Spatiotemporal patterns of Lyme disease in North Carolina: 2010-2020.

Background: Lyme disease is the most common vector-borne disease in the United States with the majority of cases occurring in the Northeast, upper Midwest, and mid-Atlantic regions. While historically considered a low incidence state, North Carolina (NC) has reported an increasing number of cases over the past decade. Therefore, the aim of this study was to characterise the spatiotemporal evolution of Lyme disease in NC from 2010 to 2020. Methods: Confirmed and probable cases reported to the NC Division of Public Health without associated travel to high-transmission state were included in the analysis. The study period was divided into four sub-periods and data were aggregated by zip code of residence. The absolute change in incidence was mapped and spatial autocorrelation analyses were performed within each sub-period. Findings: We identified the largest absolute changes in incidence in zip codes located in northwestern NC along the Appalachian Mountains. The spatial distribution of cases became increasingly clustered over the study period (Moran's I of 0.012, p = 0.127 in 2010-2012 vs. 0.403, p < 0.0001 in 2019-2020). Identified clusters included 22 high-incidence zip codes in the 2019-2020 sub-period, largely overlapping with the same areas experiencing the greatest absolute changes in disease incidence. Interpretation: Lyme disease has rapidly emerged in northwestern NC with some zip codes reporting incidence rates similar to historically high incidence regions across the US Northeast, mid-Atlantic, and upper Midwest. Efforts are urgently needed to raise awareness among medical providers to prevent excess morbidity. Funding: Funding was provided by a "Creativity Hub" award from the UNC Office of the Vice Chancellor for Research. Additional support was provided by Southeastern Center of Excellence in Vector Borne Diseases (U01CK000662).

Naloxone Accessibility by Standing Order in North Carolina Community Pharmacies.

BACKGROUND: According to a standing order in North Carolina (NC), naloxone can be purchased without a provider prescription. OBJECTIVE: The objective of this study is to examine whether same-day naloxone accessibility and cost vary by pharmacy type and rurality in NC. METHODS: A cross-sectional telephone audit of 202 NC community pharmacies stratified by pharmacy type and county of origin was conducted in March and April 2023. Trained "secret shoppers" enacted a standardized script and recorded whether naloxone was available and its cost. We examined the relationship between out-of-pocket naloxone cost, pharmacy type, and rurality. RESULTS: Naloxone could be purchased in 53% of the pharmacies contacted; 26% incorrectly noting that naloxone could be filled only with a provider prescription and 21% did not sell naloxone. Naloxone availability by standing order was statistically different by pharmacy type (chain/independent) (χ2 = 20.58, df = 4, P value < 0.001), with a higher frequency of willingness to dispense according to the standing order by chain pharmacies in comparison to independent pharmacies. The average quoted cost for naloxone nasal spray at chain pharmacies was $84.69; the cost was significantly more ($113.54; P < 0.001) at independent pharmacies. Naloxone cost did not significantly differ by pharmacy rurality (F2,136 = 2.38, P = 0.10). CONCLUSION: Approximately half of NC community pharmacies audited dispense naloxone according to the statewide standing order, limiting same-day access to this life-saving medication. Costs were higher at independent pharmacies, which could be due to store-level policies. Future studies should further investigate these cost differences, especially as intranasal naloxone transitions from a prescription only to over-the-counter product.

Spatial Clustering of Tobacco Retailers Near US Public Schools.

INTRODUCTION: Previous studies have found that tobacco retailers cluster near schools. However, all retail outlets may be located near each other and near schools due to existing infrastructure and zoning policies. We assessed whether tobacco retailers cluster near schools in the United States more than expected when accounting for existing retail locations. AIMS AND METHODS: We identified 322 056 probable tobacco retailers, 95 110 public schools, and more than 3.8 million businesses comparable to tobacco retailers in land use and business type. We created 500 simulated tobacco retailer datasets by randomly selecting from the larger list of businesses. For each simulated dataset, we calculated the distance from schools to the nearest tobacco retailer (proximity) and the count of tobacco retailers within 800 m of schools (density). Observed proximity and density values were compared to 95% coverage intervals from the 500 simulations. We stratified analyses by urbanicity, percentage of students in the free and reduced-priced lunch program (FRLP), and percentage of Hispanic/Latino, non-Hispanic Black, and non-Hispanic white students. RESULTS: Tobacco retailers were closer to schools in rural areas, cities, and towns and more dense around schools in rural areas, cities, and suburbs compared to random locations in potential retail space. Schools with more students receiving FRLP had higher density than expected while schools with fewer students receiving FRLP had lower density than expected. Within rural areas, clustering did not vary across sociodemographic groups. Within non-rural areas, there were inequities in clustering by racial, ethnic, and socioeconomic school composition. CONCLUSIONS: Tobacco retailers cluster near schools after accounting for existing business patterns. There are inequities in clustering by sociodemographic school composition. IMPLICATIONS: This study provides compelling evidence that tobacco retailers cluster near US public schools and that there are racial, ethnic, and socioeconomic inequities in clustering, even when accounting for overall retail location patterns. Given that public schools tend to reflect neighborhood demographics, policies to limit tobacco retailers near schools may reduce both school-based and neighborhood-based inequities.

Provisional Entrants, Exemptions, and Kindergarteners Up-to-Date on Vaccination Before and After a Regulatory Change in Pennsylvania, 2015-2019.

OBJECTIVES: Before the 2017-2018 school year, Pennsylvania shortened the grace period for provisional entrants-kindergarteners who are not up-to-date on vaccination and do not have medical or nonmedical exemption-from 8 months to 5 days. We analyzed the impact of this change on school-entry vaccination status. METHODS: Using data from the Pennsylvania Department of Health for school years 2015-2016 through 2018-2019, we examined state-level trends in Pennsylvania kindergarteners' vaccination status, including the percentage who were up-to-date on each required vaccine, provisionally enrolled, medically exempted from vaccination, and nonmedically exempted from vaccination. Using the Spearman correlation coefficient, we assessed associations at the school level among changes in kindergarteners' vaccination status after the grace period was shortened. RESULTS: From 2016-2017 to 2017-2018, the provisional entrance rate of kindergarteners in Pennsylvania decreased substantially after the change in the grace period (from 8.1% to 2.2%), the medical exemption rate remained stable, and the nonmedical exemption rate increased slightly (from 1.8% to 2.5%). The percentage of kindergarteners up-to-date on required vaccines increased or remained stable across the study period except for polio, which decreased from 97.9% in 2015-2016 to 96.2% in 2018-2019. The change in provisional entrance rate was negatively associated with change in kindergarteners up-to-date on required vaccines (ρ range, -0.30 to -0.70) but not with change in medical or nonmedical exemptions (ρ range, -0.01 to -0.08). CONCLUSIONS: Efforts to reduce provisional entrants may increase the percentage of kindergarteners up-to-date on vaccinations at school entry without a corresponding increase in exemptions.

Mass Probation: Effects of Sentencing Severity on Mental Health for Black and White Individuals.

BACKGROUND: Incarceration is associated with negative impacts on mental health. Probation, a form of community supervision, has been lauded as an alternative. However, the effect of probation versus incarceration on mental health is unclear. Our objective was to estimate the impact on mental health of reducing sentencing severity at individuals' first adult criminal-legal encounter. METHODS: We used the US National Longitudinal Survey on Youth 1997, a nationally representative dataset of youth followed into their mid-thirties. Restricting to those with an adult encounter (arrest, charge alone or no sentence, probation, incarceration), we used parametric g-computation to estimate the difference in mental health at age 30 (Mental Health Inventory-5) if (1) everyone who received incarceration for their first encounter had received probation and (2) everyone who received probation had received no sentence. RESULTS: Among 1835 individuals with adult encounters, 19% were non-Hispanic Black and 65% were non-Hispanic White. Median age at first encounter was 20. Under hypothetical interventions to reduce sentencing, we did not see better mental health overall (Intervention 1, incarceration to probation: RD = -0.01; CI = -0.02, 0.01; Intervention 2, probation to no sentence: RD = 0.00; CI = -0.01, 0.01) or when stratified by race. CONCLUSION: Among those with criminal-legal encounters, hypothetical interventions to reduce sentencing, including incremental sentencing reductions, were not associated with improved mental health. Future work should consider the effects of preventing individuals' first criminal-legal encounter.

Kindergarten Vaccination Status in California After Changes to Medical Exemption Policy.

This study evaluates changes in medical exemptions and geographic distribution of kindergarteners in California not up to date on vaccination after changes to state legislation.

Spatiotemporal characteristics of the SARS-CoV-2 Delta wave in North Carolina.

We constructed county-level models to examine properties of the SARS-CoV-2 B.1.617.2 (Delta) variant wave of infections in North Carolina and assessed immunity levels (via prior infection, via vaccination, and overall) prior to the Delta wave. To understand how prior immunity shaped Delta wave outcomes, we assessed relationships among these characteristics. Peak weekly infection rate and total percent of the population infected during the Delta wave were negatively correlated with the proportion of people with vaccine-derived immunity prior to the Delta Wave, signaling that places with higher vaccine uptake had better outcomes. We observed a positive correlation between immunity via infection prior to Delta and percent of the population infected during the Delta wave, meaning that counties with poor pre-Delta outcomes also had poor Delta wave outcomes. Our findings illustrate geographic variation in outcomes during the Delta wave in North Carolina, highlighting regional differences in population characteristics and infection dynamics.

Validating model output in the absence of ground truth data: A COVID-19 case study using the Simulator of Infectious Disease Dynamics in North Carolina (SIDD-NC) model.

As the COVID-19 pandemic has progressed, various models have been developed to forecast changes in the outbreak and assess intervention strategies. In this study we validate the Simulator of Infectious Disease Dynamics in North Carolina (SIDD-NC) model against an ensemble of proxy-ground truth infections datasets. We assess the performance of SIDD-NC using Spearman Rank Correlation, RMSE, and percent RMSE at a state and county level. We conduct the analysis for the period of March 2020 through November 2020 as well as in shorter time increments to assess both the recreation of the pandemic curve as well as day-to-day transmission of SARS-CoV-2 within the population. We find that SIDD-NC performs well against the datasets in the ensemble, generating an estimate of infections that is robust both spatially and temporally.

Students Provisionally Enrolled Due to Vaccination Requirements: Variation in State Laws and Rates.

This research examined the laws and regulations surrounding provisional enrollment in schools across the United States. Provisional enrollment refers to children who have started, but not completed, their required vaccinations and are allowed to attend school while completing their vaccinations. We found that nearly all states have laws regarding provisional enrollment, with 5 essential components to compare the laws including vaccine- and dose-specific requirements, type of personnel permitted to authorize, length of time that the children have to become up to date on their vaccinations (grace period), follow-up procedures, and consequences for noncompliance. In addition, we found that the percentage of provisionally enrolled kindergarteners varied greatly from state to state, with some states having less than 1% of provisionally enrolled kindergarteners and others having more than 8% between school years 2015-2016 and 2020-2021. We suggest that reducing the number of provisional entrants could be an alternative intervention to increase vaccination coverage.

Mass probation: Temporal and geographic correlation of county-level probation rates & mental health in North Carolina.

High community incarceration rates are associated with worse community mental health. However, it remains unknown whether higher rates of probation, a form of criminal legal community supervision, are similarly associated with worse community mental health. Our objective was to evaluate temporal and geographic correlations of county-level probation and mental health rates separately and to assess the association between county-level probation and mental health rates, measured by self-inflicted injury and suicide. We performed ecological analyses using North Carolina administrative data (2009-2019) and used repeated cross-section, multivariable spatial error models. From 2009 to 2019, probation rates trended downward while self-inflicted injury and suicide remained stable. We found positive spatial autocorrelation suggesting that there are spatial determinants of probation and self-harm, though less so for suicide. Hot spot analyses showed local variation with high self-harm and suicide rates being clustered in rural Western North Carolina and high probation rates being clustered in rural Eastern North Carolina. Probation was positively associated with self-inflicted injury and suicide. For example, in 2018, a 1 percentage point increase in probation was associated with a 0.05 percentage point increase in self-harm in 2019 (95% CI: 0.03, 0.06), meaning that in a county of 100,000 people, an increase in 1000 county residents being on probation would be associated with an increase in 50 self-harm injuries. High county-level probation rates may exert collateral damage on the mental health of those living in areas with much of the population under state control. These findings emphasize that the criminal legal system is not separate from communities and that future public health research and advocacy must consider these collateral consequences of probation on communities.

Deep tubewell use is associated with increased household microbial contamination in rural Bangladesh: Results from a prospective cohort study among households in rural Bangladesh.

Deep tubewells are important sources of arsenic mitigation in rural Bangladesh. Compared to commonly available shallow tubewells, deep tubewells tap into deeper low-arsenic aquifers and greatly reduce exposure to arsenic in drinking-water. However, benefits from these more distant and expensive sources may be compromised by higher levels of microbial contamination at point-of-use (POU). This paper examines differences in microbial contamination levels at source and POU among households using deep tubewells and shallow tubewells, and investigates factors associated with POU microbial contamination among deep tubewell users. We assessed a prospective longitudinal cohort of 500 rural households in Matlab, Bangladesh, across 135 villages. Concentration of Escherichia coli (E. coli) in water samples at source and POU using Compartment Bag Tests (CBTs) was measured across rainy and dry seasons. We employed linear mixed-effect regression models to measure the effect of different factors on log E. coli concentrations among deep tubewell users. CBT results show that log E. coli concentrations are similar at source and at POU during the first dry and rainy season, but are significantly higher at POU among deep tubewell users during the second dry season. Log E. coli at POU among deep tubewell users is positively associated with both presence (exponentiated beta exp(b) = 2.52, 95% Confidence Interval (CI) = 1.70, 3.73) and concentration of E. coli (exp(b) = 1.36, 95% CI = 1.19, 1.54) at source, and walking time to the tubewell source (exp(b) = 1.39, 95% CI = 1.15, 1.69). Drinking-water during the second dry season is associated with reduced log E. coli (exp(b) = 0.33, 95% CI = 0.23, 0.57) compared to the rainy season. These results suggest that while households that use deep tubewells have lower arsenic exposure, they may be at higher risk of consuming microbially contaminated water compared to households that use shallow tubewells.

Urban-rural differences in tobacco product availability in food retailers, United States, 2017.

PURPOSE: Tobacco use prevalence is higher in rural compared to urban settings, possibly due to differences in tobacco availability, including the option to purchase food and other essential items in stores that do not sell tobacco (tobacco-free food retailers). The goal of this research is to determine whether tobacco-free food retailer availability varies by urbanicity/rurality. METHODS: Using the 2017 National Establishment Time-Series database, we identified food retailers across all census tracts containing food retailers in the United States (n = 66,053). We used multivariable logistic and linear regression models to test whether tobacco-free food retailer availability varied across 4-levels of census tract urbanicity/rurality (urban, suburban, large town, and small town/rural) for 2 outcomes: (1) the presence of at least 1 tobacco-free food retailer and (2) the percent of all food retailers that were tobacco-free. FINDINGS: Compared to urban core census tracts, suburban census tracts had a lower odds (aOR = 0.77, 95% CI = 0.73, 0.81) of having at least 1 tobacco-free food retailer, while small town/rural census tracts had greater odds (aOR = 1.23, 95% CI = 1.15, 1.32). Suburban census tracts (B = -2.29, P < .001) and large town census tracts (B = -1.90, P < .001) also had a lower percentage of tobacco-free food retailers compared to urban census tracts. CONCLUSIONS: Compared to urban cores, tobacco-free food retailers were less prevalent in suburban and large town areas, though similarly or slightly more available in rural areas. Future research should assess whether these differences depend on varying store types.

Characterization of parental intention to vaccinate elementary school aged children in the state of California.

In October 2021, Emergency Use Authorization of Coronavirus Disease 2019 (COVID-19) vaccines was granted for children aged 5-11. To ensure vaccine uptake in children upon approval, California will implement a state-wide executive order mandating COVID-19 vaccination for school children following full US FDA approval. This study uses survey data collected between November 6th, 2020 and December 14th, 2020 (n = 2091) to identify how sociodemographic characteristics and attitudes towards childhood vaccines among California parents were associated with their intentions to vaccinate their child against COVID-19. About one quarter (26 %) of surveyed California parents did not intend to vaccinate their child, suggesting skepticism towards the COVID-19 vaccine for children and the potential for pushback to a COVID-19 vaccine school-entry mandate. However, 17 % were unsure of their decision, suggesting the potential for public health messaging to make a positive impact on COVID-19 vaccine confidence and uptake. This study identifies characteristics of hesitant parents in California to prioritize for research and outreach. These data also provide a baseline for parental attitudes towards vaccinating children against COVID-19 in California, which will be useful for characterizing changes in attitudes towards childhood COVID-19 vaccination over time.

NC-COVID: A Time-Varying Compartmental Model for Estimating SARS-CoV-2 Infection Dynamics in North Carolina, US.

Efforts to track and model SARS-CoV-2 infection dynamics in the population have been complicated by certain aspects of the transmission characteristics, which include a pre-symptomatic infectious phase as well as asymptomatic infectious individuals. Another problem is that many models focus on case count, as there has been (and is) limited data regarding infection status of members of the population, which is the most important aspect for constructing transmission models. This paper describes and explains the parameterization, calibration, and revision of the NC-COVID model, a compartmental model to estimate SARS-CoV-2 infection dynamics for the state of North Carolina, US. The model was developed early in the pandemic to provide rapid, up-to-date state-level estimates of the number of people who were currently infected, were immune from a prior infection, and remained susceptible to infection. As a post modeling exercise, we assessed the veracity of the model by comparing its output to SARS-CoV-2 viral particle concentrations detected in wastewater data and to estimates of people infected using COVID-19 deaths. The NC-COVID model was highly correlated with these independently derived estimates, suggesting that it produced accurate estimates of SARS-CoV-2 infection dynamics in North Carolina.

Spatial modeling of vaccine deserts as barriers to controlling SARS-CoV-2.

BACKGROUND: COVID-19 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We sought to measure if the disparities seen in the geographic distribution of other COVID-19 healthcare resources were also present during the initial rollout of the COVID-19 vaccine. METHODS: Using a comprehensive COVID-19 vaccine database (VaccineFinder), we built an empirically parameterized spatial model of access to essential resources that incorporated vaccine supply, time-willing-to-travel for vaccination, and previous vaccination across the US. We then identified vaccine deserts-US Census tracts with localized, geographic barriers to vaccine-associated herd immunity. We link our model results with Census data and two high-resolution surveys to understand the distribution and determinates of spatially accessibility to the COVID-19 vaccine. RESULTS: We find that in early 2021, vaccine deserts were home to over 30 million people, >10% of the US population. Vaccine deserts were concentrated in rural locations and communities with a higher percentage of medically vulnerable populations. We also find that in locations of similar urbanicity, early vaccination distribution disadvantaged neighborhoods with more people of color and older aged residents. CONCLUSION: Given sufficient vaccine supply, data-driven vaccine distribution to vaccine deserts may improve immunization rates and help control COVID-19.

COVID-19 has affected the elderly, people of color, and individuals with chronic illnesses more than the general population. Large barriers to accessing the COVID-19 vaccine could make this problem worse. We used a website called VaccineFinder, which has information on the location of most COVID-19 vaccine doses in the US, to measure vaccine accessibility in early 2021. We then identified vaccine deserts, defined as small US regions with poor access to the COVID-19 vaccine. We found that over 10% of the US lived in a vaccine desert. Overall, we found that vaccines were less available to people in rural areas, people of color, and individuals with chronic illnesses. It will be important to reverse this pattern and ensure enough vaccines are sent to these communities to help reduce the spread of COVID-19.

Inequities in life course criminal legal system sanctions: measuring cumulative involvement.

PURPOSE: The impact of incarceration on health is well known. Yet, most studies measure incarceration alone and miss additional exposure to the criminal legal system over time. We evaluated adult criminal legal sanctions - inclusive of arrests, charges, probation, incarceration - from ages 18-35 and inequities by juvenile sanctions and race. METHODS: Using the National Longitudinal Survey on Youth 1997, a nationally representative data set of adolescents followed into their mid-thirties (1997-2017), we calculated the mean cumulative count, or the average number of criminal legal events per person per study visit, stratified by juvenile sanctions and race. RESULTS: Of 7024 participants, 1679 experienced 3,075 encounters. There were seven arrests, 30 charges, nine probation encounters, and 13 incarceration events /100 participants by age 35. Juvenile sanctions were most common for Black individuals. Among those experiencing juvenile sanctions, Black and White individuals had similar numbers of encounters, but Black individuals had more arrests and incarceration stays. For those without juvenile encounters, Black individuals had more encounters than White individuals. CONCLUSIONS: Research on health effects of criminal legal sanctions must consider encounters beyond incarceration and focus on life course trajectories and racial inequities.

Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study.

Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers. Highlights: Organizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19.Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies.Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level.

Vaccinating children against COVID-19 is crucial to protect schools and communities.

To evaluate the joint impact of childhood vaccination rates and school masking policies on community transmission and severe outcomes due to COVID-19, we utilized a stochastic, agent-based simulation of North Carolina to test 24 health policy scenarios. In these scenarios, we varied the childhood (ages 5 to 19) vaccination rate relative to the adult's (ages 20 to 64) vaccination rate and the masking relaxation policies in schools. We measured the overall incidence of disease, COVID-19-related hospitalization, and mortality from 2021 July 1 to 2023 July 1. Our simulation estimates that removing all masks in schools in January 2022 could lead to a 31% to 45%, 23% to 35%, and 13% to 19% increase in cumulative infections for ages 5 to 9, 10 to 19, and the total population, respectively, depending on the childhood vaccination rate. Additionally, achieving a childhood vaccine uptake rate of 50% of adults could lead to a 31% to 39% reduction in peak hospitalizations overall masking scenarios compared with not vaccinating this group. Finally, our simulation estimates that increasing vaccination uptake for the entire eligible population can reduce peak hospitalizations in 2022 by an average of 83% and 87% across all masking scenarios compared to the scenarios where no children are vaccinated. Our simulation suggests that high vaccination uptake among both children and adults is necessary to mitigate the increase in infections from mask removal in schools and workplaces.

Patterns of Children's Blood Lead Screening and Blood Lead Levels in North Carolina, 2011-2018-Who Is Tested, Who Is Missed?

BACKGROUND: No safe level of lead in blood has been identified. Blood lead testing is required for children on Medicaid, but it is at the discretion of providers and parents for others. Elevated blood lead levels (EBLLs) cannot be identified in children who are not tested. OBJECTIVES: The aims of this research were to identify determinants of lead testing and EBLLs among North Carolina children and estimate the number of additional children with EBLLs among those not tested. METHODS: We linked geocoded North Carolina birth certificates from 2011-2016 to 2010 U.S. Census data and North Carolina blood lead test results from 2011-2018. We estimated the probability of being screened for lead and created inverse probability (IP) of testing weights. We evaluated the risk of an EBLL of ≥3µg/dL at <30 months of age, conditional on characteristics at birth, using generalized linear models and then applied IP weights to account for missing blood lead results among unscreened children. We estimated the number of additional children with EBLLs of all North Carolina children using the IP-weighted population and bootstrapping to produce 95% credible intervals (CrI). RESULTS: Mothers of the 63.5% of children (402,002 of 633,159) linked to a blood lead test result were disproportionately young, Hispanic, Black, American Indian, or on Medicaid. In full models, maternal age ≤20y [risk ratio (RR)=1.10; 95% confidence interval (CI): 1.13, 1.20] or smoking (RR=1.14; 95% CI: 1.12, 1.17); proximity to a major roadway (RR=1.10; 95% CI: 1.05, 1.15); proximity to a lead-releasing Toxics Release Inventory site (RR=1.08; 95% CI: 1.03, 1.14) or a National Emissions Inventory site (RR=1.11; 95% CI: 1.07, 1.14); and living in neighborhoods with more housing built before 1950 (RR=1.10; 95% CI: 1.05, 1.14) or before 1940 (RR=1.18; 95% CI: 1.11, 1.25) or more vacant housing (RR=1.14; 95% CI: 1.11, 1.17) were associated with an increased risk of EBLL, whereas overlap with a public water service system was associated with a decreased risk of EBLL (RR=0.85; 95% CI: 0.83, 0.87). Children of Black mothers were no more likely than children of White mothers to have EBLLs (RR=0.98; 95% CI: 0.96, 1.01). Complete blood lead screening in 2011-2018 may have identified an additional 17,543 (95% CrI: 17,462, 17,650) children with EBLLs ≥3µg/dL. DISCUSSION: Our results indicate that current North Carolina lead screening strategies fail to identify over 30% (17,543 of 57,398) of children with subclinical lead poisoning and that accounting for characteristics at birth alters the conclusions about racial disparities in children's EBLLs. https://doi.org/10.1289/EHP10335.

Exposure to industrial hog operations and gastrointestinal illness in North Carolina, USA.

With 9 million hogs, North Carolina (NC) is the second leading hog producer in the United States. Most hogs are housed at concentrated animal feeding operations (CAFOs), where millions of tons of hog waste can pollute air and water with fecal pathogens that can cause diarrhea, vomiting, and/or nausea (known as acute gastrointestinal illness (AGI)). We used NC's ZIP code-level emergency department (ED) data to calculate rates of AGI ED visits (2016-2019) and swine permit data to estimate hog exposure. Case exposure was estimated as the inverse distances from each hog CAFO to census block centroids, weighting with Gaussian decay and by manure amount per CAFO, then aggregated to ZIP code using population weights. We compared ZIP codes in the upper quartile of hog exposure ("high hog exposed") to those without hog exposure. Using inverse probability of treatment weighting, we created a control with similar demographics to the high hog exposed population and calculated rate ratios using quasi-Poisson models. We examined effect measure modification of rurality and race using adjusted models. In high hog exposed areas compared to areas without hog exposure, we observed a 11% increase (95% CI: 1.06, 1.17) in AGI rate and 21% increase specifically in rural areas (95% CI: 0.98, 1.43). When restricted to rural areas, we found an increased AGI rate among American Indian (RR = 4.29, 95% CI: 3.69, 4.88) and Black (RR = 1.45, 95% CI: 0.98, 1.91) residents. The association was stronger during the week after heavy rain (RR = 1.41, 95% CI: 1.19, 1.62) and in areas with both poultry and swine CAFOs (RR = 1.52, 95% CI: 1.48, 1.57). Residing near CAFOs may increase rates of AGI ED visits. Hog CAFOs are disproportionally built near rural Black and American Indian communities in NC and are associated with increased AGI most strongly in these populations.