Assessing the impact of areal unit selection and the modifiable areal unit problem on associative statistics between cases of tick-borne disease and entomological indices.

The modifiable areal unit problem (MAUP) is a cause of statistical and visual bias when aggregating data according to spatial units, particularly when spatial units may be changed arbitrarily. The MAUP is a concern in vector-borne disease research when entomological metrics gathered from point-level sampling data are related to epidemiological data aggregated to administrative units like counties or ZIP Codes. Here, we assess the statistical impact of the MAUP when calculating correlations between randomly aggregated cases of anaplasmosis in New York State during 2017 and a geostatistical layer of an entomological risk index for Anaplasma phagocytophilum in blacklegged ticks (Ixodes scapularis Say, Acari: Ixodidae) collected during the fall of 2017. Correlations were also calculated using various administrative boundaries for comparison. We also demonstrate the impact of the MAUP on data visualization using choropleth maps and offer pycnophylactic interpolation as an alternative. Polygon simulations indicate that increasing the number of polygons decreases correlation coefficients and their variability. Correlation coefficients calculated using ZIP Code tabulation area and Census tract polygons were beyond 4 standard deviations from the mean of the simulated correlation coefficients. These results indicate that using smaller polygons may not best incorporate the geographical context of the tick-borne disease system, despite the tendency of researchers to strive for more granular spatial data and associations.

Habitat suitability mapping using logistic regression analysis of long-term bioacoustic bat survey dataset in the Cassadaga Creek watershed (USA).

Bat species show global ecological importance, yet their numbers are declining worldwide. Understanding bat-habitat interactions is crucial in terms of developing effective conservation plans. In an effort to model bat habitat suitability in the Cassadaga Creek watershed, long-term bioacoustic bat data (spanning 2009-2020) was compiled, georeferenced and statistically analyzed using logistic regression techniques. In total, 1600 bat occurrence records from five species of bat (559 Eptesicus fuscus, 560 Lasionycteris noctivagans, 143 Lasiurus borealis, 260 Lasiurus cinereus, and 78 Myotis lucifugus) were paired with pseudo-absence points to study the relationship between bat calling behavior and land cover. All bats but Myotis lucifugus had a statistically significant relationship with forested land cover, and all bats had negative interactions with agricultural habitats. Geospatial data was coupled with the statistical output to create maps of habitat suitability and echolocation calling density. This work provides a model that can be employed worldwide to evaluate bat habitat needs or patterns in echolocation behavior. Future research will incorporate a more recently collected dataset that is of greater geographic diversity with a larger number of environmental variables in the species distribution model.

Mapping access to endovascular stroke care in the USA and implications for transport models.

BACKGROUND: The purpose of this cross-sectional study was to determine the percentage of the US population with 60 min ground or air access to accredited or state-designated endovascular-capable stroke centers (ECCs) and non-endovascular capable stroke centers (NECCs) and the percentage of NECCs with an ECC within a 30 min drive. METHODS: Stroke centers were identified and classified broadly as ECCs or NECCs. Geographic mapping of stroke centers was performed. The population was divided into census blocks, and their centroids were calculated. Fastest air and ground travel times from centroid to nearest ECC and NECC were estimated. RESULTS: Overall, 49.6% of US residents had 60 min ground access to ECCs. Approximately 37.7% (113 million) lack 60 min ground or air access to ECCs. Approximately 84.4% have 60 min access to NECCs. Ground-only access was available to 77.9%. Approximately 738 NECCs (45.4%) had an ECC within a 30 min drive. CONCLUSION: Nearly one-third of the US population lacks 60 min access to endovascular stroke care, but this is highly variable. Transport models and planning of additional centers should be tailored to each state depending on location and proximity of existing facilities.

Chiropteran chatter in Chautauqua, NY (USA): Using acoustic sampling and geographic information systems to create a baseline bat habitat dataset.

Understanding bat habitat use and how bat activity changes in response to differing habitats across time and space is critical in developing and implementing effective bat conservation actions. To investigate the utility of geographic information systems (GIS) in studying bat habitat interactions, habitat delineations and bioacoustic sampling were conducted along two transects in Chautauqua County, NY (USA) from mid-May until the end of August 2013. Surveys were vehicular, and driven between 29 and 32 kmph in order to match bats' flying speed. They were conducted starting 30 min after sunset on nights where the temperature was greater than 13 °C. In total, twenty surveys were completed, and 1248 bat calls were identified to species. Mixed models regression analysis revealed significant interactions among all of the species of bat analyzed in the model. The model was supported with a secondary analysis comparing bat call density with land cover. This study supports the hypothesis that bats forage in different habitats at the species level and indicates the importance of forested areas to bats. Additionally, the methodology for this study has the potential to gather large data sets in a short period of time, while collecting data on several species of bat at once and has been shown to be useful in identifying important habitat features for bats using bioacoustics and geospatial analysis. Since the data has been collected following state guidelines, the dataset and its analysis establish a baseline for future data collection campaigns and in performing a similar analysis for other regions within the state of New York or areas worldwide.

A Pilot Study of Chicago Waterways as Reservoirs of Multidrug-Resistant Enterobacteriaceae (MDR-Ent) in a High-Risk Region for Community-Acquired MDR-Ent Infection in Children.

Community-acquired multidrug resistant Enterobacteriaceae (MDR-Ent) infections continue to increase in the United States. In prior studies, we identified neighboring regions in Chicago, Illinois, where children have 5 to 6 times greater odds of MDR-Ent infections. To prevent community spread of MDR-Ent, we need to identify the MDR-Ent reservoirs. A pilot study of 4 Chicago waterways for MDR-Ent and associated antibiotic resistance genes (ARGs) was conducted. Three waterways (A1 to A3) are labeled safe for "incidental contact recreation" (e.g., kayaking), and A4 is a nonrecreational waterway that carries nondisinfected water. Surface water samples were collected and processed for standard bacterial culture and shotgun metagenomic sequencing. Generally, A3 and A4 (neighboring waterways which are not hydraulically connected) were strikingly similar in bacterial taxa, ARG profiles, and abundances of corresponding clades and genera within the Enterobacteriaceae Additionally, total ARG abundances recovered from the full microbial community were strongly correlated between A3 and A4 (R2 = 0.97). Escherichia coli numbers (per 100 ml water) were highest in A4 (783 most probable number [MPN]) and A3 (200 MPN) relative to A2 (84 MPN) and A1 (32 MPN). We found concerning ARGs in Enterobacteriaceae such as MCR-1 (colistin), Qnr and OqxA/B (quinolones), CTX-M, OXA and ACT/MIR (beta-lactams), and AAC (aminoglycosides). We found significant correlations in microbial community composition between nearby waterways that are not hydraulically connected, suggesting cross-seeding and the potential for mobility of ARGs. Enterobacteriaceae and ARG profiles support the hypothesized concerns that recreational waterways are a potential source of community-acquired MDR-Ent.

Retrospective suspect screening reveals previously ignored antibiotics, antifungal compounds, and metabolites in Bangladesh surface waters.

Densely populated countries in Asia, such as Bangladesh, are considered to be major contributors to the increased occurrence of global antimicrobial resistance (AMR). Several factors make low-and middle-income countries vulnerable to increased emergence and spread of AMR in the environment including limited regulations on antimicrobial drug use, high volume of antimicrobials used in human medicine and agricultural production, and poor wastewater management. Previous monitoring campaigns to investigate the presence of antibiotics in the aquatic environment have employed targeted analysis in which selected antibiotics are measured using liquid chromatography with tandem mass spectrometry (LC/MS/MS). However, this approach can miss several important contaminants that can contribute to the selective pressure that promotes maintenance and dissemination of antibiotic resistance genes (ARGs) in the environment. Nontarget analysis by suspect screening and reanalysis of stored digital data of previously ran samples can provide information on analytes that were formerly uncharacterized and may be chemicals of emerging concern (CECs). In this study, surface waters in both urban and rural sites in Bangladesh were collected and analyzed for the presence of antibiotic residues and other pharmaceuticals. Utilizing targeted analysis, the antibiotics with the highest concentrations detected were ciprofloxacin (1407 ng/L) and clarithromycin (909 ng/L). In addition, using high-resolution LC/MS/MS in the first ever application of retrospective analysis in samples from Bangladesh, additional antibiotics clindamycin, lincomycin, linezolid, metronidazole, moxifloxacin, nalidixic acid, and sulfapyridine were detected. Prevalence of amoxicillin transformation products in surface waters was also confirmed. In addition, medicinal and agricultural antifungal compounds were frequently found in Bangladeshi surface waters. This later finding - the near ubiquity of antifungal agents in environmental samples - is of particular concern, as it may be contributing to the alarming rise of multi-drug resistant fungal (e.g. Candida auris) disease recently seen in humans throughout the world.

A cyberGIS approach to spatiotemporally explicit uncertainty and global sensitivity analysis for agent-based modeling of vector-borne disease transmission.

While agent-based models (ABMs) provide an effective means for investigating complex interactions between heterogeneous agents and their environment, they may hinder an improved understanding of phenomena being modeled due to inherent challenges associated with uncertainty in model parameters. This study uses uncertainty analysis and global sensitivity analysis (UA-GSA) to examine the effects of such uncertainty on model outputs. The statistics used in UA-GSA, however, are likely to be affected by the modifiable areal unit problem (MAUP). Therefore, to examine the scale varying-effects of model inputs, UA-GSA needs to be performed at multiple spatiotemporal scales. Unfortunately, performing comprehensive UA-GSA comes with considerable computational cost. In this paper, our cyberGIS-enabled spatiotemporally explicit UA-GSA approach helps to not only resolve the computational burden, but also to measure dynamic associations between model inputs and outputs. A set of computational and modeling experiments shows that input factors have scale-dependent impacts on modeling output variability. In other words, most of the input factors have relatively large impacts in a certain region, but may not influence outcomes in other regions. Furthermore, our spatiotemporally explicit UA-GSA approach sheds light on the effects of input factors on modeling outcomes that are particularly spatially and temporally clustered, such as the occurrence of communicable disease transmission.

Using Multiple Scale Spatio-Temporal Patterns for Validating Spatially Explicit Agent-Based Models.

Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this paper, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.

Using Multiple Scale Space-Time Patterns in Variance-Based Global Sensitivity Analysis for Spatially Explicit Agent-Based Models.

Sensitivity analysis (SA) in spatially explicit agent-based models (ABMs) has emerged to address some of the challenges associated with model specification and parameterization. For spatially explicit ABMs, the comparison of spatial or spatio-temporal patterns has been advocated to evaluate models. Nevertheless, less attention has been paid to understanding the extent to which parameter values in ABMs are responsible for mismatch between model outcomes and observations. In this paper, we propose the use of multiple scale space-time patterns in variance-based global sensitivity analysis (GSA). A vector-borne disease transmission model was used as the case study. Input factors used in GSA include one related to the environment (introduction rates), two related to interactions between agents and environment (level of herd immunity, mosquito population density), and one that defines agent state transition (mosquito extrinsic incubation period). The results show parameters related to interactions between agents and the environment have great impact on the ability of a model to reproduce observed patterns, although the magnitudes of such impacts vary by space-time scales. Additionally, the results highlight the time-dependent sensitivity to parameter values in spatially explicit ABMs. The GSA performed in this study helps in identifying the input factors that need to be carefully parameterized in the model to implement ABMs that well reproduce observed patterns at multiple space-time scales.

Examining time-dependent effects of water, sanitation, and hygiene (WASH) interventions using an agent-based model.

The effects of water, sanitation, and hygiene (WASH) interventions have been well acknowledged to reduce the risk from diarrheal disease-causing pathogens. In spite of the recognized importance of WASH interventions on the reduction of diarrheal disease, there are still gaps in the understanding of the time-varying effects of interventions. To bridge this research gap, we developed agent-based models (ABMs) of diarrheal disease transmission in a community context. In the model, infections occur via two pathways: (i) between household members within the household environment and (ii) from the community environment outside the household. To measure the effectiveness of WASH interventions, we performed global sensitivity analysis (GSA) at the macro and micro temporal scales, varying the level of intervention coverage in the community. We simulated three intervention strategies, implemented separately in the experiments. The clean drinking water intervention, sanitation intervention, and hand washing intervention had similar success rates in the long-term. The handwashing intervention had the largest immediate effect. This highlights that proper short- and long-term intervention strategies need to be considered for disease control and the effective management of limited resources.

Les effets des interventions sur l'eau, les sanitaires et l'hygiène (WASH) ont été bien reconnus pour réduire le risque d'agents pathogènes causant des maladies diarrhéiques. En dépit de l'importance reconnue des interventions WASH sur la réduction des maladies diarrhéiques, il reste des lacunes dans la compréhension des variations en fonction du temps des effets des interventions. Pour combler cette lacune en matière de recherche, nous avons développé des modèles à base d'agents (MBA) de la transmission des maladies diarrhéiques dans un contexte communautaire. Dans le modèle, les infections se produisent via deux voies: (1) entre les membres du ménage dans l'environnement du ménage et (2) depuis l'environnement de la communauté en dehors du ménage. Pour mesurer l'efficacité des interventions WASH, nous avons effectué une analyse de sensibilité globale (ASG) aux échelles macro et micro-temporelles, en faisant varier le niveau de couverture des interventions dans la communauté. Nous avons simulé trois stratégies d'intervention, mises en œuvre séparément dans les expériences. Les interventions sur l'eau potable, sur les sanitaires et sur le lavage des mains ont eu des taux de réussite similaires à long terme. L'intervention sur le lavage des mains a eu l'effet immédiat le plus important. Cela montre qu'il faut envisager des stratégies d'intervention appropriées à court et à long terme pour lutter contre la maladie et pour la gestion efficace des ressources limitées.

Global antimicrobial resistance: a complex and dire threat with few definite answers.

Alors que divers organismes internationaux ont récemment proposé des plans pour la création de systèmes de surveillance de la résistance antimicrobienne (RAM), la plupart des PRMF ne disposent pas des infrastructures et des ressources pour le faire efficacement. La RAM est donc un problème majeur d'équité en matière de santé, mais aussi un exemple de la connexion dans notre monde unique: les populations les plus à risque disposent des mécanismes de surveillance et de confinement les plus médiocres; dans le même temps, la migration mondiale, les voyages et le commerce nous rendent tous vulnérables. Les mesures que nous utilisons actuellement ne capturent pas de manière significative l'impact potentiel de la RAM aux niveaux sanitaire, économique et sociétal plus large. La surveillance mondiale de la RAM devrait inclure une surveillance étroite de l'utilisation d'antibiotiques chez les animaux, ainsi que les concentrations de divers produits chimiques libérés dans l'environnement. En fin de compte, les efforts coordonnés de divers scientifiques et parties prenantes, dans diverses disciplines et dans le monde, sont essentiels pour relever les défis pressants de la RAM mondiale croissante.

Do sedentary behavior and physical activity spatially cluster? Analysis of a population-based sample of Boston adolescents.

Sedentary behavior and lack of physical activity are key modifiable behavioral risk factors for chronic health problems, such as obesity and diabetes. Little is known about how sedentary behavior and physical activity among adolescents spatially cluster. The objective was to detect spatial clustering of sedentary behavior and physical activity among Boston adolescents. Data were used from the 2008 Boston Youth Survey Geospatial Dataset, a sample of public high school students who responded to a sedentary behavior and physical activity questionnaire. Four binary variables were created: 1) TV watching (>2 hours/day), 2) video games (>2 hours/day), 3) total screen time (>2 hours/day); and 4) 20 minutes/day of physical activity (≥5 days/week). A spatial scan statistic was utilized to detect clustering of sedentary behavior and physical activity. One statistically significant cluster of TV watching emerged among Boston adolescents in the unadjusted model. Students inside the cluster were more than twice as likely to report > 2 hours/day of TV watching compared to respondents outside the cluster. No significant clusters of sedentary behavior and physical activity emerged. Findings suggest that TV watching is spatially clustered among Boston adolescents. Such findings may serve to inform public health policymakers by identifying specific locations in Boston that could provide opportunities for policy intervention. Future research should examine what is linked to the clusters, such as neighborhood environments and network effects.

The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model.

Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.

Geospatial clustering in sugar-sweetened beverage consumption among Boston youth.

The objective was to detect geospatial clustering of sugar-sweetened beverage (SSB) intake in Boston adolescents (age = 16.3 ± 1.3 years [range: 13-19]; female = 56.1%; White = 10.4%, Black = 42.6%, Hispanics = 32.4%, and others = 14.6%) using spatial scan statistics. We used data on self-reported SSB intake from the 2008 Boston Youth Survey Geospatial Dataset (n = 1292). Two binary variables were created: consumption of SSB (never versus any) on (1) soda and (2) other sugary drinks (e.g., lemonade). A Bernoulli spatial scan statistic was used to identify geospatial clusters of soda and other sugary drinks in unadjusted models and models adjusted for age, gender, and race/ethnicity. There was no statistically significant clustering of soda consumption in the unadjusted model. In contrast, a cluster of non-soda SSB consumption emerged in the middle of Boston (relative risk = 1.20, p = .005), indicating that adolescents within the cluster had a 20% higher probability of reporting non-soda SSB intake than outside the cluster. The cluster was no longer significant in the adjusted model, suggesting spatial variation in non-soda SSB drink intake correlates with the geographic distribution of students by race/ethnicity, age, and gender.

Local spatial clustering in youths' use of tobacco, alcohol, and marijuana in Boston.

BACKGROUND: Understanding geographic variation in youth drug use is important for both identifying etiologic factors and planning prevention interventions. However, little research has examined spatial clustering of drug use among youths by using rigorous statistical methods. OBJECTIVES: The purpose of this study was to examine spatial clustering of youth use of tobacco, alcohol, and marijuana. METHODS: Responses on tobacco, alcohol, and marijuana use from 1,292 high school students ages 13-19 who provided complete residential addresses were drawn from the 2008 Boston Youth Survey Geospatial Dataset. Response options on past month use included "none," "1-2," "3-9," and "10 or more." The response rate for each substance was approximately 94%. Spatial clustering of youth drug use was assessed using the spatial Bernoulli model in the SatScan™ software package. RESULTS: Approximately 12%, 36%, and 18% of youth reported any past-month use of tobacco, alcohol, and/or marijuana, respectively. Two clusters of elevated past tobacco use among Boston youths were generated, one of which was statistically significant. This cluster, located in the South Boston neighborhood, had a relative risk of 5.37 with a p-value of 0.00014. There was no significant localized spatial clustering in youth past alcohol or marijuana use in either the unadjusted or adjusted models. CONCLUSION: Significant spatial clustering in youth tobacco use was found. Finding a significant cluster in the South Boston neighborhood provides reason for further investigation into neighborhood characteristics that may shape adolescents' substance use behaviors. This type of research can be used to evaluate the underlying reasons behind spatial clustering of youth substance and to target local drug abuse prevention interventions and use.

Improving dengue virus capture rates in humans and vectors in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance strategy.

Dengue is of public health importance in tropical and sub-tropical regions. Dengue virus (DENV) transmission dynamics was studied in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance of 93 hospitalized subjects with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled from 208 houses with household members with a history of fever, located within a 200-m radius of an initiate case. Of 409 associates, 86 (21%) had laboratory-confirmed DENV infection. A total of 63 (1.8%) of the 3,565 mosquitoes collected were dengue polymerase chain reaction positive (PCR+). There was a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and Aedes mosquitoes. The viral detection rate from human hosts and mosquito vectors in this study was higher than previously observed by the study team in the same geographic area using different methodologies. We propose that the sampling strategy used in this study could support surveillance of DENV transmission and vector interactions.

Dengue virus neutralizing antibody levels associated with protection from infection in thai cluster studies.

BACKGROUND: Long-term homologous and temporary heterologous protection from dengue virus (DENV) infection may be mediated by neutralizing antibodies. However, neutralizing antibody titers (NTs) have not been clearly associated with protection from infection. METHODOLOGY/PRINCIPAL FINDINGS: Data from two geographic cluster studies conducted in Kamphaeng Phet, Thailand were used for this analysis. In the first study (2004-2007), cluster investigations of 100-meter radius were triggered by DENV-infected index cases from a concurrent prospective cohort. Subjects between 6 months and 15 years old were evaluated for DENV infection at days 0 and 15 by DENV PCR and IgM ELISA. In the second study (2009-2012), clusters of 200-meter radius were triggered by DENV-infected index cases admitted to the provincial hospital. Subjects of any age ≥6 months were evaluated for DENV infection at days 0 and 14. In both studies, subjects who were DENV PCR positive at day 14/15 were considered to have been "susceptible" on day 0. Comparison subjects from houses in which someone had documented DENV infection, but the subject remained DENV negative at days 0 and 14/15, were considered "non-susceptible." Day 0 samples were presumed to be from just before virus exposure, and underwent plaque reduction neutralization testing (PRNT). Seventeen "susceptible" (six DENV-1, five DENV-2, and six DENV-4), and 32 "non-susceptible" (13 exposed to DENV-1, 10 DENV-2, and 9 DENV-4) subjects were evaluated. Comparing subjects exposed to the same serotype, receiver operating characteristic (ROC) curves identified homotypic PRNT titers of 11, 323 and 16 for DENV-1, -2 and -4, respectively, to differentiate "susceptible" from "non-susceptible" subjects. CONCLUSIONS/SIGNIFICANCE: PRNT titers were associated with protection from infection by DENV-1, -2 and -4. Protective NTs appeared to be serotype-dependent and may be higher for DENV-2 than other serotypes. These findings are relevant for both dengue epidemiology studies and vaccine development efforts.

Examination of how neighborhood definition influences measurements of youths' access to tobacco retailers: a methodological note on spatial misclassification.

Measurements of neighborhood exposures likely vary depending on the definition of "neighborhood" selected. This study examined the extent to which neighborhood definition influences findings regarding spatial accessibility to tobacco retailers among youth. We defined spatial accessibility to tobacco retailers (i.e., tobacco retail density, closest tobacco retailer, and average distance to the closest 5 tobacco retailers) on the basis of circular and network buffers of 400 m and 800 m, census block groups, and census tracts by using residential addresses from the 2008 Boston Youth Survey Geospatial Dataset (n = 1,292). Friedman tests (to compare overall differences in neighborhood definitions) were applied. There were differences in measurements of youths' access to tobacco retailers according to the selected neighborhood definitions, and these were marked for the 2 spatial proximity measures (both P < 0.01 for all differences). For example, the median average distance to the closest 5 tobacco retailers was 381.50 m when using specific home addresses, 414.00 m when using census block groups, and 482.50 m when using census tracts, illustrating how neighborhood definition influences the measurement of spatial accessibility to tobacco retailers. These analyses suggest that, whenever possible, egocentric neighborhood definitions should be used. The use of larger administrative neighborhood definitions can bias exposure estimates for proximity measures.

A spatially explicit approach to the study of socio-demographic inequality in the spatial distribution of trees across Boston neighborhoods.

The racial/ethnic and income composition of neighborhoods often influences local amenities, including the potential spatial distribution of trees, which are important for population health and community wellbeing, particularly in urban areas. This ecological study used spatial analytical methods to assess the relationship between neighborhood socio-demographic characteristics (i.e. minority racial/ethnic composition and poverty) and tree density at the census tact level in Boston, Massachusetts (US). We examined spatial autocorrelation with the Global Moran's I for all study variables and in the ordinary least squares (OLS) regression residuals as well as computed Spearman correlations non-adjusted and adjusted for spatial autocorrelation between socio-demographic characteristics and tree density. Next, we fit traditional regressions (i.e. OLS regression models) and spatial regressions (i.e. spatial simultaneous autoregressive models), as appropriate. We found significant positive spatial autocorrelation for all neighborhood socio-demographic characteristics (Global Moran's I range from 0.24 to 0.86, all P=0.001), for tree density (Global Moran's I=0.452, P=0.001), and in the OLS regression residuals (Global Moran's I range from 0.32 to 0.38, all P<0.001). Therefore, we fit the spatial simultaneous autoregressive models. There was a negative correlation between neighborhood percent non-Hispanic Black and tree density (rS=-0.19; conventional P-value=0.016; spatially adjusted P-value=0.299) as well as a negative correlation between predominantly non-Hispanic Black (over 60% Black) neighborhoods and tree density (rS=-0.18; conventional P-value=0.019; spatially adjusted P-value=0.180). While the conventional OLS regression model found a marginally significant inverse relationship between Black neighborhoods and tree density, we found no statistically significant relationship between neighborhood socio-demographic composition and tree density in the spatial regression models. Methodologically, our study suggests the need to take into account spatial autocorrelation as findings/conclusions can change when the spatial autocorrelation is ignored. Substantively, our findings suggest no need for policy intervention vis-à-vis trees in Boston, though we hasten to add that replication studies, and more nuanced data on tree quality, age and diversity are needed.