National Environmental Public Health Tracking Research Articles

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information With Lower‐Latency NASA Data

AbstractExposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention's National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated data sets over the contiguous U.S. (CONUS) include: daily 5‐day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast, daily historical (1980‐present) concentrations of speciated PM2.5 based on the modern era retrospective analysis for research and applications, version 2, and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real‐time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (a) describing temporal and spatial trends in disease and potential environmental exposures, (b) identifying populations most affected, (c) generating hypotheses about associations between health and environmental exposures, and (d) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

Abstract 18866: Binge Alcohol Drinking and Myocardial Infarction Mortality in the United States

Introduction: Although moderate alcohol intake is related to decrease all cause and ischemic heart disease mortality, intake of large amounts at a time remains controversial. Some studies have shown that binge drinking (BD) could have a protective effect. Hypothesis: The aim of this study is to study life-style risk factors associated with cardiovascular mortality in the U.S. population. Methods: The CDC National Environmental Public Health Tracking Network was used to identify age-adjusted mortality rate due to myocardial infarction (MMI) per county among people ≥35 years between 2018 and 2019. County's age-adjusted prevalence of current smoking (CS), binge alcohol drinking (BD), no-leisure time physical activity (NLTPA) and obesity were also identified as potential community life-style risk factors for MMI. Multivariable regression model predicting MMI rate was used to identify relationship between county MMI rate and those 4 life-style risk factors. Results: A total of 3106 counties were included in this study. Median county age-adjusted MMI rate was 61.00 [46.30, 85.38] per 100.000. Median county age-adjusted prevalence of CS was 19.80% [17.40, 22.80], BD 17.70% [15.70, 19.90], Obesity 35.60% [32.70, 38.10], and NLTPA 26.50% [23.30, 30.68]. In a multivariable regression model, CS prevalence above 20% increased the MMI rate by 9.83 (6.82 to 12.84, p<0.001) per 100.000, NLTPA prevalence above 29% increased the MMI rate by 21.57 (18.12 to 25.02, p<0.001) per 100.000, and obesity prevalence above 36% increased the MMI rate by 8.30 (5.54 to 11.07, p<0.001) per 100.000. On the other hand, BD prevalence above 18% was not associated with a significant increase in the MMI rate. [0.67 (-2.11 to 3.44, p=0.638) per 100.000]. Conclusions: Community life-style risk-factors associated with myocardial infarction mortality include current smoking, no-leisure physical activity, and obesity. Alcohol binge drinking did not reduce myocardial infarction mortality rate.

The Impact of Air Pollutants on a Chicagoland Cohort of Patients with Acute Myeloid Leukemia

Background Outcomes in acute myeloid leukemia (AML) can be impacted by cytogenetic/molecular features along with environmental factors such as previous exposure to cytotoxic therapy and county-level income. Our group previously identified structural racism, defined as systemic disadvantage experienced by certain groups of people, as a mediator of disparities within a cohort of 822 patients (pts) diagnosed with AML in the Chicagoland area even when accounting for genetic features of disease (Abraham et al, Blood 2022). Air pollution disproportionately impacts racial-ethnic minorities and has been demonstrated to impact DNA methylation patterns in pts which in turn influence disease biology (Tessum et al, Sci Advances 2021; Rider et al, Clin Epigenetics 2019). With that in mind we aimed to investigate the impact of air pollutant exposures that have been associated with both leukemia development/mortality and with air pollution disparities in historically redlined cities. Methods Adult AML (non-APL) pts diagnosed between 2012 and 2018 at six academic cancer centers in the Chicago area were included. Pts' census tracts were joined with measures of pollution obtained from the Center for Disease Control National Environmental Public Health Tracking Network and the 2014 National Air Toxics Assessment: 1,3-butadiene, benzene, diesel particulate matter (PM), polycyclic aromatic hydrocarbons and polycyclic organic matter (PAHPOM), and PM 2.5 µm (2014 averaged daily census tract measures). Pollutant exposures by racial/ethnic groups were determined using a Kruskall-Wallis rank sum test and pairwise Wilcoxon rank sum tests. Univariate logistic regressions for each pollutant were performed for 2010 European Leukemia Net (ELN) AML criteria and TP53 mutation status. Survival among pts in the most and least polluted census block quartiles for each pollutant was compared using Kaplan-Meier survival analysis. Results Our multi-center database contained 789 pts with AML with census tract data, allowing for air pollutant data collection. Median age of diagnosis was 62 years old. In addition, 59.9% of pts were non-Hispanic White (NHW), 15.3% were non-Hispanic Black (NHB), and 15% of pts were Hispanic. Additional characteristics are summarized in Table 1. There was significantly higher median exposure to 1,3-butadiene, benzene, diesel PM, PAHPOM, and PM2.5 in NHB and Hispanic pts when compared to NHW pts. Hispanic pts had significantly median higher exposure to 1,3-butadiene and benzene when compared to NHB pts while NHB pts had significantly higher median exposure to PM2.5 ( Table 2). With univariate analysis, no pollutant exposure was found to be significantly associated with ELN 2010 risk category or with TP53 mutation status. We also compared median OS (mOS) from AML diagnosis between the quartile with the lowest exposure (Q1) and quartile with the highest exposure (Q4). For 1,3-butadiene mOS was 2.52 years (Q1) vs. 2.96 years (Q4) (p=0.75), for benzene it was 2.65 years vs 3.0 years (p=0.38), for diesel PM it was 2.56 years vs 2.96 years (p=0.56), for PAHPOM it was 2.76 years vs. 2.96 years (p=0.31), and for PM2.5 it was 2.92 years vs. 2.70 years (p=0.32). Conclusions We analyzed the impact of 1,3-butadiene, benzene, diesel PM, PAHPOM, and PM2.5 on outcomes in pts with AML in the Chicagoland area. While there were significant differences in median exposure to pollutants by race/ethnicity, there was no significant association between pollutant exposure and ELN 2010 risk category or TP53 mutation analysis. We also analyzed overall survival between Q1 and Q4 of exposure for each pollutant and found no significant difference. While pollutant exposure disproportionately impacts racial-ethnic minorities, individual pollutants did not appear to be a major driver of outcomes in AML. Limitations include the source of our air pollutant data, where misclassification of pollutants may exist and impact the ability to detect true associations.

Per- and Polyfluoroalkyl Substances (PFAS) in Community Water Systems (CWS) and the Risk of Thyroid Cancer: An Ecological Study.

Thyroid cancer incidence has been steadily increasing over the past decade in the United States (US). A discussion exists regarding the potential contribution of exposure to endocrine-disrupting chemicals, encompassing certain per- and poly-fluoroalkyl substances (PFASs). This ecological study evaluated the potential correlation between PFAS levels in drinking water and thyroid cancer incidence in the US. Data on age-adjusted thyroid cancer incidence rate (per 100,000 persons) by county were obtained from the Centers for Disease Control and Prevention (CDC) for US counties with available data in 2015-2019. Data on PFAS concentrations in the drinking water of selected community water systems (CWSs) were obtained from the CDC National Environmental Public Health Tracking Network in 2013-2015. The correlation between PFASs in CWSs and thyroid cancer incidence was calculated using Spearman correlation. A statistically significant correlation was found between perfluorooctanoic acid (PFOA) (r = 0.031; p = 0.043), perfluorononanoic acid (PFNA) (r = 0.058; p ≤ 0.001), and thyroid cancer incidence. The results suggest a potential link between certain PFAS exposures and thyroid cancer risk. However, due to the nature of an ecological study, no conclusions can be drawn at the individual level or causality. More research is needed, particularly on an individual level to allow for more detailed exposure assessment.

495 Radon and Fracking Exposures and Lymphoma Risk in a Canine Model of non-Hodgkin Lymphoma

OBJECTIVES/GOALS: The objective of this study was to determine whether residential radon and proximity to horizontal oil and drilling (fracking) are risk factors for the development of multicentric lymphoma in pet dogs, a spontaneous, immunocompetent model for non-occupational risk for NHL in humans. METHODS/STUDY POPULATION: Two case-control populations of dogs with multicentric lymphoma were utilized, with a focus on two dog breeds at high risk for lymphoma. Control dogs were matched for age, breed, and sex. Home addresses were collected for 54 Golden retrievers with lymphoma and 108 Golden retriever controls, and for 56 boxer dogs with lymphoma and 84 unaffected boxer controls. Counties of residence were matched to radon zones and percentage of home radon tests that exceeded the actionable level of 4 pCi/L, available by county through the EPA and the CDC National Environmental Public Health Tracking Network from 2008 to 2017. Locations of horizontal oil and gas wells were obtained from the Enverus Database, and distances from dog homes to the closest well, and well density by county, were calculated for each case and control. RESULTS/ANTICIPATED RESULTS: We found no significant differences in radon zones, county level radon measurements, or residential proximity to active fracking wells between dogs with lymphoma and unaffected controls in either the Golden Retriever or boxer populations. DISCUSSION/SIGNIFICANCE: Canine multicentric lymphoma resembles human NHL and is a valuable model of non-occupational environmental risk for NHL in people. Although we did not find geographic associations between radon and fracking wells, follow-up studies will measure household radon, as well as household air, water, and dog urine for potentially genotoxic chemicals.

Feasibility of visualizing cancer incidence data at sub-county level: Findings from 21 National Program of Cancer Registries

Monitoring cancer incidence data by geography is useful for planning public health activities. However, due to anticipated confidentiality and statistical reliability issues, data on cancer incidence and mortality are more often displayed at a national, state, or county level, rather than at more local levels. To address this gap in displaying cancer data at the local level, the CDC's National Environmental Public Health Tracking Program and 21 National Program of Cancer Registries worked together on a pilot project to examine the feasibility of displaying sub-county-level incidence of selected cancer types diagnosed during 2007–2016. The results from this project are important steps for building sub-county cancer displays into data visualizations and using the data in a way that provides meaningful insights. The availability of sub-county cancer data may allow researchers to better examine cancer data at a local level which may help guide public health decisions regarding community-based interventions and screening services.

A Multistate Study on Housing Factors Influential to Heat-Related Illness in the United States.

As climate change increases the frequency and intensity of devastating and unpredictable extreme heat events, developments to the built environment should consider instigating practices that minimize the likelihood of indoor overheating during hot weather. Heatwaves are the leading cause of death among weather-related causes worldwide, including in developed and developing countries. In this empirical study, a four-step approach was used to collect, extract and analyze data from twenty-seven states in the United States. Three housing characteristic categories (i.e., general housing conditions, living conditions, and housing thermal inertia) and eight variables were extracted from the American Housing Survey database, ResStock database and CDC's National Environmental Public Health Tracking Network. Multivariable regression models were used to understand the influential variables, a multicollinearity test was used to determine the dependence of those variables, and then a logistic model was used to verify the results. Three variables-housing age (HA), housing crowding ratio (HCR), and roof condition (RC)-were found to be correlated with the risk of heat-related illness (HRI) indexes. Then, a logistic regression model was generated using the three variables to predict the risk of heat-related emergency department visits (EDV) and heat-related mortality (MORD) on a state level. The results indicate that the proposed logistic regression model correctly predicted 100% of the high-risk states for MORD for the eight states tested. Overall, this analysis provides additional evidence about the housing character variables that influence HRI. The outcomes also reinforce the concept of the built environment determined health and demonstrate that the built environment, especially housing, should be considered in techniques for mitigating climate change-exacerbated health conditions.

Social vulnerability, medical care access and asthma related emergency department visits and hospitalization: An observational study

BackgroundThe Social Vulnerability Index (SVI) is a publicly available dataset to identify communities in greatest need of resources. ObjectiveTo examine the utility of using the county-level SVI as predictors of asthma-related outcomes. MethodsWe used the American Community Survey-derived SVI and the National Environmental Public Health Tracking Network – Query Tool to retrieve data for all counties with available SVI data and at least one matched outcome of interest. Then, we tested SVI as a predictor for emergency department visits (EDV) and hospitalizations, with investigating disparities in primary care physician (PCP) density and emergency department physicians (EDP) density. Linear and logistic regression models were used. ResultsCompared to counties of the lowest SVI quartile, counties of mid-low, mid-high, and highest SVI quartiles had 1%, 4%, and 5% higher odds of asthma-related EDV per 10,000 population, respectively, and 4%, 21%, and 24% higher odds of asthma-related hospitalization per 10,000 population, respectively. Moreover, the data showed an apparent resources mismatch between the EDP densities per 10,000 populations and the SVI quartiles, and the effect of the county level SVI on the asthma-related EDV and hospitalization is not strongly affected by PCP or EDP densities. ConclusionThe counties with the highest SVI -and the most vulnerable to asthma hazards- have a lower coverage of PCP and EDP. Interventions directed to address persistent social vulnerability would offer the opportunity of primary prevention with less exhaustion for the medical resources.

The association between air pollution and childhood asthma: United States, 2010–2015

Objective The current population-based study examines the association between county-level ambient air pollution and childhood asthma. Methods Data from the nationally representative 2010–2015 National Health Interview Survey were linked to nationwide fine particulate matter (PM2.5) air pollution data at the county-level from the National Environmental Public Health Tracking Network which utilizes air quality monitoring stations and modeled PM2.5 measurements (Downscaler model data) and adjusted by county-level socioeconomic characteristics data from the 2010–2015 American Community Survey. Multilevel modeling techniques were used to assess the association between PM2.5 annual concentrations (quartiles < 8.11, 8.11–9.50, 9.51–10.59, ≥ 10.60 µg/m3) and current childhood asthma along with two asthma outcomes (episode in the past year, emergency room (ER) visit due to asthma). Results From 2010 to 2015, there were significant declines in PM2.5 concentrations and asthma outcomes. In unadjusted models, children living in areas with higher PM2.5 concentrations were more likely to have current asthma, ≥1 asthma episode in the past year, and ≥1 ER visit due to asthma compared with children living in areas with the lowest quartile (< 8.11 µg/m3). After adjusting for characteristics at the county, geographic, and child and family-level, significant associations remained for asthma episode, and ER visit among children living in areas with PM2.5 annual concentrations between 9.51 and 10.59 µg/m3 (3rd quartile) compared with children living in areas with the lowest quartile. Conclusions This study adds to the limited literature by incorporating nationally representative county-, child-, and family-level data to provide a multi-level analysis of the associations between air pollution and childhood asthma in the U.S.

Common and Unique Barriers to the Exchange of Administrative Healthcare Data in Environmental Public Health Tracking Program.

CDC’s National Environmental Public Health Tracking Program (Tracking Program) receives administrative data annually from 25–30 states to track potential environmental exposures and to make data available for public access. In 2019, the CDC Tracking Program conducted a cross-sectional survey among principal investigators or program managers of the 26 funded programs to improve access to timely, accurate, and local data. All 26 funding recipients reported having access to hospital inpatient data, and most states (69.2%) regularly update data user agreements to receive the data. Among the respondents, 15 receive record-level data with protected health information (PHI) and seven receive record-level data without PHI. Regarding geospatial resolution, approximately 50.0% of recipients have access to the street address or census tract information, 34.6% have access to ZIP code, and 11.5% have other sub-county geographies (e.g., town). Only three states receive administrative data for their residents from all border states. The survey results will help the Tracking Program to identify knowledge gaps and perceived barriers to the use and accessibility of administrative data for the CDC Tracking Program. The information collected will inform the development of resources that can provide solutions for more efficient and timely data exchange.

Aggregated cumulative county arsenic in drinking water and associations with bladder, colorectal, and kidney cancers, accounting for population served.

Many studies neglect to account for variation in population served by community water systems (CWSs) when aggregating CWS-level contaminant concentrations to county level. In an ecological epidemiologic analysis, we explored two methods-unweighted and weighted (proportion of CWS population served by county population)-to account for population served by CWS in association between arsenic and three cancers to determine the impact of population served on aggregated measures of exposure. CWS arsenic concentration data for 19 states were obtained from Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network for 2000-10, aggregated to county level, and linked to county-level cancer data for 2011-5 from National Cancer Institute and CDC State Cancer Profiles. Negative binomial regression models estimated adjusted risk ratios (aRR) and 95% confidence intervals (CI) between county-level bladder, colorectal, and kidney cancers and quartiles of aggregated cumulative county-level arsenic concentration (ppb-years). We observed positive associations between the highest quartileof exposure, compared to the lowest, ofaggregated cumulative county-level arsenic concentration (ppb-year) for bladder [weighted aRR: 1.89(1.53, 2.35)], colorectal [1.64(1.33, 2.01)], and kidney [1.69(1.37, 2.09)] cancers. We observed stronger associations utilizing the weighted exposure assessment method. However, inferences from this study are limited due to the ecologic nature of the analyses and different analytic study designs are needed to assess the utility that the weighted by CWS population served metric has for exposure assessment. Weighting by CWS population served accounts for some potential exposure assignment error in epidemiologic analysis.

Publicly available UV irradiance data in the contiguous United States and its applications

Background: Skin cancer is the most common type of cancer in the United States. The majority of skin cancer is caused by overexposure to ultraviolet (UV) light. National Environmental Public Health Tracking Program at CDC has collaborated with partners to develop and disseminate county-level daily UV irradiance (2005 to 2015) data for the contiguous United States.Methods: UV dataset was derived based on measurements from the Ozone Monitoring Instrument (OMI) during 2005-2015. UV irradiance data were first calculated at the census tract level; then daily population-weighted UV irradiance were calculated at the county level. We analyzed the spatial distributions and long-term trends of UV irradiance, and ratio of UV irradiance to solar irradiance. We also have used the newly developed dataset in a few applications to improve characterization of UV exposure.Results: The UV dataset is currently the only publicly-available, spatially-resolved, and long-term UV radiation dataset covering the contiguous United States. The national averages across all years available is 2,700 J/m2 for erythemally weighted daily dose of UV irradiance (EDD). UV irradiance increased toward the South and the West. The ratio of UV to solar irradiance mainly increased toward the South and in some areas with high altitude. This spatial variation suggests that using solar irradiance as indicator of UV irradiance in studies covering large geographic regions may bias the true pattern of UV exposure. National annual average daily UV irradiance increased significantly over the years by about 0.5% per year. In addition, we identified hotspots of skin cancer vulnerability, which took into consideration demographic, social risk factors and UV exposure intensity. We also examined state laws allowing sunscreen use in schools in the context of state average UV irradiance. Finally, we are currently studying the association between UV irradiance and cutaneous melanoma incidence rates among white US residents.

Examination of Laws Allowing Sunscreen Use in Schools in the Context of UV Levels by State

PurposeSunscreen use provides ultraviolet radiation (UV) protection but is often limited in school settings because sunscreen is classified as an over-the-counter drug product. Some US states have laws allowing students to carry and self-apply sunscreen. We examined these laws in the context of state UV levels. MethodsWe obtained legislative information through April 2020 from the American Society for Dermatologic Surgery Association website and UV data for years 2005–2015 from Centers for Disease Control and Prevention's National Environmental Public Health Tracking website. ResultsTwenty-three states and District of Columbia have sunscreen laws, including 11 states with UV levels above the median UV level across states. There was no significant association between state UV levels and sunscreen laws. ConclusionsThe presence of state sunscreen legislation has increased but is not associated with UV levels. Future research could examine the implementation and public health effects of these laws.

Availability, access, analysis and dissemination of small-area data

In this era of ‘big data’, there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualizations, allowing small-area data to be seen and understood by non-expert audiences, are revolutionizing public and researcher interactions with data. The UK Small Area Health Statistics Unit’s Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and ‘mash-ups’, and user-generated inputs from social media, mobile devices and wearable tech are new data streams that will find utility in future studies, and bring novel dimensions with respect to ethical use of small-area data.

Developing a surveillance system of sub-county data: Finding suitable population thresholds for geographic aggregations

The Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program created standardized sub-county geographies that are comparable over time, place, and outcomes. Expected census tract-level counts were calculated for asthma emergency department visits and lung cancer. Census tracts were aggregated for various total population and sub-population thresholds, then suppression and stability were examined. A total of 5,000 persons was recommended for the more common outcome scheme and a total of 20,000 persons was recommended for the rare outcome scheme. Health outcomes with a median case count of 17.0 cases or higher should produce stable estimates at the census tract level. This project generated recommendations for three sub-county geographies that will be useful for surveillance purposes: census tract, a more common outcome aggregation scheme, and a rare outcome aggregation scheme. This methodology can be applied anywhere to aggregate geographic units and produce stable rates at a finer resolution.

Visualizing Carbon Monoxide Poisoning Surveillance Data on the US CDC National Environmental Public Health Tracking Network

TPS 683: Short-term health effects of air pollutants 2, Exhibition Hall, Ground floor, August 28, 2019, 3:00 PM - 4:30 PM Background: CDC’s National Environmental Public Health Tracking Program (Tracking Program) aims to provide information from a nationwide network of integrated unintentional carbon monoxide (CO) poisoning data that could inform relevant public health action and prevention. Methods: The Tracking Program has developed dynamic environmental health surveillance system that includes standard visualization tools such as charts, interactive maps, and tables, and displays a variety of measures of morbidity and mortality (e.g., crude, and age-adjusted rates per 100,000) for unintentional CO poisoning. Users also can explore these measures by cause (i.e., fire, non-fire, unknown intent or mechanism). The hospitalization and emergency department (ED) data are obtained by the Tracking Program from funded state recipients (26 states); mortality data are from the National Vital Statistics System. We pooled the CO poisoning data from 2010-2014, and examined the proportion of unintentional non-fire CO poisonings, and compared state-specific age-adjusted rates during the same period. Results: During 2010-2014, there were more than 4,500 unintentional CO poisoning deaths with an average of 916 deaths annually. Deaths and hospitalizations categorized as non-fire comprised of 41.4%, and 55.4% of cases respectively. During the same period, states that had the two highest annual age-adjusted rate of ED visits for unintentional CO poisoning were Connecticut (AR: 21.4 in 2011) and Vermont (AR=15.7 in 2013), and the highest hospitalization rate were observed in New Mexico (AR: 2.1 in 2011) and Maryland (AR=1.8 in 2009). Conclusions: The Tracking Program demonstrates the opportunity to visualize environmental and health data on one data platform. This allows users to examine temporal and spatial trends and to identify communities at greater risk for CO poisoning. The Tracking Program’s CO poisoning data can be used to drive public health policy and actions that ultimately will reduce the burden of mortality and morbidity for CO poisoning.

Community drinking water data on the National Environmental Public Health Tracking Network: a surveillance summary of data from 2000 to 2010

This report describes the available drinking water quality monitoring data on the Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network (Tracking Network). This surveillance summary serves to identify the degree to which ten drinking water contaminants are present in finished water delivered to populations served by community water systems (CWS) in 24 states from 2000 to 2010. For each state, data were collected from every CWS. CWS are sampled on a monitoring schedule established by the Environmental Protection Agency (EPA) for each contaminant monitored. Annual mean and maximum concentrations by CWS for ten water contaminants were summarized from 2000 to 2010 for 24 states. For each contaminant, we calculated the number and percent of CWS with mean and maximum concentrations above the maximum contaminant level (MCL) and the number and percent of population served by CWS with mean and maximum concentrations above the MCL by year and then calculated the median number of those exceedances for the 11-year period. We also summarized these measures by CWS size and by state and identified the source water used by those CWS with exceedances of the MCL. The contaminants that occur more frequently in CWS with annual mean and annual maximum concentrations greater than the MCL include the disinfection byproducts, total trihalomethanes (TTHM), and haloacetic acids (HAA5); arsenic; nitrate; radium and uranium. A very high proportion of exceedances based on MCLs occurred mostly in very small and small CWS, which serve a year-round population of 3,300 or less. Arsenic in New Mexico and disinfection byproducts HAA5 and TTHM, represent the greatest health risk in terms of exposure to regulated drinking water contaminants. Very small and small CWS are the systems’ greatest difficulty in achieving compliance.

Compilation and spatio-temporal analysis of publicly available total solar and UV irradiance data in the contiguous United States

Skin cancer is the most common type of cancer in the United States, the majority of which is caused by overexposure to ultraviolet (UV) irradiance, which is one component of sunlight. National Environmental Public Health Tracking Program at CDC has collaborated with partners to develop and disseminate county-level daily UV irradiance (2005–2015) and total solar irradiance (1991–2012) data for the contiguous United States. UV irradiance dataset was derived from the Ozone Monitoring Instrument (OMI), and solar irradiance was extracted from National Solar Radiation Data Base (NSRDB) and SolarAnywhere data. Firstly, we produced daily population-weighted UV and solar irradiance datasets at the county level. Then the spatial distributions and long-term trends of UV irradiance, solar irradiance and the ratio of UV irradiance to solar irradiance were analyzed. The national average values across all years are 4300 Wh/m2, 2700 J/m2 and 130 mW/m2 for global horizontal irradiance (GHI), erythemally weighted daily dose of UV irradiance (EDD) and erythemally weighted UV irradiance at local solar noon time (EDR), respectively. Solar, UV irradiances and the ratio of UV to solar irradiance all increased toward the South and in some areas with high altitude, suggesting that using solar irradiance as indicator of UV irradiance in studies covering large geographic regions may bias the true pattern of UV exposure. National annual average daily solar and UV irradiances increased significantly over the years by about 0.3% and 0.5% per year, respectively. Both datasets are available to the public through CDC's Tracking network. The UV irradiance dataset is currently the only publicly-available, spatially-resolved, and long-term UV irradiance dataset covering the contiguous United States. These datasets help us understand the spatial distributions and temporal trends of solar and UV irradiances, and allow for improved characterization of UV and sunlight exposure in future studies.

Tracking environmental hazards and health outcomes to inform decision-making in the United States

ObjectiveTo increase the availability and accessibility of standardized environmental health data for public health surveillance and decision-making.IntroductionIn 2002, the United States (US) Centers for Disease Control and Prevention (CDC) launched the National Environmental Public Health Tracking Program (Tracking Program) to address the challenges in environmental health surveillance described by the Pew Environmental Commission (1). The report cited gaps in our understanding of how the environment affects our health and attributed these gaps to a dearth of surveillance data for environmental hazards, human exposures, and health effects. The Tracking Program’s mission is to provide information from a nationwide network of integrated health and environmental data that drives actions to improve the health of communities. Accomplishing this mission requires a range of expertise from environmental health scientists to programmers to communicators employing the best practices and latest technical advances of their disciplines. Critical to this mission, the Tracking Program must identify and prioritize what data are needed, address any gaps found, and integrate the data into the network for ongoing surveillance.MethodsThe Tracking Program identifies important environmental health topics with data challenges based on the recommendations in the Pew Commission report as well as input from federal, state, territorial, tribal, and local partners. For each topic, the first step is to formulate the key surveillance question, which includes identifying the decision-maker or end user. Next, available data are evaluated to determine if the data can answer the question and, if not, what enhancements or new data are needed. Standards are developed to establish data requirements and to ensure consistency and comparability. Standardized data are then integrated into the network at national, state, and local levels. Standardized measures are calculated to translate the data into the information needed. These measures are then publically disseminated via national, state, and local web-based portals. Data are updated annually or as they are available and new data are added regularly. All data undergo a multi-step validation process that is semi-automated, routinized, and reproducible.ResultsThe first set of nationally consistent data and measures (NCDM) was released in 2008 and covered 8 environmental health topics. Since then the NCDM have grown to cover 14 topics. Additional standardized data and measures are integrated into the national network resulting in 23 topics with standardized 450 measures (Figure). On the national network, measures can be queried via the Data Explorer, viewed in the info-by-location application, or connected to via the network’s Application Program Interface (API). On average, 15,000 and 3300 queries are run every month on the Data Explorer and the API respectfully. Additional locally relevant data are available on state and local tracking networks.Gaps in data have been addressed through standards for new data collections, models to extend available data, new methodologies for using existing data, and expansion of the utility of non-traditional public health data. For example, the program has collaborated with the Environmental Protection Agency to develop daily estimates of fine particulate matter and ozone for every county in the conterminous US and to develop the first national database of standardized radon testing data. The program also collaborated with the National Aeronautics and Space Administration and its academic partners to transform satellite data into data products for public health.The Tracking Program has analyzed the data to address important gaps in our understanding of the relationship between negative health outcomes and environmental hazards. Data have been used in epidemiologic studies to better quantify the association between fine particulate matter, ozone, wildfire smoke, and extreme heat on emergency department visits and hospitalizations. Results are translated into measures of health burden for public dissemination and can be used to inform regulatory standards and public health interventions.ConclusionsThe scope of the Tracking Program’s mission and the volume of data within the network requires the program to merge traditional public health expertise and practices with current technical and scientific advances. Data integrated into the network can be used to (1) describe temporal and spatial trends in health outcomes and potential environmental exposures, (2) identify populations most affected, (3) generate hypotheses about associations between health and environmental exposures, and (4) develop, guide, and assess the environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors. The program continues to expand the data within the network and the applications deployed for others to access the data. Current data challenges include the need for more temporally and spatially resolved data to better understand the complex relationships between environmental hazards, health outcomes, and risk factors at a local level. National standards are in development for systematically generating, analyzing, and disseminating small area data and real-time data that will allow for comparisons between different datasets over geography and time.

Seeing Data in a New Light: Data Visualization Techniques to Improve Understanding

ObjectiveThe presenter will demonstrate complex health and environment surveillance data visualization techniques within the CDC’s Environmental Public Health Tracking Network.IntroductionIn 2002, the United States (US) Centers for Disease Control and Prevention (CDC) launched the National Environmental Public Health Tracking Program (Tracking Program) to address the challenges and gaps in the nation’s environmental health surveillance infrastructure. The Tracking Program’s mission is to provide information from a nationwide network of integrated health and environmental data that drives actions to improve the health of communities. As a primary objective of the Tracking Program, the Environmental Public Health Tracking Network (Tracking Network) was developed as an online surveillance system with data available for 23 topics and over 450 different health, environmental, and population measures. The integration and display of such disparate data can be challenging. For data consumers without scientific training, or even scientists and public health professionals with limited time, it can be difficult to examine and explore the data in an online surveillance system. Additionally, casual data consumers may not require complex data details; a big picture perspective may be appropriate to their needs. The Tracking Network – which applies standardized data, a modern user interface, techniques catering to a variety of data consumers, and best practices in data visualization – provides a dynamic data query system that allows users to visualize different types of environmental health data in numerous ways including a variety of charting, mapping, and graphing options.MethodsAfter the Tracking Program identifies important environmental health topics, data standards are developed to aid in data validation and to ensure consistency and comparability of the data. The data are aggregated into standardized stratifications, summarized, and used to calculate environmental health measures. Visualization requirements for each measure are determined and developed on the Tracking Network. In addition, public health content are developed to provide important context for the user. The final step is the release of the environmental health measures onto the National Tracking Network, where they can be queried, visualized, compared, and analyzed with all of the other environmental health measures on the Tracking Network.ResultsLaunched in 2009, the Tracking Network developed at CDC is home to over 450 standardized environmental health measures spanning 23 topics and multiple years, and can be displayed at a geographic level of state, county, and census tract. The Tracking Network allows data consumers to interpret this data visually using tools including dynamic timeline maps, infographics, advanced charting and a streamlined user interface designed to be simple to use. With varying user levels in mind, this collection of tools provides a variety of avenues for the users to explore the data. Visualization results can be exported and embedded into other websites with data interpretation statements, benchmarks, and other visual cues that allow a broad audience to be able to access to environmental public health surveillance data.ConclusionsWhile the internet contains a wealth of health and environmental datasets, the Tracking Network provides a centralized location to access over 450 environmental health measures and provides a variety of visualization tools to translate the data into useful information. The speaker will present a range of display options available on the Tracking Network, highlight ways to present data for easy understanding and consumption, and provide a brief look into the future of data visualization.