Correction to: Housing Affordability, Housing Tenure Status and Household Density: Are Housing Characteristics Associated with Union Dissolution?

A correction to this paper has been published: https://doi.org/10.1007/s10680-021-09587-z

Get Up and Go: Evaluating Station Area Factors affecting A.M. Commuter Rail Boardings in the Greater Toronto and Hamilton Area

This research evaluates built form and demographic factors of GO Transit commuter rail station areas that contribute to ridership and utilization of existing services in the A.M. peak period using biannual GO Rail ridership information from the Spring of 2010 to Spring of 2015. In order to identify predictors of ridership growth, four regression models were estimated that evaluated factors affecting cross-sectional ridership, cross-sectional utilization of capacity, station-level utilization at each time period, and station-level year-over-year utilization growth. Results indicate that the strongest predictors of ridership, utilization, and growth were station parking capacity and household density of the surrounding area. This suggests potential for tensions in developing GO-supportive station-area land use policy strategies focused on either expanding station-area parking capacity or station-area residential intensification. The station level utilization model produced a priority list of future service increases on GO Rail corridors based on existing capacity and ridership.

Get Up and Go: Evaluating Station Area Factors affecting A.M. Commuter Rail Boardings in the Greater Toronto and Hamilton Area

This research evaluates built form and demographic factors of GO Transit commuter rail station areas that contribute to ridership and utilization of existing services in the A.M. peak period using biannual GO Rail ridership information from the Spring of 2010 to Spring of 2015. In order to identify predictors of ridership growth, four regression models were estimated that evaluated factors affecting cross-sectional ridership, cross-sectional utilization of capacity, station-level utilization at each time period, and station-level year-over-year utilization growth. Results indicate that the strongest predictors of ridership, utilization, and growth were station parking capacity and household density of the surrounding area. This suggests potential for tensions in developing GO-supportive station-area land use policy strategies focused on either expanding station-area parking capacity or station-area residential intensification. The station level utilization model produced a priority list of future service increases on GO Rail corridors based on existing capacity and ridership.

Beyond the 405 and the 5: Geographic variations and factors associated with SARS-CoV-2 positivity rates in Los Angeles County

Objectives To highlight geographic differences and the socio-structural determinants of SARS-CoV-2 test positivity within Los Angeles County (LAC). Methods A geographic information system was used to integrate, map, and analyze SARS-CoV-2 testing data reported by LAC DPH, and data from the American Community Survey. Structural determinants included race/ethnicity, poverty, insurance status, education, population and household density. We examined which factors were associated with positivity rates, using a 5% test positivity threshold, with spatial analysis and spatial regression. Results Between 1 March and 30 June 2020 there were 843,440 SARS-CoV-2 tests and 86,383 diagnoses reported, for an overall positivity rate of 10.2% within the study area. Communities with high proportions of Latino/a residents, those living below the federal poverty line and with high household densities had higher crude positivity rates. Age- adjusted diagnosis rates were significantly associated with the proportion of Latino/as, individuals living below the poverty line, population, and household density. Conclusions There are significant local variations in test positivity within LAC and several socio-structural determinants contribute to ongoing disparities. Public health interventions, beyond shelter in place, are needed to address and target such disparities.

Implementing contact tracing for tuberculosis in Kyrgyz Republic and risk factors for positivity using QuantiFERON-TB Gold plus

Background Effective active case finding (ACF) activities are essential for early identification of new cases of active tuberculosis (TB) and latent TB infection (LTBI). Accurate diagnostics as well as the ability to identify contacts at high risk of infection are essential for ACF, and have not been systematically reported from Central Asia. The objective was to implement a pilot ACF program to determine the prevalence and risk factors for LTBI and active TB among contacts of individuals with TB in Kyrgyz Republic using Quantiferon-TB Gold plus (QuantiFERON). Methods An enhanced ACF project in the Kyrgyz Republic was implemented in which close and household (home) contacts of TB patients from the Issyk-Kul Oblast TB Center were visited at home. QuantiFERON and the tuberculin skin test (TST) alongside clinical and bacteriological examination were used to identify LTBI and active TB cases among contacts. The association for QuantiFERON positivity and risk factors were analysed and compared to TST results. Results Implementation of ACF with QuantiFERON involved close collaboration with the national sanitary and epidemiological services (SES) and laboratories in the Kyrgyz Republic. From 67 index cases, 296 contacts were enrolled of whom 253 had QuantiFERON or TST results; of those 103 contacts had LTBI (positive TST or IGRA), and four (1.4%) active TB cases were detected. Index case smear microscopy (OR 1.76) and high household density (OR 1.97) were significant risk factors for QuantiFERON positivity for all contacts. When stratified by age, association with smear positivity disappeared for children below 15 years. TST was not associated with any risk factor. Conclusions This is the first time that ACF activities have been reported for Central Asia, and provide insight for implementation of effective ACF in the region. These ACF activities using QuantiFERON led to increase in the detection of LTBI and active cases, prior to patients seeking treatment. Household density should be taken into consideration as an important risk factor for the stratification of future ACF activities.

Leukocyte mitochondrial DNA copy number and built environment in Mexican Americans: a cross-sectional study

Mitochondrial DNA (mtDNA) copy number in leukocytes has been regarded as a biomarker for various environmental exposures and chronic diseases. Our previous study showed that certain demographic factors (e.g. age, gender, BMI, etc.) significantly affect levels of leukocyte mtDNA copy number in Mexican Americans. However, the effect of the built environment on leukocyte mtDNA copy number has not been studied previously. In this cross-sectional study, we examined the association between multiple components of the built environment with leukocyte mtDNA copy number among 5,502 Mexican American adults enrolled in Mano-A-Mano, the Mexican American Cohort Study (MACS). Based on the median levels of mtDNA copy number, the study population was stratified into low mtDNA copy number group (< median) and high mtDNA copy number group (≥ median). Among all built environment exposure variables, household density and road/intersection ratio were found to be statistically significant between groups with low and high mtDNA copy number (P < 0.001 and 0.002, respectively). In the multivariate logistic regression analysis, individuals living in areas with elevated levels of household density had 1.24-fold increased odds of having high levels of mtDNA copy number [Odds ratio (OR) = 1.24, 95% confidence interval (CIs) 1.08, 1.36]. Similarly, those living in areas with elevated levels of road/intersection ratio had 1.12-fold increased odds of having high levels of mtDNA copy number (OR = 1.12, 95% CI 1.01, 1.27). In further analysis, when both variables were analyzed together in a multivariate logistic regression model, the significant associations remained. In summary, our results suggest that selected built environment variables (e.g. population density and road/intersection ratio) may influence levels of mtDNA copy number in leukocytes in Mexican Americans.

The Effect of Urban Land-Use Regulations on Density

Urban land is crucial to economic productivity and growth in cities, given substantial land intensive economic activity takes place. While land use regulations are needed for inclusive growth and to protect the urban poor, they create distortions in the land market, and become counter-productive. Indian cities are characterized by strong urban land use controls, given its socialistic and planned economy for a long time. Draconian land use regulations that continue to exist in India’s cities are rent control and highly restrictive floor area ratios (FARs). In this chapter, I focus on FARs and rent control to a limited extent. I examine the impact FARs have on population and household density, in the context of the standard urban framework, taking the case of Bengaluru, where ward-level data have been recently put together on FARs. I find in Bengaluru that FARs impact (both population and household) density negatively, consistent with what other studies have found. The Karnataka rent control Act essentially renders the Act ineffective in Bengaluru. In the context of Mumbai, I use anecdotal evidence to examine FAR, where the effects are compounded by the existence of other distortions such as rent control. Based on the findings, the chapter summarizes the policy implications, its caveats, concludes and presents directions for future research.