Validating self-reported Toxic Release Inventory data using Benford's Law: investigating toxic chemical release hazards in floodplains.

Introduction: Acute and long-term health impacts from flooding related toxic chemical releases are a significant local health concern and can disproportionately impact communities with vulnerable populations; reliable release data are needed to quantify this hazard. Methods: In this paper, we analyze US Federal Emergency Management Agency designated floodplain data and US Environmental Protection Agency Toxic Release Inventory (TRI) data to determine if geographically manipulated databases adhere to Benford's Law. Results: We investigated multiple variants and discovered pollution releases adhere to Benford's Law and tests which thereby validates the self-reported toxic release dataset. Discussion: We find that Benford's Law applies to self-reported toxic chemical release and disposal data, indicating a lack of widespread data errors or manipulation.

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 Web-Based Interactive Map to Promote Health-Care Facility Flood Preparedness.

OBJECTIVES: Little is known about how flood risk of health-care facilities (HCFs) is evaluated by emergency preparedness professionals and HCFs administrators. This study assessed knowledge of emergency preparedness and HCF management professionals regarding locations of floodplains in relation to HCFs. A Web-based interactive map of floodplains and HCF was developed and users of the map were asked to evaluate it. METHODS: An online survey was completed by administrators of HCFs and public health emergency preparedness professionals in Illinois, before and after an interactive online map of floodplains and HCFs was provided. RESULTS: Forty Illinois HCFs located in floodplains were identified, including 12 long-term care facilities. Preparedness professionals have limited knowledge of whether local HCFs were in floodplains, and few reported availability of geographic information system (GIS) resources at baseline. Respondents intended to use the interactive map for planning and stakeholder communications. CONCLUSIONS: Given that HCFs are located in floodplains, this first assessment of using interactive maps of floodplains and HCFs may promote a shift to reliable data sources of floodplain locations in relation to HCFs. Similar approaches may be useful in other settings.

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.

Hospitalizations for heat-stress illness varies between rural and urban areas: an analysis of Illinois data, 1987-2014.

BACKGROUND: The disease burden due to heat-stress illness (HSI), which can result in significant morbidity and mortality, is expected to increase as the climate continues to warm. In the United States (U.S.) much of what is known about HSI epidemiology is from analyses of urban heat waves. There is limited research addressing whether HSI hospitalization risk varies between urban and rural areas, nor is much known about additional diagnoses of patients hospitalized for HSI. METHODS: Hospitalizations in Illinois for HSI (ICD-9-CM codes 992.x or E900) in the months of May through September from 1987 to 2014 (n = 8667) were examined. Age-adjusted mean monthly hospitalization rates were calculated for each county using U.S. Census population data. Counties were categorized into five urban-rural strata using Rural Urban Continuum Codes (RUCC) (RUCC1, most urbanized to RUCC5, thinly populated). Average maximum monthly temperature (°C) was calculated for each county using daily data. Multi-level linear regression models were used, with county as the fixed effect and temperature as random effect, to model monthly hospitalization rates, adjusting for the percent of county population below the poverty line, percent of population that is Non-Hispanic Black, and percent of the population that is Hispanic. All analyses were stratified by county RUCC. Additional diagnoses of patients hospitalized for HSI and charges for hospitalization were summarized. RESULTS: Highest rates of HSI hospitalizations were seen in the most rural, thinly populated stratum (mean annual summer hospitalization rate of 1.16 hospitalizations per 100,000 population in the thinly populated strata vs. 0.45 per 100,000 in the metropolitan urban strata). A one-degree Celsius increase in maximum monthly average temperature was associated with a 0.34 increase in HSI hospitalization rate per 100,000 population in the thinly populated counties compared with 0.02 per 100,000 in highly urbanized counties. The most common additional diagnoses of patients hospitalized with HSI were dehydration, electrolyte abnormalities, and acute renal disorders. Total and mean hospital charges for HSI cases were $167.7 million and $20,500 (in 2014 US dollars). CONCLUSION: Elevated temperatures appear to have different impacts on HSI hospitalization rates as function of urbanization. The most rural and the most urbanized counties of Illinois had the largest increases in monthly hospitalization rates for HSI per unit increase in the average monthly maximum temperature. This suggests that vulnerability of communities to heat is complex and strategies to reduce HSI may need to be tailored to the degree of urbanization of a county.