Implementation of an Awareness Level Training to Prepare the Workforce for Future Infectious Disease Outbreaks.

OBJECTIVE: The COVID-19 pandemic underscores the need for workforce awareness-level training for infectious disease outbreaks. A training program was created and evaluated to provide strategies for emergency preparedness as well as worker health and safety during a disease outbreak. METHODS: Participants (N = 292) completed instructor-led synchronous online training modules between January 2022 and February 2023. Training covered 5 areas: vaccine awareness, infectious disease transmission and prevention, pandemic awareness, and inapparent infections, as well as workplace controls to reduce or remove hazards. Participants completed a survey before and after training to assess knowledge change in the five areas. Chi-square analyses assessed how predictors were related to knowledge change. RESULTS: Overall, an increase in knowledge was observed between pre- (80.9%) and post-training (92.7%). Participants from small businesses, with less work experience, and in non-health care roles were under-informed. Knowledge of disease transmission and prevention improved for non-health care professions and workers with less experience. All participants gained knowledge in identifying and ranking safeguards to protect workers from injuries and illness at job sites. CONCLUSIONS: Training improved employee knowledge about safe work practices and pandemic preparedness. Studies should continue to evaluate the effectiveness of preparedness training to prepare the workforce for infectious disease outbreaks and pandemics.

AERMOD modeling of ambient manganese for residents living near a ferromanganese refinery in Marietta, OH, USA.

Elevated exposure to ambient manganese (Mn) is associated with adverse health outcomes. In Marietta, Ohio, the primary source of ambient Mn exposure is from the longest operating ferromanganese refinery in North America. In this study, the US EPA air dispersion model, AERMOD, was used to estimate ambient air Mn levels near the refinery for the years 2008-2013. Modeled air Mn concentrations for 2009-2010 were compared to concentrations obtained from a stationary air sampler. Census block population data were used to estimate population sizes exposed to an annual average air Mn > 50 ng/m3, the US EPA guideline for chronic exposure, for each year. Associations between modeled air Mn, measured soil Mn, and measured indoor dust Mn in the modeled area were also examined. Median modeled air Mn concentrations ranged from 6.3 to 43 ng/m3 across the years. From 12,000-56,000 individuals, including over 2000 children aged 0-14 years, were exposed to respirable annual average ambient air Mn levels exceeding 50 ng/m3 in five of the six years. For 2009-2010, the median modeled air Mn concentration at the stationary site was 20 ng/m3, compared to 18 ng/m3 measured with the stationary air sampler. All model performance measures for monthly modeled concentrations compared to measured concentrations were within acceptable limits. The study shows that AERMOD modeling of ambient air Mn is a viable method for estimating exposure from refinery emissions and that the Marietta area population was at times exposed to Mn levels that exceeded US EPA guidelines.

Rethinking Environmental Protection: Meeting the Challenges of a Changing World.

SUMMARY: From climate change to hydraulic fracturing, and from drinking water safety to wildfires, environmental challenges are changing. The United States has made substantial environmental protection progress based on media-specific and single pollutant risk-based frameworks. However, today's environmental problems are increasingly complex and new scientific approaches and tools are needed to achieve sustainable solutions to protect the environment and public health. In this article, we present examples of today's environmental challenges and offer an integrated systems approach to address them. We provide a strategic framework and recommendations for advancing the application of science for protecting the environment and public health. We posit that addressing 21st century challenges requires transdisciplinary and systems approaches, new data sources, and stakeholder partnerships. To address these challenges, we outline a process driven by problem formulation with the following steps: a) formulate the problem holistically, b) gather and synthesize diverse information, c) develop and assess options, and d) implement sustainable solutions. This process will require new skills and education in systems science, with an emphasis on science translation. A systems-based approach can transcend media- and receptor-specific bounds, integrate diverse information, and recognize the inextricable link between ecology and human health.

Pathways of inhalation exposure to manganese in children living near a ferromanganese refinery: A structural equation modeling approach.

Manganese (Mn) is both essential element and neurotoxicant. Exposure to Mn can occur from various sources and routes. Structural equation modeling was used to examine routes of exposure to Mn among children residing near a ferromanganese refinery in Marietta, Ohio. An inhalation pathway model to ambient air Mn was hypothesized. Data for model evaluation were obtained from participants in the Communities Actively Researching Exposure Study (CARES). These data were collected in 2009 and included levels of Mn in residential soil and dust, levels of Mn in children's hair, information on the amount of time the child spent outside, heat and air conditioning in the home and level of parent education. Hair Mn concentration was the primary endogenous variable used to assess the theoretical inhalation exposure pathways. The model indicated that household dust Mn was a significant contributor to child hair Mn (0.37). Annual ambient air Mn concentration (0.26), time children spent outside (0.24) and soil Mn (0.24) significantly contributed to the amount of Mn in household dust. These results provide a potential framework for understanding the inhalation exposure pathway for children exposed to ambient air Mn who live in proximity to an industrial emission source.

A Citizen-Science Study Documents Environmental Exposures and Asthma Prevalence in Two Communities.

A citizen-science study was conducted in two low-income, flood-prone communities in Atlanta, Georgia, in order to document environmental exposures and the prevalence of occupant asthma. Teams consisting of a public-health graduate student and a resident from one of the two communities administered a questionnaire, inspected residences for mold growth, and collected a dust sample for quantifying mold contamination. The dust samples were analyzed for the 36 molds that make up the Environmental Relative Moldiness Index (ERMI). Most residents (76%) were renters. The median duration of residence was 2.5 years. Although only 12% of occupants reported a history of flooding, 46% reported at least one water leak. Homes with visible mold (35%) had significantly (P < 0.05) higher mean ERMI values compared to homes without (14.0 versus 9.6). The prevalence of self-reported, current asthma among participants was 14%. In logistic regression models controlling for indoor smoking, among participants residing at their current residence for two years or less, a positive association was observed between asthma and the homes' ERMI values (adjusted odds ratio per unit increase in ERMI = 1.12, 95% confidence intervals (CI): 1.01-1.25; two-tailed P = 0.04). Documentation of the exposures and asthma prevalence has been presented to the communities and public officials. Community-based organizations have taken responsibility for planning and implementing activities in response to the study findings.

Comparison of stationary and personal air sampling with an air dispersion model for children's ambient exposure to manganese.

Manganese (Mn) is ubiquitous in the environment and essential for normal growth and development, yet excessive exposure can lead to impairments in neurological function. This study modeled ambient Mn concentrations as an alternative to stationary and personal air sampling to assess exposure for children enrolled in the Communities Actively Researching Exposure Study in Marietta, OH. Ambient air Mn concentration values were modeled using US Environmental Protection Agency's Air Dispersion Model AERMOD based on emissions from the ferromanganese refinery located in Marietta. Modeled Mn concentrations were compared with Mn concentrations from a nearby stationary air monitor. The Index of Agreement for modeled versus monitored data was 0.34 (48 h levels) and 0.79 (monthly levels). Fractional bias was 0.026 for 48 h levels and -0.019 for monthly levels. The ratio of modeled ambient air Mn to measured ambient air Mn at the annual time scale was 0.94. Modeled values were also time matched to personal air samples for 19 children. The modeled values explained a greater degree of variability in personal exposures compared with time-weighted distance from the emission source. Based on these results modeled Mn concentrations provided a suitable approach for assessing airborne Mn exposure in this cohort.

Mold contamination in schools with either high or low prevelance of asthma.

BACKGROUND: Mold exposures have been linked to the development and exacerbation of asthma. The purpose of this study was to determine whether the Environmental Relative Moldiness Index (ERMI) metric, developed to quantify mold exposures in homes, might be applied to evaluating the mold contamination in schools. METHODS: Settled dust samples (n = 10) were collected on each level of a water-damaged school in Springfield, Massachusetts and two samples per level in five Idaho schools. Each dust sample was analyzed for the 36 molds that make up the ERMI. The concentration of 2.5-µm particulate matter (PM2.5 ) was measured in each school at two locations during the spring of 2013. RESULTS: The average ERMI value in the Springfield school, 15.51, was significantly greater (p < 0.001) than the average ERMI value, -2.87, in the Idaho schools. Ten of the twenty-six Group 1 molds, which are associated with water-damaged environments, were in significantly greater concentrations in the Springfield school. The populations of Group 2 molds, which are common indoors even without water damage, were essentially the same in Springfield and Idaho schools. The average PM2.5 concentration in the Springfield and Idaho schools was 11.6 and 3.4 µg/m(3) , respectively. CONCLUSIONS: The ERMI scale might be useful in comparing the relative mold contamination in schools.

Enhancing toxicity test performance by using a statistical criterion.

Aquatic toxicity tests are laboratory experiments that measure the biological effect (e.g., growth, survival, reproduction) of effluents, receiving waters, or storm water on aquatic organisms. These toxicity tests must be performed using the best laboratory practices, and every effort must be made to enhance repeatability of the test method. We evaluated the generated reference toxicant test data for insurance of a level of quality assurance for tests over time within a laboratory and among laboratories. We recommend the reporting and evaluation of the percent minimum significant difference (PMSD) value for all toxicity test results. The minimum significant difference (MSD) represents the smallest difference between the control mean and a treatment mean that leads to the statistical rejection of the null hypothesis (i.e., no toxicity) at each concentration of the toxicity test dilution series. The MSD provides an indication of within-test variability, and smaller values of MSD are associated with increased power to detect a toxic effect. We recommend upper and lower PMSD bounds for each test method in order to minimize within-test variability and increase statistical power. To ensure that PMSD does not exceed an upper bound, testing laboratories may need to increase replication, decrease variability among replicates, or increase the control mean performance.

Development and evaluation of a Macroinvertebrate Biotic Integrity Index (MBII) for regionally assessing Mid-Atlantic Highlands Streams.

The Macroinvertebrate Biotic Integrity Index (MBII) was developed from data collected at 574 wadeable stream reaches in the Mid-Atlantic Highlands region (MAHR) by the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program (EMAP). Over 100 candidate metrics were evaluated for range, precision, responsiveness to various disturbances, relationship to catchment area, and redundancy. Seven metrics were selected, representing taxa richness (Ephemeroptera richness, Plecoptera richness, Trichoptera richness), assemblage composition (percent non-insect individuals, percent 5 dominant taxa), pollution tolerance [Macroinvertebrate Tolerance Index (MTI)], and one functional feeding group (collector-filterer richness). We scored metrics and summed them, then ranked the resulting index through use of independently evaluated reference stream reaches. Although sites were classified into lowland and upland ecoregional groups, we did not need to develop separate scoring criteria for each ecoregional group. We were able to use the same metrics for pool and riffle composite samples, but we had to score them differently. Using the EMAP probability design, we inferred the results, with known confidence bounds, to the 167,797 kilometers of wadeable streams in the Mid-Atlantic Highlands. We classified 17% of the target stream length in the MAHR as good, 57% as fair, and 26% as poor. Pool-dominated reaches were relatively rare in the MAHR, and the usefulness of the MBII was more difficult to assess in these reaches. The process used for developing the MBII is widely applicable and resulted in an index effective in evaluating region-wide conditions and distinguishing good and impaired reaches among both upland and lowland streams dominated by riffle habitat.

Methods development and use of macroinvertebrates as indicators of ecological conditions for streams in the Mid-Atlantic Highlands Region.

The Mid-Atlantic Highlands Assessment (MAHA) included the sampling of macroinvertebrates from 424 wadeable stream sites to determine status and trends, biological conditions, and water quality in first through third order streams in the Mid-Atlantic Highlands Region (MAHR) of the United States in 1993-1995. We identified reference and impaired sites using water chemistry and habitat criteria and evaluated a set of candidate macroinvertebrate metrics using a stepwise process. This process examined several metric characteristics, including ability of metrics to discriminate reference and impaired sites, relative scope of impairment, correlations with chemical and habitat indicators of stream disturbance, redundancy with other metrics, and within-year variability. Metrics that performed well were compared with metrics currently being used by three states in the region: Pennsylvania, Virginia, and West Virginia. Some of the metrics used by these states did not perform well when evaluated using regional data, while other metrics used by all three states in some form, specifically number of taxa, number of EPT taxa, and Hilsenhoff Biotic Index, performed well overall. Reasons for discrepancies between state and regional evaluations of metrics are explored. We also provide a set of metrics that, when used in combination, may provide a useful assessment of stream conditions in the MAHR.

Development and evaluation of the Lake Macroinvertebrate Integrity Index (LMII) for New Jersey lakes and reservoirs.

In response to the recent focus by the U.S. Environmental Protection Agency on bioassessment of lakes, a multimetric index was developed for New Jersey lakes and reservoirs using benthic macroinvertebrates. Benthic samples were collected from reference and impaired lakes with muck and intermediate sediments in central and northern New Jersey during summer 1997. We used a stepwise process to evaluate properties of candidate metrics and selected five for the Lake Macroinvertebrate Integrity Index (LMII): Hilsenhoff Biotic Index (HBI), percent chironomid individuals, percent collector-gatherer taxa, percent oligochaetes/leeches, and number of Diptera taxa. We scored metrics as the fraction of the best expected value (based on all sites) achieved at a site and summed them into the LMII. Evaluation of the LMII showed that it discriminated well between reference and impaired lakes and was strongly related to several potential stressors. Chemical and physical gradients distinguished between reference and impaired lakes, and the LMII summarized these gradients well. The LMII corresponded strongly with land use, but some lakes with more urban land use still achieved high scores. Based on a power analysis, the ability of the LMII to detect differences in condition was sensitive to the number of samples from each lake.