High-income Neighborhoods Research Articles

Telehealth Initiation of Buprenorphine for Opioid Use Disorder: Patient Characteristics and Outcomes.

The COVID-19 pandemic exacerbated access barriers for patients with opioid use disorder. Telehealth presents an opportunity to improve access, treatment quality, and patient outcomes. To determine patient characteristics associated with initiating buprenorphine treatment via telehealth and to examine how telehealth initiation is associated with access, treatment quality, and health outcomes. This cross-sectional study used deidentified insurance claims to identify opioid use disorder adult patients initiating buprenorphine treatment between March 1, 2020, and November 30, 2021. Multivariable logistic regression assessed determinants of telehealth initiation. Propensity score matching addressed observed differences between in-person and telehealth initiators. Treatment quality outcomes included initiation within 14 days of diagnosis, engagement (at least 2 opioid use disorder-related visits), and any buprenorphine refill during the study period. Health outcomes included opioid overdose and opioid use disorder-related emergency department and inpatient visits. We identified 23,565 adult buprenorphine initiators, including 3314 (14.1%) patients using telehealth. Younger patients (OR 0.91 to 0.77), females (OR 1.18), South (OR 1.63) and Midwest (OR 1.27) regions, rural area (OR 1.12), and higher-income (OR 1.16) neighborhood residents were more likely to use telehealth. Telehealth patients were more likely than in-person patients (54.5% vs. 48.4%; adjusted odds ratio (AOR), 1.29; 95% CI, 1.19-1.40) to stay engaged with opioid use disorder treatment, and more likely to refill buprenorphine during the study period (83.6% vs. 79.0%, AOR 1.37; 95% CI, 1.23-1.52). Telehealth initiation of buprenorphine was associated with 36% lower overdose rate than in-person initiation (adjusted incidence rate ratio 0.64; 95% CI, 0.45-0.94). The two groups evidenced no significant differences in opioid use disorder-related ED visit and hospitalization. Our findings suggest that telehealth-initiated buprenorphine treatment is associated with reduced opioid overdose rate and improved patient engagement. Our findings strengthen the case for extending telehealth exemptions and prescribing flexibilities for treatment.

Pubertal timing, neighborhood income, and mental health in boys and girls: Findings from the adolescent brain cognitive development study

Early pubertal timing is associated with youth mental health problems, with association amplified or mitigated by characteristics of the residential neighborhood. Yet, limited research simultaneously examines the roles of neighborhood context and biological sex in this association. This study fills this research gap by examining sex-specific associations between pubertal timing and neighborhood income with youth mental health problems (internalizing and externalizing symptoms) in a longitudinal cohort of early adolescents in the United States (US). Participants were 9201 youth aged 9 or 10 years from the Adolescent Brain Cognitive Development Study. Pubertal timing was the average of parent- and youth-reported pubertal status standardized within sex and age. Outcome variables were youths’ internalizing and externalizing symptoms assessed at 1-year follow-up via parent survey. We evaluated interaction effects between pubertal timing and neighborhood income in a series of sex-stratified linear mixed effect models, adjusted for family and personal sociodemographic characteristics. In girls, earlier pubertal timing was associated with more internalizing (β = 0.06, p < 0.001) and externalizing problems (β = 0.07, p < 0.001) at 1-year follow-up, not moderated by neighborhood income. In boys, earlier pubertal timing was associated with more externalizing problems among youth living in high-income neighborhoods, but not among those in low-income neighborhoods (interaction-p = 0.006). Results suggest that pubertal timing may affect youth mental health differentially in boys and girls, depending on the neighborhood contexts. These findings highlight the importance of both biological and social forces in shaping adolescent mental health and, thus, have public health and clinical implications for health promotion.

Agency factors associated with first response systems that improve out-of-hospital cardiac arrest outcomes

BackgroundData are conflicting regarding the association between first responder (FR) intervention and improved outcomes after out-of-hospital cardiac arrest (OHCA). We evaluated characteristics of agencies that have positive associations between FR interventions and outcomes. MethodsWe analyzed the 2016–2021 national Cardiac Arrest Registry to Enhance Survival (CARES). We defined the exposures as FR CPR and AED. The outcome was survival with favorable neurologic status. We used logistic regression models to evaluate the association between FR interventions with OHCA outcome for each agency, stratifying agencies into positive association (95% confidence interval above 1) and no/inverse association (95% confidence below or including 1). We compared characteristics between cohorts. ResultsFor the association between FR CPR and outcomes, 21 agencies caring for 42,856 OHCAs had a positive association; 371 agencies caring for 449,824 OHCAs had no association. For FR AED, 47 agencies caring for 103,120 OHCAs had a positive association; 262 agencies caring for 327,761 OHCAs had no association. Comparing agency characteristics for FR CPR, agencies with a positive association had more annual OHCAs (+300), lower FR CPR rate (-11.3%), and lower FR AED rate (-10.8%). Comparing FR AED, agencies with a positive association had more OHCAs per year (+150.5), lower FR CPR rate (-6.8%), lower FR AED rate (-13.3%), lower response time (-0.6 minutes), and more OHCAs from high-income neighborhoods (+3.7%). ConclusionFR AED more commonly had a positive association with outcomes than FR CPR. Agencies with better outcomes from FR interventions treated more OHCAs and had lower rates of FR intervention.

Examining the spatial distribution of parking tickets in San Francisco neighborhoods: An overlooked form of urban inequality?

ABSTRACT Parking citations are among the most common minor offenses, which can result in millions of dollars in revenue each year for cities. However, it is an open question whether the spatial distribution of parking citations is equitable in terms of neighborhoods’ racial/ethnic composition and economic standing. To the extent that parking citations are issued in nonwhite or low-income neighborhoods, this would represent a form of urban inequality. Thus, for the present study, we assess this understudied proposition by collecting data on neighborhoods in San Francisco, California, and estimating a series of negative binomial regression models. Although we find that measures of nonwhite ethnicities are non-significant in relation to all types of parking citations, we do find evidence that low-income neighborhoods have significantly higher rates of both street cleaning and metered parking citations, in comparison to high-income neighborhoods. We also determine that the effect of neighborhood income is moderated by the concentration of certain ethnicities. The implications of these findings for urban sociology and public policy are discussed.

Frozen city: Analysing the disruption and resilience of urban activities during a heavy snowfall event using Google Popular Times

Understanding the impact of climate change on cities is fundamental to address the increasing occurrence of extreme weather events. This research aims to raise awareness and emphasise the need and potential of proactive measures to mitigate the adverse effects of climate change. To do so, this article conducts a case study for a huge snowfall that occurred in the city of Madrid (Spain) in January 2021, blocking the city for several days. The analysis is based on geolocated big data sourced from Google Popular Times (GPT), which captures the occupancy of establishments throughout the city over the entire study period. An exploratory spatial-temporal analysis has been conducted to examine the impact of the snowfall on the daily activities of the city, taking into consideration the demographic characteristics. The findings reveal a distinction in the impact of the snowfall on activities. Essential activities experience less impact compared to leisure activities. Furthermore, at the socio-economic level, the impact on low-income neighbourhoods is observed to be less affected than on high-income neighbourhoods. The implications of this research contribute to the body of knowledge on climate change resilience and adaptation, providing valuable insights for urban management strategies and informing future research in this field.

The heterogeneous impacts of widespread upzoning: Lessons from Auckland, New Zealand

Zoning reform is increasingly recognised as an important strategy to increase housing affordability and environmental sustainability. Few cities have undertaken significant upzoning of low-density neighbourhoods, making the 2016 Auckland Unitary Plan (AUP) probably the most ambitious zoning reform in the world. Parcels zoned for single houses previously dominated Auckland, but three-quarters of them now allow multiple units. Existing studies have documented the building boom that followed this zoning reform, yet the relatively rare case offers additional insights. In this article, we use appraisal, census and zoning data on over 200,000 parcels in Auckland to answer three research questions about the heterogeneous impacts of the AUP. First, to what extent did upzoning increase the appraised value of properties’ redevelopment options? Second, did upzoning increase appraised property values to a greater degree in higher-income and more centrally located neighbourhoods? Finally, was zoning reform in Auckland significantly influenced by similar political pressures as in other countries? That is, was upzoning less likely (and downzoning more likely) in higher-income neighbourhoods? The answers to these three questions are substantially, it’s complicated, and yes.

Factors associated with undergoing microdissection testicular sperm extraction among men with non-obstructive azoospermia following evaluation by a reproductive urologist.

Microdissection testicular sperm extraction (mTESE) is the gold standard treatment for men with non-obstructive azoospermia (NOA). However, many men do not elect to pursue this surgical intervention. We aimed to identify factors associated with NOA patients undergoing mTESE after initial evaluation by a reproductive urologist (RU) through a retrospective cohort study. We retrospectively reviewed NOA patient who underwent evaluation by a RU between 2002-2018. Demographic and clinical data were collected. Our primary outcome was electing to undergo mTESE. 44.4% (75/169) of NOA men underwent mTESE. These patients earned significantly higher median neighborhood income ($133,000 vs. $97,000, P<0.001), spent fewer years trying to conceive before seeking care {1.3 [interquartile range (IQR): 1-3] vs. 2.3 (IQR: 1-5), P=0.012}, and were more likely to be married (79.7% vs. 53.9%, P=0.001). On univariate analysis, married men [odds ratio (OR) 3.37, 95% confidence interval (CI): 1.67-6.79, P=0.001] and men with higher neighborhood income (OR 1.14, 95% CI: 1.06-1.21, P<0.001) were more likely to undergo mTESE, while couples attempting to conceive for a longer period of time prior to initial evaluation were less likely to undergo mTESE (OR 0.79, 95% CI: 0.68-0.92, P=0.003). On multivariable regression analysis, marital status and years attempting to conceive remained significantly associated with NOA patients undergoing mTESE (OR 4.61, 95% CI: 1.16-18.25, P=0.03; OR 0.67, 95% CI: 0.52-0.88, P=0.003, respectively). Higher neighborhood income and marital status were positively associated with patients undergoing mTESE, while couples who attempted to conceive for a longer period of time before seeking infertility care were less likely to undergo mTESE.

Urban mosquito distributions are modulated by socioeconomic status and environmental traits in the USA.

The distribution of mosquitoes and associated vector diseases (e.g., West Nile, dengue, and Zika viruses) is likely to be a function of environmental conditions in the landscape. Urban environments are highly heterogeneous in the amount of vegetation, standing water, and concrete structures covering the land at a given time, each having the capacity to influence mosquito abundance and disease transmission. Previous research suggests that socioeconomic status is correlated with the ecology of the landscape, with lower-income neighborhoods generally having more concrete structures and standing water via residential abandonment, garbage dumps, and inadequate sewage. Whether these socioecological factors affect mosquito distributions across urban environments in the USA remains unclear. Here, we present a meta-analysis of 42 paired observations from 18 articles testing how socioeconomic status relates to the overall mosquito burden in urban landscapes in the USA. We also analyzed how socioecological covariates (e.g., abandoned buildings, vegetation, education, and garbage containers) varied across socioeconomic status in the same mosquito studies. The meta-analysis revealed that lower-income neighborhoods (regions with median household incomes <US$50,000 per household per year) are exposed to 63% greater mosquito densities and mosquito-borne illnesses compared with higher-income neighborhoods (≥US$50,000 per household per year). One common species of urban mosquito (Aedes aegypti) showed the strongest relationship with socioeconomic status, with Ae. aegypti being 126% higher in low-income than high-income neighborhoods. We also found that certain socioecological covariates correlated with median household income. Garbage, trash, and plastic containers were found to be 67% higher in low-income neighborhoods, whereas high-income neighborhoods tended to have higher levels of education. Together, these results indicate that socioecological factors can lead to disproportionate impacts of mosquitoes on humans in urban landscapes. Thus, concerted efforts to manage mosquito populations in low-income urban neighborhoods are required to reduce mosquito burden for the communities most vulnerable to human disease.

On learning agent-based models from data

Agent-Based Models (ABMs) are used in several fields to study the evolution of complex systems from micro-level assumptions. However, a significant drawback of ABMs is their inability to estimate agent-specific (or “micro”) variables, which hinders their ability to make accurate predictions using micro-level data. In this paper, we propose a protocol to learn the latent micro-variables of an ABM from data. We begin by translating an ABM into a probabilistic model characterized by a computationally tractable likelihood. Next, we use a gradient-based expectation maximization algorithm to maximize the likelihood of the latent variables. We showcase the efficacy of our protocol on an ABM of the housing market, where agents with different incomes bid higher prices to live in high-income neighborhoods. Our protocol produces accurate estimates of the latent variables while preserving the general behavior of the ABM. Moreover, our estimates substantially improve the out-of-sample forecasting capabilities of the ABM compared to simpler heuristics. Our protocol encourages modelers to articulate assumptions, consider the inferential process, and spot potential identification problems, thus making it a useful alternative to black-box data assimilation methods.

Racial and income characteristics and the burden of illness among metastatic prostate cancer patients.

e17064 Background: The incidence of metastatic prostate cancer has increased dramatically between 2010 and 2017 in the United States. Since the racial and ethnic mix of the population of the United States (U.S.) have changed between the years 2010 and 2020–it is extremely important to understand its effects on prostate cancer outcomes. Therefore, we investigated the burden of illness across racial groups and income levels among patients diagnosed with metastatic prostate cancer. Methods: This study utilized the U.S. 2017 National Inpatient Sample database to identify hospitalizations with a primary diagnosis of prostate cancers. We evaluated associations between race and income levels, and the burden of illness (total charges and length of stay (LOS)) adjusting for patient and clinical factors with multivariable generalized linear models. Results: A total of 63,880 metastatic prostate cancer patients were included in the study, and the median [IQR] age was 74 [66, 82]. There were 65.6% Whites, 20.6% Blacks, 7.7% Hispanics, and 6.1% Asians and Others. Blacks had a higher prevalence in the age group 45-55 (34.2%), when compared to 55-64 (29.8%), or &gt; 65 (17.6%) age group. There were only 10% Blacks and 4.9% Hispanics living in high-income neighborhoods, whereas this was 75.5% for Whites. In the adjusted analysis, compared to the Whites, Hispanics (1.43; 95%CI-1.29- 1.57), and Asians and Others (1.39; 95%CI- 1.25- 1.56) had a higher total charge; and compared to Whites, Blacks had a higher LOS (1.28; 95%CI-1.15-1.44). Compared to high-income neighborhoods, those living in the 26th to 50th percentile had a lower total charge (0.86; 95%CI- 0.78-0.94). Compared to the &gt; 65 years age group, the 44-55 age group had a lower total charge (0.73; 95%CI-0.61-0.89). Compared to patients with Medicare, those with Private Insurance (0.87; 95%CI- 0.80-0.94) and Self-pay and Others (0.73; 95C%CI-0.62–0.86) had a lower total charge. And when compared to non-elective admissions, elective admissions had a higher total charge (1.44; 95%CI-1.29- 1.59). Conclusions: Hispanics and Asians and Others had a higher burden of illness, and Blacks had a higher LOS. Patients who reside in lower income neighborhoods had lower total charges. Understanding prostate cancer outcomes by race and income is crucial to designing strategies to improve access to care.

Environmental goods provision and gentrification: Evidence from MillionTreesNYC

Urban trees offer extensive environmental benefits. However, the distribution of trees in urban areas often disproportionately favors higher-income neighborhoods. Implementing tree-planting programs in lower-income neighborhoods may provide environmental amenity values but may also lead to unintended consequences, such as gentrification. This paper focuses on one of the largest tree-planting programs in the U.S., the MillionTreesNYC Program, and estimates the impact of an increased supply of urban street trees on housing values and neighborhood compositions. The results demonstrate that the additional urban street trees did serve as an environmental amenity, resulting in higher housing values and attracting more white, educated, and young households to areas with new trees. However, the gentrification effects of this tree-planting program were relatively small, with minimal change in community composition. These findings suggest that it is possible to provide public goods without significant displacement of the existing population while also reaping the numerous benefits trees offer to urban areas.

Evaluating the quality of street trees in Washington, D.C.: Implications for environmental justice

Urban street trees are part of the bundle of environmental amenities that support healthy social, economic, and environmental functions. In this study, we systematically evaluate the quality of 196,825 street trees at the US. Census tract level in Washington D.C., as well as related impacts from socioeconomic, landscape patterns and environmental factors using Ordinary least-squares (OLS) regression, geographically weighted regression (GWR) and structural equation modeling (SEM). Our results reveal that environmental and socioeconomic factors can explain most of the spatial variation of street tree quality in Washington, D.C. There is a substantial statistical negative relationship between median household income and the percent of street trees under stress, which provided the evidence of the inequities of street tree quality in Washington D.C. Higher-income neighborhoods exhibited a lower proportion of street trees under stress. In addition, the extreme summer temperature is positively associated with the proportion of street trees under stress. The quality of street trees is directly impacted by environmental and landscape pattern factors. There is also an indirect impact from socioeconomic factor toward quality of street trees. Our findings suggest that multiple variables, related to income, age, education, landscape pattern, and environment contribute to the quality of street trees in D.C. Based upon our findings, we identify strategies and insights for urban street tree management in DC to not only address environmental inequity and injustice, but also promote a more inclusive and resilient urban greenery system.

Variations in all-cause mortality, premature mortality and cause-specific mortality among persons with diabetes in Ontario, Canada

IntroductionPatients with diabetes have a higher risk of mortality compared with the general population. Large population-based studies that quantify variations in mortality risk for patients with diabetes among subgroups in...

GIS Mapping and Breast Cancer Health Care Access Gaps for African American Women.

Black women face an unequal opportunity to survive breast cancer compared with White women. One would expect that US metropolitan areas with high percentages of Black people should report similar racial disparities in breast health. Yet, this is not the case. To provide insights about breast cancer disparities in cities with above-average and below-average racial disparities, we use GIS analysis. We depict racial composition and income categories on the same map with mammography facility locations to distinguish unique patterns of mammography access, a critical resource for breast cancer care. Looking more closely at low health disparities cities, a general and consistent pattern arises. Both White and Black people are concentrated in middle-income neighborhoods. Further, MQSA-certified facilities are not clustered in affluent areas but tend to be centrally located in the middle of the city or highly dispersed across the city, regardless of income. Our findings are consistent with the hypothesis that metropolitan areas that have a preponderance of racially segregated low-income Black households-a characteristic of neighborhoods that have experienced a history of racism and disinvestment-are more likely to experience disparities in access to primary breast care than middle-income Black, middle-income White, or high-income White neighborhoods.

Disparities in Adult Patient Selection for Extracorporeal Membrane Oxygenation in the United States: A Population-Level Study.

Rationale: Disparities in patient selection for advanced therapeutics in health care have been identified in multiple studies, but it is unclear if disparities exist in patient selection for extracorporeal membrane oxygenation (ECMO), a rapidly expanding critical care resource. Objectives: To determine if disparities exist in patient selection for ECMO based on sex, primary insurance, and median income of the patient's neighborhood. Methods: In a retrospective cohort study using the Nationwide Readmissions Database 2016-2019, we identified patients treated with mechanical ventilation (MV) and/or ECMO with billing codes. Patient sex, insurance, and income level for patients receiving ECMO were compared with the patients treated with MV only, and hierarchical logistic regression with the hospital as a random intercept was used to determine odds of receiving ECMO based on patient demographics. Results: We identified 2,170,752 MV hospitalizations with 18,725 cases of ECMO. Among patients treated with ECMO, 36.1% were female compared with 44.5% of patients treated with> MV only (adjusted odds ratio [aOR] for ECMO, 0.73; 95% confidence interval [CI], 0.70-0.75). Of patients treated with ECMO, 38.1% had private insurance compared with 17.4% of patients treated with MV only. Patients with Medicaid were less likely to receive ECMO than patients with private insurance (aOR, 0.55; 95% CI, 0.52-0.57). Patients treated with ECMO were more likely to live in the highest-income neighborhoods compared with patients treated with MV only (25.1% vs. 17.3%). Patients living in the lowest-income neighborhoods were less likely to receive ECMO than those living in the highest-income neighborhoods (aOR, 0.63; 95% CI, 0.60-0.67). Conclusions: Significant disparities exist in patient selection for ECMO. Female patients, patients with Medicaid, and patients living in the lowest-income neighborhoods are less likely to be treated with ECMO. Despite possible unmeasured confounding, these findings were robust to multiple sensitivity analyses. On the basis of previouswork describing disparities in other areas of health care, wespeculate that limited access in some neighborhoods, restrictive/biased interhospital transfer practices, differences in patient preferences, and implicit provider bias may contribute to the observed differences. Future studies with more granular data are needed to identify and modify drivers of observed disparities.

Impact of a Publicly-Funded Pharmacare Program on Prescription Stimulant use Among Children and Youth: A Population-Based Observational Natural Experiment.

Stimulants are first-line pharmacotherapy for individuals with attention-deficit hyperactivity disorder. However, disparities in drug coverage may contribute to inequitable treatment access. In January 2018, the government of Ontario, Canada, implemented a publicly-funded program (OHIP+) providing universal access to medications at no cost to children and youth between the ages of 0 and 24. In April 2019, the program was amended to cover only children and youth without private insurance. We studied whether these policy changes were associated with changes in prescription stimulant dispensing to Ontario children and youth. We conducted a population-based observational natural experiment study of stimulant dispensing to children and youth in Ontario between January 2013 and March 2020. We used interventional autoregressive integrated moving average models to estimate the association between OHIP+ and its subsequent modification with stimulant dispensing trends. The implementation of OHIP+ was associated with a significant immediate increase in the monthly rate of stimulant dispensing of 53.6 individuals per 100,000 population (95% confidence interval [CI], 36.8 to 70.5 per 100,000) and a 14.2% (95% CI, 12.8% to 15.6%) relative percent increase in stimulant dispensing rates between December 2017 and March 2019 (1198.6 vs. 1368.7 per 100,000 population). The April 2019 OHIP+ program amendment was associated with an increase in monthly stimulant dispensing trends of 10.2 individuals per 100,000 population (95% CI, 5.0 to 15.5), with rates increasing 7.5% (95% CI, 6.2% to 8.7%) between March 2019 and March 2020 (1368.7 vs. 1470.8 per 100,000 population). These associations were most pronounced among males, children and youth living in the highest income neighbourhoods and individuals aged 20 to 24. A publicly-funded pharmacare program was associated with more children and youth being dispensed stimulants.

Effectiveness of Screening for Household Gun Ownership in an Urban Primary Care Clinic.

Gun-related suicide and homicide are leading causes of death among children. Little is known about the effectiveness of screening for gun ownership in primary care. We examined positive gun ownership screens over a 2.5-year period in a pediatric primary care clinic. The main outcome was a positive screen for gun ownership. The main predictors included insurance type, neighborhood median income, number of clinic visits, and other social needs. Of 19 163 patients, 474 (2.5%) screened positive for gun ownership. Patients with private insurance and from higher income neighborhoods had 2 to 3 times higher odds of a positive screen. Patients with more visits and with food insecurity had approximately 2 to 4 times the odds of a positive screen for household gun ownership. In conclusion, the rate of positive gun ownership screens was very low and far below known gun ownership rates. Improved screening methods could better identify opportunities for gun safety advocacy.

Beyond costs: How urban form could limit the uptake of residential solar PV systems in low-income neighborhoods in Ghana

This paper examines the relationship between urban form, residential rooftop solar PV potential, and levelized cost of electricity (LCOE) in high-income, middle-class, and low-income neighborhoods in Accra, Ghana. Using building footprint data, ArcGIS Pro, and linear regression analysis, we find a statistically significant association between urban form parameters (building density, neighborhood compactness, building footprint area, suitable rooftop area, and near distance between buildings) and the rooftop solar PV potential in all the three types of neighborhoods. However, the well-planned high-income neighborhood exhibited the highest rooftop solar PV potential with low LCOE values for most houses, while the lowest rooftop PV potential and highest LCOE values were found in the largely unplanned low-income neighborhood. The low-income neighborhood exhibited higher density with clustered building patterns and, consequently, lower rooftop PV potential. The LCOE ranged between $0.02/kWh-$0.19/kWh for most buildings, with 92 %, 74 %, and 51 % of houses in the high-income, middle-class, and low-income neighborhoods falling within this range, respectively. We conclude that while capital subsidies for residential solar PV can boost their uptake by urbanites, their effectiveness could be limited in low-income neighborhoods due to the limitations imposed by their urban form. It may be more appropriate for policy interventions to target such neighborhoods with community solar schemes while targeting high-income neighborhoods with building integrated solar photovoltaics.

Property crime and violent crime in Detroit: spatial association with built environment before and during COVID-19

This study expands the literature by finding the associations of land use (LU) and road-related Built Environment (BE) with property and violent crime in Detroit from 2019 to 2021. It builds two spatial models with a wide range of built environment elements and sociodemographic information. Findings indicate that the retail and office LU proportion, bus stop density, and density of roads of less than 40 miles per hour are positively linked with crime rates. Conversely, block groups' median income, population density, and tenure length are inversely associated with crime rates. Single-family houses experienced more violent crime in low-income neighborhoods and less in high income neighborhoods. Bus stop densities in downtown were more positively associated with violent crime in 2020–2021 than in the pre-pandemic time. This study advances understanding related to the BE–crime relationship during the pandemic, sheds new light on street-related BE, and leaves essential evidence for local policymakers in Detroit.

Exploring the spatiotemporal factors affecting bicycle-sharing demand during the COVID-19 pandemic.

This study investigates the roles of the socio-economic, land use, built environment, and weather factors in shaping up the demand for bicycle-sharing trips during the COVID-19 pandemic in Toronto. It uses "Bike Share Toronto" ridership data of 2019 and 2020 and a two-stage methodology. First, multilevel modelling is used to analyze how the factors affect monthly station-level trip generation during the pandemic compared to pre-pandemic period. Then, a geographically weighted regression analysis is performed to better understand how the relationships vary by communities and regions. The study results indicate that the demand of the service for commuting decreased, and the demand for recreational and maintenance trips increased significantly during the pandemic. In addition, higher-income neighborhoods are found to generate fewer weekday trips, whereas neighbourhoods with more immigrants experienced an increase in bike-share ridership during the pandemic. Moreover, the pandemic trip generation rates are more sensitive to the availability of bicycle facilities within station buffers than pre-pandemic rates. The results also suggest significant spatial heterogeneity in terms of the level of influence of the explanatory factors on the demand for bicycle-sharing during the pandemic. Based on the findings, some neighbourhood-specific policy recommendations are made, which inform decisions regarding the locations and capacity of new stations and the management of existing stations so that equity concerns about the usage of the system are adequately accounted for.