Using Artificial Intelligence to Identify Sources and Pathways of Lead Exposure in Children.

CONTEXT: Sources and pathways of lead exposure in young children have not been analyzed using new artificial intelligence methods. OBJECTIVE: To collect environmental, behavioral, and other data on sources and pathways in 17 rural homes to predict at-risk households and to compare urban and rural indicators of exposure. DESIGN: Cross-sectional pilot study. SETTING: Knox County, Illinois, which has a high rate of childhood lead poisoning. PARTICIPANTS: Rural families. METHODS: Neural network and K-means statistical analysis. MAIN OUTCOME MEASURE: Children's blood lead level. RESULTS: Lead paint on doors, lead dust, residential property assessed tax, and median interior paint lead level were the most important predictors of children's blood lead level. CONCLUSIONS: K-means analysis confirmed that settled house dust lead loadings, age of housing, concentration of lead in door paint, and geometric mean of interior lead paint samples were the most important predictors of lead in children's blood. However, assessed property tax also emerged as a new predictor. A sampling strategy that examines these variables can provide lead poisoning prevention professionals with an efficient and cost-effective means of identifying priority homes for lead remediation. The ability to preemptively target remediation efforts can help health, housing, and other agencies to remove lead hazards before children develop irreversible health effects and incur costs associated with lead in their blood.

A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States.

Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is a risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic.

A second wave of COVID-19 in Cook County: What lessons can be applied?

During the ongoing public health crisis, many agencies are reporting COVID-19 health outcome information based on the overall population. This practice can lead to misleading results and underestimation of high risk areas. To gain a better understanding of spatial and temporal distribution of COVID-19 deaths; the long term care facility (LTCF) and household population (HP) deaths must be used. This approach allows us to better discern high risk areas and provides policy makers with reliable information for community engagement and mitigation strategies. By focusing on high-risk LTCFs and residential areas, protective measures can be implemented to minimize COVID-19 spread and subsequent mortality.  These areas should be a high priority target when COVID-19 vaccines become available.

Chemical facility risks to natural flooding hazards in the United States.

Toxic release inventory (TRI) facilities contain chemicals, most must be kept in process equipment, otherwise leaks are possible. An analysis of the National Flood Hazard Layer and TRI facilities within ArcGIS. The national analysis included TRI facilities intersecting the 100-year floodplain based on the National Flood Hazard Layer. The frequency which TRI facilities are impacted by flooding was analyzed with federal declarations data. We were able to determine what percentage of each state's facilities fall into the floodplain and calculate and assign a risk number to each state.

Mercury generation potential from dental waste amalgam.

OBJECTIVE: The main objective of this study was to quantify the total amount of amalgam used in dental offices in the state of Illinois and to estimate the fractions of amalgam waste material generated during dental procedures. A second objective was to estimate the fractions of non-contact, contact, and tooth retained amalgam through an in vitro study. METHODS: The collection system consisted of containers placed in six dental offices and clinics to collect the material from the in-line trap (contact amalgam) and the excess dental amalgam not placed into the oral cavity (non-contact amalgam). In order to have comparable results, the data was adjusted by the number of dental chairs being used and the number of working days. RESULTS: The range for the non-contact amalgam was from 0 to 102 g, and for the contact amalgam, from 2 to 16 g. The median estimate of non-contact amalgam generated from the 6 dental offices was 421 mg/day/chair, whereas the median estimate of contact amalgam was 64 mg/day/chair. For the in vitro study, 40 one and two surface amalgams (bicuspids and molars), was distributed as follows, 46+/-20% in the tooth, 43+/-19% as non-contact amalgam, and 11+/-4% as contact amalgam. CONCLUSIONS: Based on survey data from the ADA concerning the number of working days per year, the number of practicing dentists, a 50%, by weight, mercury content in amalgam, and the generation estimates from this project, it was estimated that the practicing dentists in the State of Illinois (6455) have the potential to generate 947 kg of non-contact mercury per year, which is recyclable, and 144 kg of contact mercury which has the potential to be discarded in the environment, or be partially recycled. If this approach is applied to the total population of practicing dentist in the United States (123,641), then 18,159 kg of recyclable, non-contact mercury may be generated per year, whereas 2763 kg of contact mercury may be discarded in the environment, or be partially recycled.

Particle versus mercury removal efficiency of amalgam separators.

OBJECTIVE: The intent of this project was to evaluate the efficiency of three commercial amalgam separators based on mercury and particle removal. METHODS: Dental wastewater samples were collected from a 54-chair dental clinic and a one chair private dental office. Atomic absorption spectrometry was used to measure mercury, and a laser diffractometer method to determine the particle size distributions. RESULTS: The mercury removal efficiency of the three units ranged from 26.5 to 61.8% for the 54-chair clinic and from 80.8 to 94.7% for the one chair office. Following treatment, the particle size range of the effluent was 8.3-19.2 microm for the 54-chair office and 27.5-41.4 microm for the one-chair clinic. For particle samples based on the silver-copper and copper standards, the three amalgam separators had a particle removal efficiency ranging from 92.3 to 99.9%. The initial particle size distributions for these samples were all under 100 microm. CONCLUSIONS: The efficiency of the amalgam separators is influenced by the initial concentration of the dental wastewater, the physical setup of the discharge system before the dental wastewater reaches the separators, and the addition of chemicals to the dental wastewater. In addition, it is likely that assessment of efficiency based on particle removal by weight may not be as effective as removal based on concentration.