Many communities and territories in developing countries experience significant gaps in access to and use of information and communication technology (ICT), which is viewed as a major impediment to socioeconomic and health-related vulnerabilities. Geographic considerations, on the other hand, as well as variations in motivation for ICT usage and technology adoption within and across nations, as well as between cultures, have exacerbated the digital divide. This paper investigates disparities in access to and utilization of ICT in 31 Iranian provinces from 2011 to 2020. The research discovers evidence that family income and the number of R&D centers affected the formation of the digital divide, albeit the degree of the split has fluctuated through time and space. This study discovered that digital inequality is associated with social exclusion throughout Iranian regions, and it went on to try to better understand the underlying issues and potential solutions. In this regard, some policy avenues are suggested for government action, particularly for marginalized socioeconomic groups, such as the provision of infrastructure, training and skill augmentation, and the easing of digital services supplied by the government or private sector.

Although numerous studies have been conducted to discover the spatial patterns of road crashes, relatively few have focused on the patterns of road crashes suffered by socially disadvantaged groups, while simultaneously accounting for urban environmental features. This study used advanced econometric (negative binomial regression) and spatial (geographically weighted Poisson regression) approaches to capture latent geographical diversity in crash patterns. The police-reported crash data for the over-65 population in metropolitan Adelaide, Australia, were investigated for two periods: before and after COVID-19. Using both spatial and nonspatial models, the effects of land use mix, population density, road network design, distance to the central business district, and accessibility of public transit on crash frequency, and location at the neighborhood level were investigated. The findings revealed that, in addition to sociodemographic factors, the aforementioned components had nonlinear effects in varied geographical contexts. Although the number of crashes fell by 20% during the periods studied, the fundamental reasons for such incidents did not change. The results of the study could assist academics and policy makers in Australia to better understand the multidimensional implications of the built environment on the road safety of the elderly—a vulnerable group in society who were disproportionately affected by the global pandemic. The hybrid technique presented in this research has the potential to be useful in other scenarios experiencing varying crash patterns.

Today, the inequality of distribution of built environments leads to the formation of advantaged and disadvantaged neighborhoods. Advantage neighborhoods have good accessibility (Distance to) and availability (Number of) service centers. If the neighborhoods have some service centers that don’t provide healthy lifestyles, especially in increasing obesity, they can decline community health in these areas. So, this research tries to have a spatial view of obesity as a dependent variable. Independent variables are the number of and distance to food, smoking, and physical activity centers that are based on theoretical concepts. We analyzed them with dependent variables on SEIFA Clusters at SA2 level. This research has used spatial analysis methods such as BILISA Cluster on Local Moran I for clustering, GWR for spatial correlation which is a base of the analysis method. The results in the Great Melbourne Area (GMA) show that the level of accessibility is more important than availability and some SA2s in the low levels of SEIFA haven’t good access to a healthy built environment and which makes them more obese.

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