Volume 2, Issue 1

Having poor mental health can be life-threatening, and problems tied to it are prevalent in communities across the United States (US). The city of Austin is one of the ten cities in the US undergoing rapid urban gentrification; however, there is insufficient empirical evidence on the impact of this process on residents’ health. Consequently, this study explored the concept of weathering and life course perspective using data of 331 residents recruited from two regions endemic with gentrification to assess the health impacts of gentrification. We used a triangulation method including univariate, bivariate correlation, and multiple linear regression implemented through the structural equation model to examine the complex pathways to three health outcomes—measured stress, self-rated mental health, and depression symptoms. Bivariate Pearson’s correlation indicated a significant positive association between gentrification score and mental health symptoms and stress. However, the direct association between gentrification and depression disappeared in the causal/path model. In support of the weathering hypothesis, this study found that stress score was directly related to the adulthood depression score. Therefore, this research builds on the accumulating evidence of environmental stress and mental health in the US’s rapidly changing physical and sociocultural environment. Hence, implementing and guaranteeing social equity of resources will improve residents’ health and reduce the cost of health care spending at both the household level and the city government level.

The coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first reported in December, 2019, in Wuhan, China. Even the public health sector experts could not anticipate that the virus would spread rapidly to create the worst worldwide crisis in more than a century. The World Health Organization (WHO) declared COVID-19 a public health emergency on January 30, 2020, but it was not until March 11, 2020 that the WHO declared it a global pandemic. The epidemiology of SARS-CoV-2 is different from the SARS coronavirus outbreak in 2002 and the Middle East Respiratory Syndrome (MERS) in 2012; therefore, neither SARS nor MERS could be used as a suitable model for foreseeing the future of the current pandemic. The influenza pandemic of 1918 could be referred to in order to understand and control the COVID-19 pandemic. Although influenza and the SARS-CoV-2 are from different families of viruses, they are similar in that both silently attacked the world and the societal and political responses to both pandemics have been very much alike. Previously, the 1918 influenza pandemic and unpredictability of the second wave caused distress among people as the first wave of that outbreak (so-called Spanish flu) proved to be relatively mild compared to a much worse second wave, followed by smaller waves. As of April, 2021, the second wave of COVID-19 has occurred around the globe, and future waves may also be expected, if the total population of the world is not vaccinated. This article aims to highlight the key similarities and differences in both pandemics. Similarly, lessons from the previous pan-demics and various possibilities for the future course of COVID-19 are also highlighted.

The connection between urban greenspace and mental health is a robust but unsettled area of research in the public health and urban planning literatures. Inconsistent findings in prior studies are mostly due to differences in greenspace measurements and interrelations with socio-demographic factors. This study examines the relationships of mental health prevalence (MHP) with health prevention, socioeconomic and race-ethnicity factors, and proximity to greenspace at the census-tract level in the City of San Diego, California, using data from the CDC 500 Cities Project and US Census Bureau. We considered three greenspace proximity measures: distances to specified vegetation types, parks, and tree cover. Spear-man’s rank correlation showed that MHP was significantly correlated to distances to greenspace (rho = 0.480), parks (rho = 0.234), and tree cover (rho = 0.342), and greenspace proximity plus crime occurrence explained 37.8% of the variance in MHP in regression analysis. Further analysis revealed that socioeconomic status, race-ethnicity, and health prevention explained more than 93% of the variance in MHP, while greenspace proximity did not enter the regression model with statistical significance. We discovered that certain socioeconomic and race-ethnicity variables, such as proportion of Hispanic population, poverty, and regular checkup, may fully represent the effects of greenspace on MHP in the City of San Diego. Regression analysis for three subsections of the city suggested that different predictors of MHP should be considered in formulating intervention measures. Our results indicate the need to improve mental health conditions through a range of interventions that address the disparities experienced by racial-ethnic minorities and those in lower-socioeconomic classes.

Background: It is estimated that by 2050, almost 70 percent of the global population will be residing in urban areas. In recent years, cities have become central in tackling key urban challenges and have demonstrated greater flexibility in policymaking and innovation than national governments. Cities are currently more inclined to learn from each other via networks, partnerships, and pairings to develop solutions to many global challenges including pandemics such as COVID-19. Aim: To explore the role cities and city networks present in supporting urban resilience to pandemics focusing on conflict-affected settings. Methods: A desk-based literature review of academic and grey sources was conducted followed by thematic analysis. Results: Although most COVID-19 response plans have been developed and implemented by governments, the pandemic has revealed the significant potential for city networks in providing platforms for knowledge sharing and coordination of mitigation plans to address pandemic-specific interventions. We found that in conflict settings, city networks continue to play only a minor role, if any, compared to humanitarian and informal actors. Conclusion: City networks have the potential to contribute to strengthening global collaborative approaches to pandemic responses, but this has not been given sufficient investment and even less so in conflict-affected settings. It is essential for these networks to be integrated within a wider multidisciplinary and multisectoral platform that includes academics, humanitarian and informal actors.