Intra-neighborhood associations between residential greenness and blood pressure.

INTRODUCTION: Previous investigations have reported that individuals living in greener neighborhoods have better cardiovascular health. It is unclear whether the effects reported at large geographic scales persist when examined at an intra-neighborhood level. The effects of greenness have not been thoroughly examined using high-resolution metrics of greenness exposure, and how they vary with spatial scales of assessment or participant characteristics. METHODS: We conducted a cross-sectional assessment of associations between blood pressure and multiple high-resolution measures of residential area greenness in spatially concentrated HEAL Study cohort of the Green Heart Project. We employed generalized linear models, accounting for individual-level covariates, to examine associations between different high-resolution measures of greenness and blood pressure among 667 participants in a 4 sq. mile contiguous neighborhood area in Louisville, KY. RESULTS: In adjusted models, we observed significant inverse associations between residential greenness, measured by leaf area index (LAI), and systolic blood pressure (SBP) within 150-250 m and 500 m of homes, but not for Normalized Difference Vegetation Index (NDVI) or grass cover. Weaker associations were also found with diastolic blood pressure (DBP). Significant positive associations were observed between LAI and SBP among participants who reported being female, White, without obesity, non-exercisers, non-smokers, younger age, of lower income, and who had high nearby roadway traffic. We found few significant associations between grass cover and SBP, but an inverse association in those with obesity, but positive associations for those without obesity. CONCLUSIONS: We found that leaf surface area of trees around participants home is strongly associated with lower blood pressure, with little association with grass cover. These effects varied with participant characteristics and spatial scales. More research is needed to test causative links between greenspace types and cardiovascular health and to develop population-, typology-, and place-based evidence to inform greening interventions.

Wastewater threshold as an indicator of COVID-19 cases in correctional facilities for public health response: A modeling study.

Although prison facilities are not fully isolated from the communities in which they are located, most of the population is confined and requires high levels of health vigilance and protection. This study aimed to examine the dynamic relationship between facility-level wastewater viral concentrations and the probability of at least one positive COVID-19 case within the facility. The study period was from January 11, 2021 to May 8, 2023. Wastewater samples were collected and analyzed for SARS-CoV-2 (N1) and pepper mild mottle virus (PMMoV) three times weekly across 14 prison facilities in Kentucky (USA). Positive clinical case reports were also provided. A hierarchical Bayesian facility-level temporal model with a latent lagged process was developed. We modeled facility-specific SARS-CoV-2 (N1) normalized by the PMMoV wastewater concentration ratio threshold associated with at least one COVID-19 clinical case at an 80 % probability. The threshold differed among facilities. Across the 14 facilities, our model demonstrates a mean capture rate of 94.95 % via the N1/PMMoV ratio threshold with pts≥0.5. However, as the pts threshold was set higher, such as at ≥0.9, the mean capture rate of the model was reduced to 60 %. This robust performance underscores the effectiveness of the model for accurately detecting the presence of positive COVID-19 cases among incarcerated people. The findings of this study provide a facility-specific threshold model for public health response based on frequent wastewater surveillance.

Environmental Levels of Volatile Organic Compounds, Race, and Socioeconomic Markers Correlate with Areas of High Colorectal Cancer Incidence.

BACKGROUND: Ambient levels of volatile organic compounds (VOCs) released from nearby industrial plants have shown positive associations with increased colorectal cancer (CRC) rates. The objective of this study is to analyze the distribution of CRC in the context of socioeconomic status and its correlation with community environmental data. METHODS: A retrospective study analyzed CRC patients from 2021 to 2023. The census tracts of the patients' residential addresses were obtained, and CRC rates were calculated for each census tract. Socioeconomic data was gathered on these communities. Environmental VOC measurements were obtained from the National Scale Air Toxics Assessment. All datapoints were compared to statewide levels. RESULTS: Three census tracts in the county had higher CRC cases comparatively. These areas exhibited higher incidence rates and localized clusters of CRC cases, higher distribution of Black or African Americans, lower household incomes, lower home values, and lower educational attainment. VOC measurements in these census tracts had higher levels compared to county and state averages: specifically, 10.68% higher than county and 48.07% higher than state benzene levels (0.52 µg/m3 clusters vs 0.47µg/m3 county vs 0.35 µg/m3 state), 10.84% and 129.15% higher toluene (1.65 µg/m3 vs 1.49 vs 0.72 µg/m3), and 15.64% and 141.87% higher butadiene (0.048 µg/m3 vs 0.041 µg/m3 vs 0.020 µg/m3). CONCLUSION: This study illustrates a positive correlation between higher ambient exposure to VOCs with increased CRC incidence. These findings underscore the potential interplay of environmental factors, socioeconomic determinants, and environmental injustice when considering strategies to address health disparities and CRC incidence.

Dynamic SARS-CoV-2 surveillance model combining seroprevalence and wastewater concentrations for post-vaccine disease burden estimates.

BACKGROUND: Despite wide scale assessments, it remains unclear how large-scale severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. METHODS: We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021-August 2021 in Jefferson County, Kentucky (USA). Our susceptible ( S ), vaccinated ( V ), variant-specific infected ( I 1 and I 2 ), recovered ( R ), and seropositive ( T ) model ( S V I 2 R T ) tracked prevalence longitudinally. This was related to wastewater concentration. RESULTS: Here we show the 64% county vaccination rate translate into about a 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence is a 24-fold increase of infection counts, which correspond to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration have the strongest correlation (r = 0.95) at 1 week lag. CONCLUSIONS: Our study underscores the importance of continuing environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.

It is unclear how large-scale COVID-19 vaccination impacts wastewater concentration or overall disease burden. Here, we developed a mathematical surveillance model that allows estimation of overall vaccine impact based on the amount of SARS-CoV-2 in wastewater, seroprevalence and the number of cases admitted to hospitals between April 2021­August 2021 in Jefferson County, Kentucky USA. We found that a 64% vaccination coverage correlated to a 61% decrease in COVID-19 cases. The emergence of the SARS-CoV-2 Delta variant during the time of the surveillance directly correlated with a sharp increase in infection incidence as well as viral counts in wastewater. The hospitalization burden was closely reflected by the viral count found in the wastewater, indicating that post-vaccine environmental surveillance can be an effective method of estimating changing disease prevalence in future pandemics.

Wastewater Surveillance for Identifying SARS-CoV-2 Infections in Long-Term Care Facilities, Kentucky, USA, 2021-2022.

Persons living in long-term care facilities (LTCFs) were disproportionately affected by COVID-19. We used wastewater surveillance to detect SARS-CoV-2 infection in this setting by collecting and testing 24-hour composite wastewater samples 2-4 times weekly at 6 LTCFs in Kentucky, USA, during March 2021-February 2022. The LTCFs routinely tested staff and symptomatic and exposed residents for SARS-CoV-2 using rapid antigen tests. Of 780 wastewater samples analyzed, 22% (n = 173) had detectable SARS-CoV-2 RNA. The LTCFs reported 161 positive (of 16,905) SARS-CoV-2 clinical tests. The wastewater SARS-CoV-2 signal showed variable correlation with clinical test data; we observed the strongest correlations in the LTCFs with the most positive clinical tests (n = 45 and n = 58). Wastewater surveillance was 48% sensitive and 80% specific in identifying SARS-CoV-2 infections found on clinical testing, which was limited by frequency, coverage, and rapid antigen test performance.

Vibrio cholerae and Salmonella Typhi culture-based wastewater or non-sewered sanitation surveillance in a resource-limited region.

BACKGROUND: In resource-limited regions, relying on individual clinical results to monitor community diseases is sometimes not possible. Establishing wastewater and non-sewered sanitation surveillance systems can offer opportunities to improve community health. OBJECTIVE: We provide our experience of establishing a wastewater and non-sewered sanitation surveillance laboratory in Malawi, a resource-limited region, for Vibrio cholerae and Salmonella serotype Typhi. METHODS: Three locations (inclusive of 8 discrete sample collection sites in total) in the Blantyre District were studied for nine weeks, from September 6 to November 1, 2022. Grab samples were collected weekly. We piloted locally available culture-based medical diagnostic methods for V. cholerae and S. Typhi in wastewater, followed by confirmation analysis of the isolates using reverse transcription polymerase chain reaction (RT-PCR). RESULTS: Bacterial counts ranged from up to 106 colony-forming units/mL for V. cholerae and up to 107 colony-forming units/mL for S. Typhi. RT-PCR of the isolates showed that the available culture-based medical diagnostic methods were successful in detecting V. cholerae but were less accurate for S. Typhi in wastewater. IMPACT STATEMENT: This experience serves as a catalyst for the development and validation of alternative wastewater surveillance analytical methods that are not dependent solely on RT-PCR. In this field trial conducted in Africa, new data-driven approaches were developed to promote early-level wastewater research and expand analysis options in resource-limited settings. Although culture-based methods are labor-intensive and have some limitations, we suggest initially leveraging the overlap with the locally available medical testing capacity for V. cholerae, whereas S. Typhi with RT-PCR may still be required. Wastewater analysis may be acceptable for V. cholerae and S. Typhi, which have a high degree of clinical case underreporting, fecal shedding, short incubation periods, and clear outbreak trends, predominantly in low- and middle-income countries.

Predictive power of wastewater for nowcasting infectious disease transmission: A retrospective case study of five sewershed areas in Louisville, Kentucky.

BACKGROUND: Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. METHODS: We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. FINDINGS: Adding wastewater data minimally improved the predictive performance of nowcasts compared to a model fitted to case and death data (Weighted Interval Score (WIS) 0.208 versus 0.223), and reduced the predictive performance compared to a model fitted to deaths data (WIS 0.517 versus 0.500). Adding wastewater data to deaths data improved the nowcasts agreement to estimates from models using cases and deaths data. These findings were consistent across individual sewersheds as well as for models fit to the aggregated total data of 5 sewersheds. Retrospective reconstructions of epidemiological dynamics created using different combinations of data were in general agreement (coverage >75%). INTERPRETATION: These findings show wastewater data may be valuable for infectious disease nowcasting when clinical surveillance data are absent, such as early in a pandemic or in low-resource settings where systematic collection of epidemiologic data is difficult.

Biomonitoring of Exposures to Solvents and Metals in Electronics Manufacturing Facilities in Batam, Indonesia.

Concerns about chemical exposure in the electronics manufacturing industry have long been recognized, but data are lacking in Southeast Asia. We conducted a study in Batam, Indonesia, to evaluate chemical exposures in electronics facilities, using participatory research and biological monitoring approaches. A convenience sample of 36 workers (28 exposed, 8 controls) was recruited, and urine samples were collected before and after shifts. Five solvents (acetone, methyl ethyl ketone, toluene, benzene, and xylenes) were found in 46%-97% of samples, and seven metals (arsenic, cadmium, cobalt, tin, antimony, lead, and vanadium) were detected in 60%-100% of samples. Biological monitoring and participatory research appeared to be useful in assessing workers' exposure when workplace air monitoring is not feasible due to a lack of cooperation from the employer. Several logistical challenges need to be addressed in future biomonitoring studies of electronics workers in Asia in factories where employers are reluctant to track workers' exposure and health.

Resting state functional connectivity changes following mindfulness-based stress reduction predict improvements in disease control for patients with asthma.

BACKGROUND: The staggering morbidity associated with chronic inflammatory diseases can be reduced by psychological interventions, including Mindfulness-Based Stress Reduction (MBSR). Proposed mechanisms for MBSR's beneficial effects include changes in salience network function. Salience network perturbations are also associated with chronic inflammation, including airway inflammation in asthma, a chronic inflammatory disease affecting approximately 10% of the population. However, no studies have examined whether MBSR-related improvements in disease control are related to changes in salience network function. METHODS: Adults with asthma were randomized to 8 weeks of MBSR or a waitlist control group. Resting state functional connectivity was measured using fMRI before randomization, immediately post-intervention, and 4 months post-intervention. Using key salience network regions as seeds, we calculated group differences in change in functional connectivity over time and examined whether functional connectivity changes were associated with increased mindfulness, improved asthma control, and decreased inflammatory biomarkers. RESULTS: The MBSR group showed greater increases in functional connectivity between salience network regions relative to the waitlist group. Improvements in asthma control correlated with increased functional connectivity between the salience network and regions important for attention control and emotion regulation. Improvements in inflammatory biomarkers were related to decreased functional connectivity between the salience network and other networks. CONCLUSIONS: Increased resting salience network coherence and connectivity with networks that subserve attention and emotion regulation may contribute to the benefits of MBSR for patients with asthma. Understanding the neural underpinnings of MBSR-related benefits in patients is a critical step towards optimizing brain-targeted interventions for chronic inflammatory disease management.

Wastewater-Informed Digital Advertising as a COVID-19 Geotargeted Neighborhood Intervention: Jefferson County, Kentucky, 2021-2022.

We sought to deliver a geotargeted digital health advertising intervention. We assessed risk of community infection through an integrated public health and wastewater rubric and delivered advertisements between November 2021 and April 2022 in Louisville, Kentucky. The average daily click-through rates for the campaigns were 0.19%, 0.15%, and 0.13%. Results show potential for digital public health interventions that are geographically anchored to subcity sewersheds and community interest and willingness to engage with targeted wastewater-themed public health messaging. (Am J Public Health. 2024;114(1):34-37. https://doi.org/10.2105/AJPH.2023.307439).

What is the functional reach of wastewater surveillance for respiratory viruses, pathogenic viruses of concern, and bacterial antibiotic resistance genes of interest?

BACKGROUND: Despite a clear appreciation of the impact of human pathogens on community health, efforts to understand pathogen dynamics within populations often follow a narrow-targeted approach and rely on the deployment of specific molecular probes for quantitative detection or rely on clinical detection and reporting. MAIN TEXT: Genomic analysis of wastewater samples for the broad detection of viruses, bacteria, fungi, and antibiotic resistance genes of interest/concern is inherently difficult, and while deep sequencing of wastewater provides a wealth of information, a robust and cooperative foundation is needed to support healthier communities. In addition to furthering the capacity of high-throughput sequencing wastewater-based epidemiology to detect human pathogens in an unbiased and agnostic manner, it is critical that collaborative networks among public health agencies, researchers, and community stakeholders be fostered to prepare communities for future public health emergencies or for the next pandemic. A more inclusive public health infrastructure must be built for better data reporting where there is a global human health risk burden. CONCLUSIONS: As wastewater platforms continue to be developed and refined, high-throughput sequencing of human pathogens in wastewater samples will emerge as a gold standard for understanding community health.

The Green Heart Project: Objectives, Design, and Methods.

The Green Heart Project is a community-based trial to evaluate the effects of increasing greenery on urban environment and community health. The study was initiated in 2018 in a low-to-middle-income mixed-race residential area of nearly 28,000 residents in Louisville, KY. The 4 square mile area was surveyed for land use, population characteristics, and greenness, and assigned to 8 paired clusters of demographically- and environmentally matched "target" (T) and adjacent "control" (C), clusters. Ambient levels of ultrafine particles, ozone, oxides of nitrogen, and environmental noise were measured in each cluster. Individual-level data were acquired during in-person exams of 735 participants in Wave 1 (2018-2019) and 545 participants in Wave 2 (2021) to evaluate sociodemographic and psychosocial factors. Blood, urine, nail, and hair samples were collected to evaluate standard cardiovascular risk factors, inflammation, stress, and pollutant exposure. Cardiovascular function was assessed by measuring arterial stiffness and flow-mediated dilation. After completion of Wave 2, more than 8,000 mature, mostly evergreen, trees and shrubs were planted in the T clusters in 2022. Post planting environmental and individual-level data were collected during Wave 3 (2022) from 561 participants. We plan to continue following changes in area characteristics and participant health to evaluate the long-term impact of increasing urban greenery.

Addressing the challenges of establishing quality wastewater or non-sewered sanitation-based surveillance, including laboratory and epidemiological considerations, in Malawi.

Learning from clinical laboratories, wastewater or environmental (including non-sewered sanitation) environmental microbiology laboratories can be established in resource-limited settings that focus on pathogen detection and pandemic prevention. Transparent discussions on the laboratory challenges and adaptations required for this can help meet the future requirements of health research and surveillance. This report aims to describe the challenges encountered when setting up a wastewater or environmental laboratory for multipathogen surveillance in Malawi, a resource-limited setting, as well as the lessons learnt. We identified nine unifying themes: what to monitor, human resource capacity, indicators of data quality, equipment availability, supply of consumable goods, ongoing operation and maintenance of the laboratory, application of localised guidelines for laboratory operations, lack of real-time clinical correlation for calibration and localised ethical considerations. Over our 6-month timeline, only Salmonella typhi, Vibrio cholerae and severe acute respiratory syndrome coronavirus 2 analyses were set-up. However, we were unable to set-up measles and tuberculosis analyses owing largely to supply delays. By establishing this system at a public higher education academic laboratory in Malawi, we have ensured that ongoing capacity building and piloting of public health work is conducted in the country, rather than relying on non-governmental organisations or reference laboratory support beyond national borders. This work is not intended to replace clinical testing but rather demonstrates the potential for adapting higher education academic laboratory infrastructure to add wastewater or environmental (including non-sewered sanitation) samples, where appropriate, as additive epidemiological data for better pandemic preparedness.

Wastewater-based epidemiology for comprehensive communitywide exposome surveillance: A gradient of metals exposure.

Community wastewater surveillance is an established means to measure health threats. Exposure to toxic metals as one of the key environmental contaminants has been attracting public health attention as exposure can be related to contamination across air, water, and soil as well as associated with individual factors. This research uses Jefferson County, Kentucky, as an urban exposome case study to analyze sub-county metal concentrations in wastewater as a possible indicator of community toxicant exposure risk, and to test the feasibility of using wastewater to identify potential community areas of elevated metals exposure. Variability in wastewater metal concentrations were observed across the county; 19 of the 26 sites had one or more metal results greater than one standard deviation above the mean and were designated areas of concern. Additionally, thirteen of the nineteen sites were of increased concern with levels greater than two standard deviations above the mean. This foundational research found variability in several instances between smaller nested upstream contributing neighborhood sewersheds when measured in the associated downstream treatment plant. Wastewater provides an opportunity to look at integrated toxicology to complement other toxicology data, looking at where people live and what toxicants need to be focused on to protect the health of people in that area.

Wastewater Surveillance for SARS-CoV-2 at Long-Term Care Facilities: Mixed Methods Evaluation.

BACKGROUND: Wastewater surveillance provided early indication of COVID-19 in US municipalities. Residents of long-term care facilities (LTCFs) experienced disproportionate morbidity and mortality early in the COVID-19 pandemic. We implemented LTCF building-level wastewater surveillance for SARS-CoV-2 at 6 facilities in Kentucky to provide early warning of SARS-CoV-2 in populations considered vulnerable. OBJECTIVE: This study aims to evaluate the performance of wastewater surveillance for SARS-CoV-2 at LTCFs in Kentucky. METHODS: We conducted a mixed methods evaluation of wastewater surveillance following Centers for Disease Control and Prevention (CDC) guidelines for evaluating public health surveillance systems. Evaluation steps in the CDC guidelines were engaging stakeholders, describing the surveillance system, focusing the evaluation design, gathering credible evidence, and generating conclusions and recommendations. We purposively recruited stakeholders for semistructured interviews and undertook thematic content analysis of interview data. We integrated wastewater, clinical testing, and process data to characterize or calculate 7 surveillance system performance attributes (simplicity, flexibility, data quality, sensitivity and positive predictive value [PPV], timeliness, representativeness, and stability). RESULTS: We conducted 8 stakeholder interviews. The surveillance system collected wastewater samples (N=811) 2 to 4 times weekly at 6 LTCFs in Kentucky from March 2021 to February 2022. Synthesis of credible evidence indicated variable surveillance performance. Regarding simplicity, surveillance implementation required moderate human resource and technical capacity. Regarding flexibility, the system efficiently adjusted surveillance frequency and demonstrated the ability to detect additional pathogens of interest. Regarding data quality, software identified errors in wastewater sample metadata entry (110/3120, 3.53% of fields), technicians identified polymerase chain reaction data issues (140/7734, 1.81% of reactions), and staff entered all data corrections into a log. Regarding sensitivity and PPV, using routine LTCF SARS-CoV-2 clinical testing results as the gold standard, a wastewater SARS-CoV-2 signal of >0 RNA copies/mL was 30.6% (95% CI 24.4%-36.8%) sensitive and 79.7% (95% CI 76.4%-82.9%) specific for a positive clinical test at the LTCF. The PPV of the wastewater signal was 34.8% (95% CI 27.9%-41.7%) at >0 RNA copies/mL and increased to 75% (95% CI 60%-90%) at >250 copies/mL. Regarding timeliness, stakeholders received surveillance data 24 to 72 hours after sample collection, with delayed reporting because of the lack of weekend laboratory staff. Regarding representativeness, stakeholders identified challenges delineating the population contributing to LTCF wastewater because of visitors, unknown staff toileting habits, and the use of adult briefs by some residents preventing their waste from entering the sewer system. Regarding stability, the reoccurring cost to conduct 1 day of wastewater surveillance at 1 facility was approximately US $144.50, which included transportation, labor, and materials expenses. CONCLUSIONS: The LTCF wastewater surveillance system demonstrated mixed performance per CDC criteria. Stakeholders found surveillance feasible and expressed optimism regarding its potential while also recognizing challenges in interpreting and acting on surveillance data.

Using wastewater to overcome health disparities among rural residents.

The SARS-CoV-2 pandemic highlighted the need for novel tools to promote health equity. There has been a historical legacy around the location and allocation of public facilities (such as health care) focused on efficiency, which is not attainable in rural, low-density, United States areas. Differences in the spread of the disease and outcomes of infections have been observed between urban and rural populations throughout the COVID-19 pandemic. The purpose of this article was to review rural health disparities related to the SARS-CoV-2 pandemic while using evidence to support wastewater surveillance as a potentially innovative tool to address these disparities more widely. The successful implementation of wastewater surveillance in resource-limited settings in South Africa demonstrates the ability to monitor disease in underserved areas. A better surveillance model of disease detection among rural residents will overcome issues around the interactions of a disease and social determinants of health. Wastewater surveillance can be used to promote health equity, particularly in rural and resource-limited areas, and has the potential to identify future global outbreaks of endemic and pandemic viruses.

Generative AI as a Tool for Environmental Health Research Translation.

One valuable application for generative artificial intelligence (AI) is summarizing research studies for non-academic readers. We submitted five articles to Chat Generative Pre-trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight-oriented activities, such as the production of eighth-grade reading level summaries, and summaries highlighting the most important findings and real-world applications. The general summary request was rated lower. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.

Beyond COVID-19: Designing Inclusive Public Health Surveillance by Including Wastewater Monitoring.

Wastewater-based epidemiology is a promising and expanding public health surveillance method. The current wastewater testing trajectory to monitor primarily at community wastewater treatment plants was necessitated by immediate needs of the pandemic. Going forward, specific consideration should be given to monitoring vulnerable and underserved communities to ensure inclusion and rapid response to public health threats. This is particularly important when clinical testing data are insufficient to characterize community virus levels and spread in specific locations. Now is a timely call to action for equitably protecting health in the United States, which can be guided with intentional and inclusive wastewater monitoring.

Greenness and equity: Complex connections between intra-neighborhood contexts and residential tree planting implementation.

Associations between neighborhood greenness and socioeconomic status (SES) are established, yet intra-neighborhood context and SES-related barriers to tree planting remain unclear. Large-scale tree planting implementation efforts are increasingly common and can improve human health, strengthen climate adaptation, and ameliorate environmental inequities. Yet, these efforts may be ineffective without in-depth understanding of local SES inequities and barriers to residential planting. We recruited 636 residents within and surrounding the Oakdale Neighborhood of Louisville, Kentucky, USA, and evaluated associations of individual and neighborhood-level sociodemographic indicators with greenness levels at multiple scales. We offered no-cost residential tree planting and maintenance to residents within a subsection of the neighborhood and examined associations of these sociodemographic indicators plus baseline greenness levels with tree planting adoption among 215 eligible participants. We observed positive associations of income with Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) within all radii around homes, and within yards of residents, that varied in strength. There were stronger associations of income with NDVI in front yards but LAI in back yards. Among Participants of Color, associations between income and NDVI were stronger than with Whites and exhibited no association with LAI. Tree planting uptake was not associated with income, education, race, nor employment status, but was positively associated with lot size, home value, lower population density, and area greenness. Our findings reveal significant complexity of intra-neighborhood associations between SES and greenness that could help shape future research and equitable greening implementation. Results show that previously documented links between SES and greenspace at large scales extend to residents' yards, highlighting opportunities to redress greenness inequities on private property. Our analysis found that uptake of no-cost residential planting and maintenance was nearly equal across SES groups but did not redress greenness inequity. To inform equitable greening, further research is needed to evaluate culture, norms, perceptions, and values affecting tree planting acceptance among low-SES residents.

Stratified Simple Random Sampling Versus Volunteer Community-Wide Sampling for Estimates of COVID-19 Prevalence.

Objectives. To evaluate community-wide prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using stratified simple random sampling. Methods. We obtained data for the prevalence of SARS-CoV-2 in Jefferson County, Kentucky, from adult random (n = 7296) and volunteer (n = 7919) sampling over 8 waves from June 2020 through August 2021. We compared results with administratively reported rates of COVID-19. Results. Randomized and volunteer samples produced equivalent prevalence estimates (P < .001), which exceeded the administratively reported rates of prevalence. Differences between them decreased as time passed, likely because of seroprevalence temporal detection limitations. Conclusions. Structured targeted sampling for seropositivity against SARS-CoV-2, randomized or voluntary, provided better estimates of prevalence than administrative estimates based on incident disease. A low response rate to stratified simple random sampling may produce quantified disease prevalence estimates similar to a volunteer sample. Public Health Implications. Randomized targeted and invited sampling approaches provided better estimates of disease prevalence than administratively reported data. Cost and time permitting, targeted sampling is a superior modality for estimating community-wide prevalence of infectious disease, especially among Black individuals and those living in disadvantaged neighborhoods. (Am J Public Health. 2023;113(7):768-777. https://doi.org/10.2105/AJPH.2023.307303).