Citizen science initiatives document biodiversity baselines at an urban lake.

Changes to biodiversity from urbanization are occurring worldwide, and baseline data is vital to document the magnitude and direction of these alterations. We set out to document the biodiversity of an urban lake in Eastern Iowa that was devoid of baseline data prior to a renovation project that will convert the site into a major area for human recreation. Throughout the course of one year, we studied the biodiversity at Cedar Lake utilizing the citizen-science application iNaturalist coupled with semi-structured BioBlitz events, which we compared to previous opportunistic observations at the site. From a semi-structured approach to document biodiversity with citizen science, our analyses revealed more diverse community metrics over a shorter period compared to more than a decade of prior observations.

Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment.

With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.

Identifying predictors of COVID-related delays in cancer-specific medical care.

PURPOSE: Evidence of the impact of the COVID-19 pandemic on cancer prevention and control is growing, but little is known about patient-level factors associated with delayed care. We analyzed data from a survey focused on Iowan cancer patients' COVID-19 experiences in the early part of the pandemic. METHODS: Participants were recruited from the University of Iowa Holden Comprehensive Cancer Center's Patients Enhancing Research Collaborations at Holden (PERCH) program. We surveyed respondents on demographic characteristics, COVID-19 experiences and reactions, and delays in any cancer-related health care appointment, or cancer-related treatment appointments. Two-sided significance tests assessed differences in COVID-19 experiences and reactions between those who experienced delays and those who did not. RESULTS: There were 780 respondents (26% response), with breast, prostate, kidney, skin, and colorectal cancers representing the majority of respondents. Delays in cancer care were reported by 29% of respondents. In multivariable-adjusted models, rural residents (OR 1.47; 95% CI 1.03, 2.11) and those experiencing feelings of isolation (OR 2.18; 95% CI 1.37, 3.47) were more likely to report any delay, where experiencing financial difficulties predicted delays in treatment appointments (OR 5.72; 95% CI 1.96, 16.67). Health insurance coverage and concern about the pandemic were not statistically significantly associated with delays. CONCLUSION: These findings may inform cancer care delivery during periods of instability when treatment may be disrupted by informing clinicians about concerns that patients have during the treatment process. Future research should assess whether delays in cancer care impact long-term cancer outcomes and whether delays exacerbate existing disparities in cancer outcomes.

Detection of lymphoproliferative disease virus in Iowa Wild Turkeys (Meleagris gallopavo): Comparison of two sections of the proviral genome.

An accurate diagnostic test is an essential aspect of successfully monitoring and managing wildlife diseases. Lymphoproliferative Disease Virus (LPDV) is an avian retrovirus that was first identified in domestic turkeys in Europe and was first reported in a Wild Turkey (Meleagris gallopavo) in the United States in 2009. It has since been found to be widely distributed throughout North America. The majority of studies have utilized bone marrow and PCR primers targeting a 413-nucleotide sequence of the gag gene of the provirus to detect infection. While prior studies have evaluated the viability of other tissues for LPDV detection (whole blood, spleen, liver, cloacal swabs) none to date have studied differences in detection rates when utilizing different genomic regions of the provirus. This study examined the effectiveness of another section of the provirus, a 335-nucleotide sequence starting in the U3 region of the LTR (Long Terminal Repeat) and extending into the Matrix of the gag region (henceforth LTR), for detecting LPDV. Bone marrow samples from hunter-harvested Wild Turkeys (n = 925) were tested for LPDV with the gag gene and a subset (n = 417) including both those testing positive and those where LPDV was not detected was re-tested with LTR. The positive percent agreement (PPA) was 97.1% (68 of 70 gag positive samples tested positive with LTR) while the negative percent agreement (NPA) was only 68.0% (236 of 347 gag negative samples tested negative with LTR). Cohen's Kappa (κ = 0.402, Z = 10.26, p<0.0001) and the McNemar test (OR = 55.5, p<0.0001) indicated weak agreement between the two gene regions. We found that in Iowa Wild Turkeys use of the LTR region identified LPDV in many samples in which we failed to detect LPDV using the gag region and that LTR may be more appropriate for LPDV surveillance and monitoring. However, neither region of the provirus resulted in perfect detection and additional work is necessary to determine if LTR is more reliable in other geographic regions where LPDV occurs.

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells.

Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018-2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018-19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57-99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO3-N), median intake from water was 44 % (IQR: 26-72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R2 = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R2 = 0.52) as diet (R2 = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.

Potential for managing pool levels in a flood-control reservoir to increase nitrate-nitrogen load reductions.

Few strategies are available to reduce nitrate-nitrogen (NO3 -N) loads at larger landscape scales, but flood control reservoirs are known to reduce riverine loads. In this study, we evaluated the potential to increase nitrogen (N) loss at Lake Red Rock, a large reservoir located in central Iowa, by evaluating the inundation of sediments deposited at the reservoir inflow. Sediment samples were collected at 51 locations in the lower delta region and analyzed for particle size and nutrient content. Nitrogen loss rates in delta sediments were determined from laboratory assays, and satellite imagery was used to develop a rating curve to quantify land area inundated within the delta. The daily mass of NO3 -N reduced with delta inundation was estimated by applying the mean N 24-h loss rate (0.66 g N m2 day-1 ) by the area of inundation (m2 ). Results indicated that raising pool elevations to inundate more of the delta would result in greater N losses, ranging from 2 to 377 Mg per year. Potential N loss of 102 Mg achieved by increasing pool stage by 0.5 m would be equivalent to installing nearly 650 edge-of-field practices in the watershed. Although more work is needed to integrate with an existing environmental pool management plan, study results indicate that reservoir management could achieve N reductions at a novel landscape scale.

Tendencies for Comparing Up and Down: An Examination of the Directional Subscales of the Iowa-Netherlands Comparison Orientation Measure.

People vary in their individual tendencies to compare to others-referred to as social comparison orientation (SCO). Researchers have heretofore developed and validated a scale to assess SCO-the Iowa-Netherlands Comparison Orientation Measure (INCOM). The standard INCOM assesses non-directional comparisons, but not directional comparisons to better- and worse-off others. The goal of the present research was to examine the factor structure and validity of directional (and non-directional) comparison tendencies using the expanded INCOM. Across four archival studies and one pre-registered study using student and non-student samples, we provide evidence for 1) a 3-factor structure for the INCOM with non-directional, directional-upward, and directional-downward SCO dimensions, 2) inter-correlations among the SCO dimensions suggesting convergent validity of the directional scales, 3) greater endorsement of non-directional, then directional-upward, and directional-downward SCO, 4) lower SCO among older individuals and members of racial/ethnic minority groups, and 5) strong and consistent associations of directional-upward SCO with well-being and affect, appearance beliefs (e.g., body satisfaction), social emotions (e.g., envy), and agency-related motivations and consequences in interpersonal contexts, but smaller and less consistent associations of non-directional and directional-downward SCO with outcomes (with notable exceptions). Taken together, this research indicates that SCO is a multi-faceted individual difference variable.

A review of extended coronavirus disease 2019 (COVID-19) isolation duration among inpatients in a tertiary-care hospital-Iowa, 2020-2022.

Of the 2,668 patients admitted with coronavirus disease 2019 (COVID-19), 4% underwent prolonged isolation for >20 days. Reasons for extended isolation were inconsistent with Centers for Disease Control and Prevention (CDC) guidelines in 25% of these patients and were questionable in 54% due to an ongoing critically ill condition at day 20 without CDC-defined immunocompromised status.

In-depth assessment of critical access hospital stewardship program adherence to the CDC Core Elements in Iowa and Nebraska.

In 21 antimicrobial stewardship programs in critical-access hospitals in Nebraska and Iowa that self-reported nonadherence to a CDC Core Element or Elements, in-depth program assessment and feedback revealed that accountability and education most needed improvement. Recommendations included providing physician and pharmacist training, tracking interventions, and providing education. Program barriers included lack of time and/or personnel and antimicrobial stewardship and/or infectious diseases expertise.

Iowa family physician's reporting of elder abuse: 20-year follow-up.

The purpose of this project was to assess changes over 20 years, between family physicians perceived magnitude of elder mistreatment, physician knowledge of state laws, barriers to reporting suspected cases, and what is done in practice. Questionnaires were mailed to 1,080 physician members of the Iowa Academy of Family Physicians. Thirty-six percent of physicians returned the questionnaire. These respondents had a mean age of 51 years, were licensed for 19 years, and 51% were male. Twenty-nine percent of physicians ask their patients direct questions about elder abuse in 2022 compared to 14% in 2002. Identifying an elder abuse case was associated with asking direct questions about abuse and the belief that prompt action would be taken. Knowledge of elder abuse legislation was associated with reporting of all abuse cases, along with thinking there were clear definitions of abuse and that reporting benefits patients.

Benefits and Challenges of Sealing Deceased Individual Immunization Records in Immunization Information Systems (IIS): An Overview of Iowa's Process.

Data cleansing practices aimed to improve data quality in immunization information systems (IIS) continue to be identified and evaluated by immunization programs to generate accurate and reliable immunization coverage rates. The Iowa Immunization Program has implemented several automated, daily data cleansing practices to improve the quality of records in Iowa's Immunization Registry Information System (IRIS), including the process of sealing records of deceased individuals through vital records matching. This process removes deceased individual records from the active IIS population, which helps reduce denominator inflation and improve the accuracy of immunization rate calculations. Other benefits to this process include decreasing record fragmentation, increasing completeness and accuracy of IIS data, improving reminder/recall functionality, and supporting better clinical decision-making for providers. This process is one of multiple practices implemented in IIS to improve data quality and is limited by several factors, including the inability to capture deaths for out-of-state records.

The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.

IMPORTANCE: This manuscript will be of interest to most Clinical and Translational Science Awards (CTSA) as they retool for the increasing emphasis on translational science from translational research. This effort is an extension of the EDW4R work that most CTSAs have done to deploy infrastructure and tools for researchers to access clinical data. OBJECTIVES: The Iowa Health Data Resource (IHDR) is a strategic investment made by the University of Iowa to improve access to real-world health data. The goals of IHDR are to improve the speed of translational health research, to boost interdisciplinary collaboration, and to improve literacy about health data. The first objective toward this larger goal was to address gaps in data access, data literacy, lack of computational environments for processing Personal Health Information (PHI) and the lack of processes and expertise for creating transformative datasets. METHODS: A three-pronged approach was taken to address the objective. The approach involves integration of an intercollegiate team of non-informatics faculty and staff, a data enclave for secure patient data analyses, and novel comprehensive datasets. RESULTS: To date, all five of the health science colleges (dentistry, medicine, nursing, pharmacy, and public health) have had at least one staff and one faculty member complete the two-month experiential learning curriculum. Over the first two years of this project, nine cohorts totaling 36 data liaisons have been trained, including 18 faculty and 18 staff. IHDR data enclave eliminated the need to duplicate computational infrastructure inside the hospital firewall which reduced infrastructure, hardware and human resource costs while leveraging the existing expertise embedded in the university research computing team. The creation of a process to develop and implement transformative datasets has resulted in the creation of seven domain specific datasets to date. CONCLUSION: The combination of people, process, and technology facilitates collaboration and interdisciplinary research in a secure environment using curated data sets. While other organizations have implemented individual components to address EDW4R operational demands, the IHDR combines multiple resources into a novel, comprehensive ecosystem IHDR enables scientists to use analysis tools with electronic patient data to accelerate time to science.

Detection and disease diagnosis trends (2017-2022) for Streptococcus suis, Glaesserella parasuis, Mycoplasma hyorhinis, Actinobacillus suis and Mycoplasma hyosynoviae at Iowa State University Veterinary Diagnostic Laboratory.

BACKGROUND: Accurate measurement of disease associated with endemic bacterial agents in pig populations is challenging due to their commensal ecology, the lack of disease-specific antemortem diagnostic tests, and the polymicrobial nature of swine diagnostic cases. The main objective of this retrospective study was to estimate temporal patterns of agent detection and disease diagnosis for five endemic bacteria that can cause systemic disease in porcine tissue specimens submitted to the Iowa State University Veterinary Diagnostic Laboratory (ISU VDL) from 2017 to 2022. The study also explored the diagnostic value of specific tissue specimens for disease diagnosis, estimated the frequency of polymicrobial diagnosis, and evaluated the association between phase of pig production and disease diagnosis. RESULTS: S. suis and G. parasuis bronchopneumonia increased on average 6 and 4.3%, while S. suis endocarditis increased by 23% per year, respectively. M. hyorhinis and A. suis associated serositis increased yearly by 4.2 and 12.8%, respectively. A significant upward trend in M. hyorhinis arthritis cases was also observed. In contrast, M. hyosynoviae arthritis cases decreased by 33% average/year. Investigation into the diagnostic value of tissues showed that lungs were the most frequently submitted sample, However, the use of lung for systemic disease diagnosis requires caution due to the commensal nature of these agents in the respiratory system, compared to systemic sites that diagnosticians typically target. This study also explored associations between phase of production and specific diseases caused by each agent, showcasing the role of S. suis arthritis in suckling pigs, meningitis in early nursery and endocarditis in growing pigs, and the role of G. parasuis, A. suis, M. hyorhinis and M. hyosynoviae disease mainly in post-weaning phases. Finally, this study highlighted the high frequency of co-detection and -disease diagnosis with other infectious etiologies, such as PRRSV and IAV, demonstrating that to minimize the health impact of these endemic bacterial agents it is imperative to establish effective viral control programs. CONCLUSIONS: Results from this retrospective study demonstrated significant increases in disease diagnosis for S. suis, G. parasuis, M. hyorhinis, and A. suis, and a significant decrease in detection and disease diagnosis of M. hyosynoviae. High frequencies of interactions between these endemic agents and with viral pathogens was also demonstrated. Consequently, improved control programs are needed to mitigate the adverse effect of these endemic bacterial agents on swine health and wellbeing. This includes improving diagnostic procedures, developing more effective vaccine products, fine-tuning antimicrobial approaches, and managing viral co-infections.

One-Week-Ahead Prediction of Cyanobacterial Harmful Algal Blooms in Iowa Lakes.

Cyanobacterial harmful algal blooms (CyanoHABs) pose serious risks to inland water resources. Despite advancements in our understanding of associated environmental factors and modeling efforts, predicting CyanoHABs remains challenging. Leveraging an integrated water quality data collection effort in Iowa lakes, this study aimed to identify factors associated with hazardous microcystin levels and develop one-week-ahead predictive classification models. Using water samples from 38 Iowa lakes collected between 2018 and 2021, feature selection was conducted considering both linear and nonlinear properties. Subsequently, we developed three model types (Neural Network, XGBoost, and Logistic Regression) with different sampling strategies using the nine selected variables (mcyA_M, TKN, % hay/pasture, pH, mcyA_M:16S, % developed, DOC, dewpoint temperature, and ortho-P). Evaluation metrics demonstrated the strong performance of the Neural Network with oversampling (ROC-AUC 0.940, accuracy 0.861, sensitivity 0.857, specificity 0.857, LR+ 5.993, and 1/LR- 5.993), as well as the XGBoost with downsampling (ROC-AUC 0.944, accuracy 0.831, sensitivity 0.928, specificity 0.833, LR+ 5.557, and 1/LR- 11.569). This study exhibited the intricacies of modeling with limited data and class imbalances, underscoring the importance of continuous monitoring and data collection to improve predictive accuracy. Also, the methodologies employed can serve as meaningful references for researchers tackling similar challenges in diverse environments.

High pesticide exposures events, pesticide poisoning, and shingles: A medicare-linked study of pesticide applicators in the agricultural health study.

OBJECTIVES: Self-reported shingles was associated with history of high pesticide exposure events (HPEE) in licensed pesticide applicators aged >60 years in the Agricultural Health Study (AHS). In the current study, using AHS-linked Medicare claims data, we examined incident shingles in relation to pesticide-related illness and pesticide poisoning, as well as HPEE. METHODS: We studied 22,753 licensed private pesticide applicators (97% white males, enrolled in the AHS 1993-97), aged ≥66 years with >12 consecutive months of Medicare fee-for-service hospital and outpatient coverage between 1999 and 2016. Incident shingles was identified based on having ≥1 shingles claim(s) after 12 months without claims. At AHS enrollment, participants were asked if they ever sought medical care or were hospitalized for pesticide-related illness, and a supplemental questionnaire (completed by 51%) asked about HPEE and poisoning. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards regression, adjusted for age, sex, race, state, and education. RESULTS: Over 192,053 person-years (PY), 2396 applicators were diagnosed with shingles (10.5%; age-standardized rate, 13.6 cases per 1,000PY), with higher rates among those reporting hospitalization for pesticide-related illness, pesticide poisoning, and HPEE (23.2, 22.5, and 16.6 per 1,000PY, respectively). In adjusted models, shingles was associated with hospitalization for pesticide-related illness (HR 1.69; 1.18, 2.39), poisoning (1.49; 1.08, 1.46), and HPEE (1.23; 95% CI = 1.03, 1.46), especially HPEE plus medical care/poisoning (1.78; 1.30, 2.43). CONCLUSION: These novel findings suggest that acute, high-level, and clinically impactful pesticide exposures may increase risk of shingles in subsequent years to decades following exposure.

Evaluating differences in density estimation for central Iowa butterflies using two methodologies.

The Pollard-Yates transect is a widely used method for sampling butterflies. Data from these traditional transects are analyzed to produce density estimates, which are then used to make inferences about population status or trends. A key assumption of the Pollard-Yates transect is that detection probability is 1.0, or constant but unknown, out to a fixed distance (generally 2.5 m on either side of a transect line). However, species-specific estimates of detection probability would allow for sampling at farther distances, resulting in more detections of individuals. Our objectives were to (1) evaluate butterfly density estimates derived from Pollard-Yates line transects and distance sampling, (2) estimate how detection probabilities for butterflies vary across sampling distances and butterfly wing lengths, and (3) offer advice on future butterfly sampling techniques to estimate population density. We conducted Pollard-Yates transects and distance-sampling transects in central Iowa in 2014. For comparison to densities derived from Pollard-Yates transects, we used Program DISTANCE to model detection probability (p) and estimate density (D) for eight butterfly species representing a range of morphological characteristics. We found that detection probability among species varied beyond 2.5 m, with variation apparent even within 5 m of the line. Such variation correlated with wing size, where species with larger wing size generally had higher detection probabilities. Distance sampling estimated higher densities at the 5-m truncation for five of the eight species tested. At this truncation, detection probability was <0.8 for all species, and ranged from 0.53 to 0.79. With the exception of the little yellow (Pyrisitia lisa), species with median wing length <5.0 mm had the lowest detection probabilities. We recommend that researchers integrate distance sampling into butterfly sampling and monitoring, particularly for studies utilizing survey transects >5 m wide and when smaller species are targeted.

Simultaneous stream assessment of antibiotics, bacteria, antibiotic resistant bacteria, and antibiotic resistance genes in an agricultural region of the United States.

Antimicrobial resistance (AMR) is now recognized as a leading global threat to human health. Nevertheless, there currently is a limited understanding of the environment's role in the spread of AMR and antibiotic resistance genes (ARGs). In 2019, the U.S. Geological Survey conducted the first statewide assessment of antibiotic resistant bacteria (ARB) and ARGs in surface water and bed sediment collected from 34 stream locations across Iowa. Environmental samples were analyzed for a suite of 29 antibiotics and plated on selective media for 15 types of bacteria growth; DNA was extracted from culture growth and used in downstream polymerase chain reaction (PCR) assays for the detection of 24 ARGs. ARGs encoding resistance to antibiotics of clinical importance to human health and disease prevention were prioritized as their presence in stream systems has the potential for environmental significance. Total coliforms, Escherichia coli (E. coli), and staphylococci were nearly ubiquitous in both stream water and stream bed sediment samples, with enterococci present in 97 % of water samples, and Salmonella spp. growth present in 94 % and 67 % of water and bed sediment samples. Bacteria enumerations indicate that high bacteria loads are common in Iowa's streams, with 23 (68 %) streams exceeding state guidelines for primary contact for E. coli in recreational waters and 6 (18 %) streams exceeding the secondary contact advisory level. Although antibiotic-resistant E. coli growth was detected from 40 % of water samples, vancomycin-resistant enterococci (VRE) and penicillinase-resistant Staphylococcus aureus (MRSA) colony growth was detected from nearly all water samples. A total of 14 different ARGs were detected from viable bacteria cells from 30 Iowa streams (88 %, n = 34). Study results provide the first baseline understanding of the prevalence of ARB and ARGs throughout Iowa's waterways and health risk potential for humans, wildlife, and livestock using these waterways for drinking, irrigating, or recreating.

Rates and predictors of teen driver crash culpability.

BACKGROUND: Motor-vehicle crash risk is highest among teen drivers. Despite a wealth of research on the topic, there are still many contributors to these crashes that are not well understood. The current study sought to examine the contribution of graduated driver licensing (GDL) restrictions, sex, age, roadway circumstances, and citation history to teen drivers' crash culpability. METHOD: Crash system data from the Iowa Department of Transportation were linked with traffic-related charges from the Iowa Court Information System. Crashes involving teens aged 14 to 17 years between 2016 and 2019 were analyzed (N = 19,847). Culpability was determined using the driver contributing circumstances from the crash report. Moving and non-moving traffic citations issued prior to the date of each crash were considered. A multivariable logistic regression model was constructed to examine predictors of crash culpability. RESULTS: Teen drivers were determined to be culpable for more than two thirds of crashes (N = 13,604, 68.54%). Culpability was more prevalent among males, younger teens, in rural areas, in the presence of reported roadway contributing circumstances, during hours of restricted nighttime driving, and among teens with citation histories that included both moving and non-moving citations. Similarly, multivariable model results indicated that the likelihood of culpability was higher among males, in rural areas, and at each stage of GDL compared to teen drivers with unrestricted licenses. While drivers with a history of both moving and non-moving violations were more likely to be culpable, those with a history of only moving or only non-moving violations were less likely to be culpable compared to those with no violation history. CONCLUSION: Sex, crash location, and GDL stage were associated with teen driver crash culpability. A singular prior moving or non-moving violation may play a protective role in teen crash culpability.

Validation of the Iowa Head-Mounted Open-Source Perimeter.

Purpose: To assess the validity of visual field (VF) results from the Iowa Head-Mounted Display (HMD) Open-Source Perimeter and to test the hypothesis that VF defects and test-retest repeatability are similar between the HMD and Octopus 900 perimeters. Methods: We tested 20 healthy and nine glaucoma patients on the HMD and Octopus 900 perimeters using the Open Perimetry Interface platform with size V stimuli, a custom grid spanning the central 26° of the VF, and a ZEST thresholding algorithm. Historical data from the Humphrey Field Analyzer (HFA) were also analyzed. Repeatability was analyzed with the repeatability coefficient (RC), and VF defect detection was determined through side-by-side comparisons. Results: The pointwise RCs were 2.6 dB and 3.4 dB for the HMD and Octopus 900 perimeters in ocular healthy subjects, respectively. Likewise, the RCs were 4.2 dB and 3.5 dB, respectively, in glaucomatous patients. Limits of agreement between the HMD and Octopus 900 perimeters were ±4.6 dB (mean difference, 0.4 dB) for healthy patients and ±8.9 dB (mean difference, 0.1 dB) for glaucomatous patients. Retrospective analysis showed that pointwise RCs on the HFA2 perimeter were between 3.4 and 3.7 dB for healthy patients and between 3.9 and 4.7 dB for glaucoma patients. VF defects were similar between the HMD and Octopus 900 for glaucoma subjects. Conclusions: The Iowa Virtual Reality HMD Open-Source Perimeter is as repeatable as the Octopus 900 perimeter and is a more portable and less expensive alternative than traditional perimeters. Translational Relevance: This study demonstrates the validity of the visual field results from the Iowa HMD Open-Source Perimeter which may help expand perimetry access.