival.

Impacts of Municipal Water-Rainwater Source Transitions on Microbial and Chemical Water Quality Dynamics at the Tap.

When rainwater harvesting is utilized as an alternative water resource in buildings, a combination of municipal water and rainwater is typically required to meet water demands. Altering source water chemistry can disrupt pipe scale and biofilm and negatively impact water quality at the distribution level. Still, it is unknown if similar reactions occur within building plumbing following a transition in source water quality. The goal of this study was to investigate changes in water chemistry and microbiology at a green building following a transition between municipal water and rainwater. We monitored water chemistry (metals, alkalinity, and disinfectant byproducts) and microbiology (total cell counts, plate counts, and opportunistic pathogen gene markers) throughout two source water transitions. Several constituents including alkalinity and disinfectant byproducts served as indicators of municipal water remaining in the system since the rainwater source does not contain these constituents. In the treated rainwater, microbial proliferation and Legionella spp. gene copy numbers were often three logs higher than those in municipal water. Because of differences in source water chemistry, rainwater and municipal water uniquely interacted with building plumbing and generated distinctively different drinking water chemical and microbial quality profiles.

Ebola Virus Dose Response Model for Aerosolized Exposures: Insights from Primate Data.

This study develops dose-response models for Ebolavirus using previously published data sets from the open literature. Two such articles were identified in which three different species of nonhuman primates were challenged by aerosolized Ebolavirus in order to study pathology and clinical disease progression. Dose groups were combined and pooled across each study in order to facilitate modeling. The endpoint of each experiment was death. The exponential and exact beta-Poisson models were fit to the data using maximum likelihood estimation. The exact beta-Poisson was deemed the recommended model because it more closely approximated the probability of response at low doses though both models provided a good fit. Although transmission is generally considered to be dominated by person-to-person contact, aerosolization is a possible route of exposure. If possible, this route of exposure could be particularly concerning for persons in occupational roles managing contaminated liquid wastes from patients being treated for Ebola infection and the wastewater community responsible for disinfection. Therefore, this study produces a necessary mathematical relationship between exposure dose and risk of death for the inhalation route of exposure that can support quantitative microbial risk assessment aimed at informing risk mitigation strategies including personal protection policies against occupational exposures.

Development of a dose-response model for Naegleria fowleri.

This study develops novel dose-response models for Naegleria fowleri from selected peer-reviewed experiments on the virulence based on the intranasal exposure pathway. One data set measured the response of mice intranasally inoculated with the amebae and the other study addressed the response of mice swimming in N. fowleri infected water. The measured response for both studies was death. All experimental data were best fit by the beta-Poisson dose-response model. The three swimming experiments could be pooled, and this is the final recommended model with an LD50 of 13,257 amebae. The results of this study provide a better estimate of the probability of the risk to N. fowleri exposure than the previous models developed based on an intravenous exposure. An accurate dose-response model is the first step in quantifying the risk of free-living amebae like N. fowleri, which pose risks in recreational environments and have been detected in drinking water and premise plumbing systems. A better understanding of this risk will allow for risk management that limits the ability for pathogen growth, proliferation, and exposure.

A Case Study Evaluating the Risk of Infection from Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV) in a Hospital Setting Through Bioaerosols.

Middle Eastern respiratory syndrome, an emerging viral infection with a global case fatality rate of 35.5%, caused major outbreaks first in 2012 and 2015, though new cases are continuously reported around the world. Transmission is believed to mainly occur in healthcare settings through aerosolized particles. This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies. The exposure scenario includes a single index patient emitting virus-containing aerosols into the air by coughing, leading to short- and long-range airborne exposures for other patients in the same room, nurses, healthcare workers, and family visitors. Aerosol transport modeling was coupled with Monte Carlo simulation to evaluate the risk of MERS illness for the exposed population. Results from a typical scenario show the daily mean risk of infection to be the highest for the nurses and healthcare workers (8.49 × 10-4 and 7.91 × 10-4 , respectively), and the lowest for family visitors and patients staying in the same room (3.12 × 10-4 and 1.29 × 10-4 , respectively). Sensitivity analysis indicates that more than 90% of the uncertainty in the risk characterization is due to the viral concentration in saliva. Assessment of risk interventions showed that respiratory masks were found to have a greater effect in reducing the risks for all the groups evaluated (>90% risk reduction), while increasing the air exchange was effective for the other patients in the same room only (up to 58% risk reduction).

Evaluation of the Influenza Risk Reduction from Antimicrobial Spray Application on Porous Surfaces.

Antimicrobial spray products are used by millions of people around the world for cleaning and disinfection of commonly touched surfaces. Influenza A is a pathogen of major concern, leading to up to 49,000 deaths and 114,000 hospitalizations per year in the United States alone. One of the recognized routes of transmission for influenza A is by transfer of viruses from surfaces to hands and subsequently to mucous membranes. Therefore, routine cleaning and disinfection of surfaces is an important part of the environmental management of influenza A. While the emphasis is generally on spraying hard surfaces and laundering cloth and linens with high temperature machine drying, not all surfaces can be treated in this manner. The quantitative microbial risk assessment (QMRA) approach was used to develop a stochastic risk model for estimating the risk of infection from indirect contact with porous fomite with and without surface treatment with an antimicrobial spray. The data collected from laboratory analysis combined with the risk model show that influenza A infection risk can be lowered by four logs after using an antimicrobial spray on a porous surface. Median risk associated with a single touch to a contaminated fabric was estimated to be 1.25 × 10-4 for the untreated surface, and 3.6 × 10-8 for the treated surface as a base case assumption. This single touch scenario was used to develop a generalizable model for estimating risks and comparing scenarios with and without treatment to more realistic multiple touch scenarios over time periods and with contact rates previously reported in the literature. The results of this study and understanding of product efficacy on risk reduction inform and broaden the range of risk management strategies for influenza A by demonstrating effective risk reduction associated with treating nonporous fomites that cannot be laundered at high temperatures.

Development of a microbial dose response visualization and modelling application for QMRA modelers and educators.

Microbial dose response modelling is vital to a well-characterized microbial risk estimate. Dose response modelling is an inherently multidisciplinary field, which collates knowledge and data from disparate scientific fields. This multidisciplinary nature presents a key challenge to the expansion of microbial dose response modelling into new groups of researchers and modelers. This research employs a dose response optimization R code used in 18 peer-reviewed research studies to develop a multi-functional dose response software. The underlying R code performs an optimization of the two primary dose response models using the MLE method and outputs statistical analyses of the fits and bootstrapped uncertainty information for the models. VizDR (Visual Dose Response) was developed to provide microbial dose response modelling capabilities to a larger audience. VizDR is programmed in JavaScript with underlying Python scripts for intercommunication with Rserve. VizDR allows for dose response model visualization and optimization of a user's own experimental data.

Development and evaluation of an intensive short course: the Quantitative Microbial Risk Assessment Interdisciplinary Instructional Institute (QMRA III).

Quantitative microbial risk assessment (QMRA) is a growing interdisciplinary field addressing exposures to microbial pathogens and infectious disease processes. Risk science is inherently interdisciplinary, but few of the contributing disciplinary programs offer courses and training specifically in QMRA. To develop multidisciplinary training in QMRA, an annual 10-day long intensive workshop was conducted from 2015 to 2019-the Quantitative Microbial Risk Assessment Interdisciplinary Instructional Institute (QMRA III). National leaders in the fields of public health, engineering, microbiology, epidemiology, communications, public policy, and QMRA served as instructors and mentors over the course of the program. To provide cross-training, multidisciplinary teams of 5-6 trainees were created from the approximately 30 trainees each year. A formal assessment of the program was performed based on observations and surveys containing Likert-type scales and open-ended prompts. In addition, a longitudinal alumni survey was also disseminated to facilitate the future redevelopment of QMRA institutes and determine the impact of the program. Across all years, trainees experienced statistically significant increases (P < 0.05) in their perceptions of their QMRA abilities (e.g., use of specific computer programs) and knowledge of QMRA constructs (e.g., risk management). In addition, 12 publications, three conference presentations, and two research grants were derived from the QMRA III institute projects or tangential research. The success of QMRA III indicates that a short course format can effectively address many multidisciplinary training needs. Key features of QMRA III, including the inter-disciplinary training approach, hands-on exercises, real-world institute projects, and interaction through a mentoring process, were vital for training multidisciplinary teams housing multiple forms of expertise. Future QMRA institutes are being redeveloped to leverage hybrid learning formats that can further the multidisciplinary training and mentoring objectives.

Memory and Traumatic Brain Injury: Assessment and Management Practices of Speech-Language Pathologists.

PURPOSE: Memory impairments are among the most commonly reported deficits and among the most frequent rehabilitation targets for individuals with traumatic brain injury (TBI). Memory and learning are also critical for rehabilitation success and broader long-term outcomes. Speech-language pathologists (SLPs) play a central role in memory management for individuals with TBI across the continuum of care. Yet, little is known about the current practice patterns of SLPs for post-TBI memory disorders. This study aims to examine the clinical management of memory disorders in adults with TBI by SLPs and identify opportunities to improve post-TBI memory outcomes. METHOD: SLPs from across the continuum of care were recruited to complete an online survey. The survey assessed key practice areas specific to memory and memory disorders post-TBI, including education and training, knowledge and confidence, and assessment and treatment patterns. RESULTS: Surveys from 155 SLPs were analyzed. Results revealed that TBI-specific training remains low in the field. Respondents varied in their practice patterns in assessing and treating memory disorders. Most SLPs do not appear to have access to appropriate standardized assessments to measure unique forms of memory. Respondents also reported a range of barriers and opportunities to advance memory outcomes following TBI and provided suggestions of areas in which they would like to see more basic and clinical research. CONCLUSIONS: These findings establish a baseline of the current practices for clinical management of memory impairment in adults with TBI by SLPs. Improved opportunities for clinician training, the development of a single tool to assess multiple forms of memory, better access to existing memory assessments, and implementation of evidence-based interventions promise to lead to improved memory outcomes for individuals with TBI.

Diversity of Research Participant Gender, Race, and Ethnicity in Communication Sciences and Disorders: A Systematic Review and Quantitative Synthesis of American Speech-Language-Hearing Association Publications in 2020.

Purpose: One manifestation of systemic inequities in communication sciences and disorders (CSD) is the chronic underreporting and underrepresentation of sex, gender, race, and ethnicity in research. The present study characterized recent demographic reporting practices and representation of participants across CSD research. Methods: We systematically reviewed and extracted key reporting and participant data from empirical studies conducted in the United States (US) with human participants published in the year 2020 in journals by the American Speech-Language-Hearing Association (ASHA; k = 407 articles comprising a total n = 80,058 research participants, search completed November 2021). Sex, gender, race, and ethnicity were operationalized per National Institutes of Health guidelines (National Institutes of Health, 2015a, 2015b). Results: Sex or gender was reported in 85.5% of included studies; race was reported in 33.7%; and ethnicity was reported in 13.8%. Sex and gender were clearly differentiated in 3.4% of relevant studies. Where reported, median proportions for race and ethnicity were significantly different from the US population, with underrepresentation noted for all non-White racial groups and Hispanic participants. Moreover, 64.7% of studies that reported sex or gender and 67.2% of studies that reported race or ethnicity did not consider these respective variables in analyses or discussion. Conclusion: At present, research published in ASHA journals frequently fails to report key demographic data summarizing the characteristics of participants. Moreover, apparent gaps in representation of minoritized racial and ethnic groups threaten the external validity of CSD research and broader health care equity endeavors in the US. Although our study is limited to a single year and publisher, our results point to several steps for readers that may bring greater accountability, consistency, and diversity to the discipline.

Listeriosis Risk Model for Cancer Patients Who Consume Ready-to-Eat Salad.

The foodborne pathogen Listeria monocytogenes generally infects immunocompromised individuals, such as cancer patients, more frequently and with higher morbidity and mortality than the general population. Because of the anticipated risk associated with L. monocytogenes and other pathogens in produce, immunocompromised individuals are often placed on neutropenic diets that exclude fresh produce, though these risks have not been quantified. Therefore, this study developed a data-driven risk model for listeriosis in cancer patients who consume ready-to-eat (RTE) salads, consisting of leafy greens, cucumbers, and tomatoes, as influenced by kitchen-scale treatments and storage practices. Monte Carlo simulations were used to model the risk of invasive listeriosis during one chemotherapy cycle. Refrigerating all salad components decreased the median risk by approximately one-half log. For refrigerated salads with no treatment, the predicted median risk was ≤ 4.3 × 10-08. When salad ingredients were surface blanched with greens rinsed, the predicted risk decreased to 5.4 × 10-10. Predicted risk was lowest (1.4 × 10-13) for a blanched "salad" consisting of solely cucumbers and tomatoes. Interestingly, rinsing, as recommended by FDA, only decreased the median risk by 1 log. A sensitivity analysis revealed that the highly variable dose-response parameter k strongly influenced risk, indicating that reducing uncertainty in this variable may improve model accuracy. Overall, this study demonstrates that kitchen-scale pathogen reduction approaches have high risk reduction efficacy and could be considered as an alternative to diets that exclude produce when making risk management decisions.

Problem-solving interventions and depression among adolescents and young adults: A systematic review of the effectiveness of problem-solving interventions in preventing or treating depression.

Problem-solving (PS) has been identified as a therapeutic technique found in multiple evidence-based treatments for depression. To further understand for whom and how this intervention works, we undertook a systematic review of the evidence for PS's effectiveness in preventing and treating depression among adolescents and young adults. We searched electronic databases (PsycINFO, Medline, and Cochrane Library) for studies published between 2000 and 2022. Studies meeting the following criteria were included: (a) the intervention was described by authors as a PS intervention or including PS; (b) the intervention was used to treat or prevent depression; (c) mean or median age between 13-25 years; (d) at least one depression outcome was reported. Risk of bias of included studies was assessed using the Cochrane Risk of Bias 2.0 tool. A narrative synthesis was undertaken given the high level of heterogeneity in study variables. Twenty-five out of 874 studies met inclusion criteria. The interventions studied were heterogeneous in population, intervention, modality, comparison condition, study design, and outcome. Twelve studies focused purely on PS; 13 used PS as part of a more comprehensive intervention. Eleven studies found positive effects in reducing depressive symptoms and two in reducing suicidality. There was little evidence that the intervention impacted PS skills or that PS skills acted as a mediator or moderator of effects on depression. There is mixed evidence about the effectiveness of PS as a prevention and treatment of depression among AYA. Our findings indicate that pure PS interventions to treat clinical depression have the strongest evidence, while pure PS interventions used to prevent or treat sub-clinical depression and PS as part of a more comprehensive intervention show mixed results. Possible explanations for limited effectiveness are discussed, including missing outcome bias, variability in quality, dosage, and fidelity monitoring; small sample sizes and short follow-up periods.

Identifying water quality and environmental factors that influence indicator and pathogen decay in natural surface waters.

Biphasic decay has been observed for indicators and pathogens in bench-scale and in-situ water experiments for decades, however, first-order decay kinetics continue to be applied to persistence data because of their simplicity and ease of application. Model uncertainty introduced by broadly applying first-order decay kinetics to persistence data may lead to erroneous decision making in the fields of water management and protection. As surface waters are exposed to highly variable environmental and water quality factors that influence microbial and viral persistence, it is expected that first-order decay kinetics are not representative of most of the persistence literature for indicators and pathogens in surface water matrices. This review compiled the methods and results of 61 studies that conducted experiments evaluating the persistence of fecal indicator bacteria (FIB), bacteriophages, pathogenic bacteria, viruses, and protozoa in natural surface water matrices. The goals of this review were trifold: (1) collate studies in the literature with data available for future persistence modeling, (2) present the current state of knowledge with regards to the environmental and water quality factors affecting persistence in natural surface waters, and (3) identify recurrent evidence for interactions between the frequently studied factors to inform future factor analyses. Comparing the methods and results across the 61 studies suggest potential interactions between sunlight and water type; sunlight and method of detection; predation and water type; predation and temperature; and water type and method of detection. The majority of the identified literature evaluated FIB or bacteria persistence; future experiments are needed that focus on protozoa, brackish or marine water types, and molecular-based methods of detection.

Persistence of poliovirus types 2 and 3 in waste-impacted water and sediment.

Eradication of poliovirus (PV) is a global public health priority, and as clinical cases decrease, the role of environmental surveillance becomes more important. Persistence of PV and the environmental factors that influence it (such as temperature and sample type) are an important part of understanding and interpreting positive environmental surveillance samples. The objective of this study was to evaluate the persistence of poliovirus type 2 (PV2) and type 3 (PV3) in wastewater and sediment. Microcosms containing either 1) influent wastewater or 2) influent wastewater with a sediment matrix were seeded with either PV2 or PV3, and stored for up to 126 days at three temperatures (4°C, room temperature [RT], and 30°C). Active PV in the liquid of (1), and the sediment and liquid portions of (2) were sampled and quantified at up to 10 time points via plaque assay and RT-qPCR. A suite of 17 models were tested for best fit to characterize decay of PV2 and PV3 over time and determine the time points at which >90% (T90) and >99% (T99) reduction was reached. Linear models assessed the influence of experimental factors (matrix, temperature, virus type and method of detection) on the predicted T90 and T99 values. Results showed that when T90 was the dependent variable, virus type, matrix, and temperature significantly affected decay, and there was a clear interaction between the sediment matrix and temperature. When T99 was the dependent variable, only temperature and matrix type significantly influenced the decay metric. This study characterizes the persistence of both active and molecular PV2 and PV3 in relevant environmental conditions, and demonstrates that temperature and sediment both play important roles in PV viability. As eradication nears and clinical cases decrease, environmental surveillance and knowledge of PV persistence will play a key role in understanding the silent circulation in endemic countries.