Reevaluating the Spatial Scale of Residential Segregation: Racial Change Within and Between Neighborhoods.

This study evaluates the extent to which metropolitan racial segregation occurs between neighborhoods-from tract to tract-and within neighborhoods-from block to block-and is framed theoretically by Putnam's (2007) "hunkering down" hypothesis. Analyses are based on complete-count block, tract, and metropolitan data from the last four U.S. decennial censuses. We document recent patterns of block-to-block segregation between Whites and racial and ethnic minorities (Blacks, Asians, and Hispanics) and between different minority pairs. For example, roughly 40% of all metro Black-White segregation is due to segregation from block to block within neighborhoods. Among Asians, the between-neighborhood component of metropolitan segregation has increased over time but was largely compensated by declines in the within-neighborhood (or block) component. Metropolitan fixed-effects models show that trends and racial and ethnic differences in segregation-overall and within and between neighborhoods-are broadly observed across metro areas but are most evident in the largest, oldest, and most highly segregated metro areas. The results are robust to alternative estimates that adjust for differential privacy, metropolitan reclassification, and neighborhood boundary changes. Analyses of neighborhood change in Atlanta, Georgia, further reinforce the generality of our multiscale approach.

Longitudinal disparities in social determinants of health and COVID-19 incidence and mortality in the United States from the three largest waves of the pandemic.

The United States experienced at least five COVID-19 waves linked with different mutated SARS-CoV-2 variants including Alpha, Delta and Omicron. In addition to the variants, the intensity, geographical distribution, and risk factors related to those waves also vary within socio-demographic characteristics and timeframes. In this project, we have examined the spatial and temporal pattern of COVID-19 in the USA and its associations with Social Determinants of Health (SDoH) by utilizing the County Health Rankings & Roadmaps (CHRR) dataset. Our epidemiologic investigation at the county level showed that the burden of COVID-19 cases and deaths is higher in counties with high percentages of smoking, number of preventable hospital stays, primary care physician rate, the average daily density of PM2.5 and percentages of high proportions of Hispanic residents. In addition, the analysis also demonstrated that COVID-19 incidence and mortality had distinct characteristics in their association with SDoH variables. For example, the percentages of the population 65 and older had negative associations with incidence while a significant positive association with mortality. In addition to the elderly population, median household income, unemployment, and number of drug overdose deaths showed a mixed association with COVID-19 incidence and mortality. Our findings validate several influential factors found in the existing social epidemiology literature and highlight temporal associations between SDoH variables and COVID-19 incidence and mortality not yet frequently studied.

Does land use change, waterlogging, and salinity impact on sustainability of agriculture and food security? Evidence from southwestern coastal region of Bangladesh.

The United Nation's sustainable development goal is to achieve zero hunger by 2030 and achieve food security throughout the world. In this context, we analyze the anthropogenic factors such as land use and land cover change, waterlogging, and soil salinity which combinedly affecting the agricultural sustainability and threatening the food security in the southwestern region of Bangladesh. Landsat satellite images from 1991 to 2021 were used to detect the changes and identify how anthropogenic activities have altered the land cover and land use and impede the sustainability of agriculture. Terra MODIS vegetation indices from 2000 to 2020 were used to detect waterlogging. Soil salinity was measured from the soil samples and vegetation soil salinity index (VSSI) from Landsat images. Findings of the study revealed that agricultural lands have decreased because of an increase in shrimp farming. Waterlogging and soil salinity are increasing due to increased shrimp farms also for poor drainage infrastructure and human modification. The area of agricultural land in 2011 was 19,657.12 acres,12,750.14 acres, and 38,774.70 acres in Keshabpur, Abhaynagar, and Manirampur, which changed to 12,668.70 acres (-36%), 7151.27 acres (-44%), and 32,809.30 acres (-16%) in 2021. Our hotspot analysis reveals that very high vulnerability to waterlogging due to floods was highest in Manirampur (15,464.09 acres). Finally, we proposed a new framework called IDCEM designed for monitoring land-use change, salinity, and waterlogging in the interior coast, which will indirectly help to promote food security and help in achieving sustainable development goal.

Does anthropogenic upstream water withdrawal impact on downstream land use and livelihood changes of Teesta transboundary river basin in Bangladesh?

This article evaluates the impact of upstream water withdrawal on downstream land use and livelihood changes in the Teesta River basin, using a combination of geospatial and social data. Results show that water bodies gradually decreased, indicating a low volume of water discharge from upstream of the Teesta River basin due to the construction of several barrages. During the study period, a significant change in the area of water bodies was observed between 2012 and 2016, from 881 to 1123 Ha, respectively. The cropland area increased because farmers changed their cropping practice due to water scarcity and floods. Trend analyses of riverbank erosion and accretion patterns suggest an increase in accretion rates compared to the rate of riverbank erosion. A household survey was conducted using a self-administered questionnaire where 450 respondents have participated (farmers: 200 and fishermen: 250). Survey results show that most of the farmers (65.5%) and fishermen (76.8%) think that the construction of upstream barrages caused harm to them. The majority of farmers and fishermen feel water scarcity, mainly in the dry season. We found that a large number of participants in the study area are willing to change their occupations. Furthermore, participants observed that many local people are migrating or willing to migrate to other places nowadays. Our study also found that farmers who face water scarcity in their area are more likely to change their location than their counterparts, while those who face problems in their cultivation are less likely to move. On the other hand, upstream barrages, fishing effects, and getting support in crisis significantly predict fishermen's occupation changes. We believe our results provide essential information on the significance of transboundary water-sharing treaties, sustainable water resource management, and planning.

Internal migration effectiveness and income effectiveness in the most populous cities in the United States.

In this study, migration data compiled by the Internal Revenue Serve (IRS) and the US Census Bureau for 2006-07 were used to analyse internal migration patterns using migration and income effectiveness for the counties containing the 25 most populous cities in the United States. The results indicated that both large metropolitan and rural counties have lost population and income due to migration. Small metropolitan and non-metropolitan counties closer to cities gained population and income. Counties in South Florida attracted a large number of higher-income migrants from the largest cities in the US. In the last 13 years, New York, Los Angeles and Chicago, the three most populous cities in the US, had negative migration effectiveness. Suburban areas and second-tier cities continued to attract people from large metropolitan areas.