Awareness and knowledge of AIDS among Indian women: evidence from 13 states

Over 30,000 ever-married women in 13 (out of 25) Indian states where HIV is thought to be highly prevalent—Maharashtra, West Bengal, Tamil Nadu, and ten other less populous states—were surveyed about their awareness and knowledge of AIDS. Only one in six women had heard of AIDS. Among those, knowledge about transmission and prevention is poor. Multivariate analyses reveal that rural, poorly educated, and poor women are the least likely to be AIDS-aware and if aware, have the poorest understanding of the syndrome. Despite low levels of awareness and knowledge, we find a strong positive association between AIDS awareness and knowledge and condom use

A Guide to Global Population Projections

Interdisciplinary studies that draw on long-term, global population projections often make limited use of projection results, due at least in part to the historically opaque nature of the projection process. We present a guide to such projections aimed at researchers and educators who would benefit from putting them to greater use. Drawing on new practices and new thinking on uncertainty, methodology, and the likely future courses of fertility and life expectancy, we discuss who makes projections and how, and the key assumptions upon which they are based. We also compare methodology and recent results from prominent institutions and provide a guide to other sources of demographic information, pointers to projection results, and an entry point to key literature in the field.forecasting, population projections, projection methodology, uncertainty

Urban Change in the United States, 1990-2010: A Spatial Assessment of Administrative Reclassification

In today&rsquo;s increasingly urban world, understanding the components of urban population growth is essential. While the demographic components of natural increase and migration have received the overwhelming share of attention to date, this paper addresses the effects of administrative reclassification on urban population growth as derived from census data, which remain largely unstudied. We adopt a spatial approach, using the finest resolution US census data available for three decennial census periods, to estimate the magnitude of reclassification and examine the spatial-temporal variation in reclassification effects. We supplement the census data by using satellite-derived settlement data to further explain reclassification outcomes. We find that while 10% and 7% of the population live in areas that underwent urban/rural reclassification during the 1990&ndash;2000 and 2000&ndash;2010 time periods, respectively (with smaller fractions of corresponding land), reclassification has a substantial effect on metrics derived to characterize the urbanization process&mdash;comprising roughly 44% and 34% of total urban population growth over each period. The estimated magnitude of this effect is sensitive to assumptions regarding the timing of reclassification. The approach also reveals where, how, to what degree, and, in some part, why reclassification is affecting to the process of urbanization on the fine spatial scale, including the impact of underlying demographic processes. This research provides new directions to more effectively study coupled nature&ndash;human systems and their interactions.</div

Estimating population and urban areas at risk of coastal hazards, 1990–2015: how data choices matter

The accurate estimation of population living in the low-elevation coastal zone (LECZ) – and at heightened risk from sea level rise – is critically important for policymakers and risk managers worldwide. This characterization of potential exposure depends on robust representations not only of coastal elevation and spatial population data but also of settlements along the urban–rural continuum. The empirical basis for LECZ estimation has improved considerably in the 13 years since it was first estimated that 10 % of the world's population – and an even greater share of the urban population – lived in the LECZ (McGranahan et al., 2007a). Those estimates were constrained in several ways, not only most notably by a single 10 m LECZ but also by a dichotomous urban–rural proxy and population from a single source. This paper updates those initial estimates with newer, improved inputs and provides a range of estimates, along with sensitivity analyses that reveal the importance of understanding the strengths and weaknesses of the underlying data. We estimate that between 750 million and nearly 1.1 billion persons globally, in 2015, live in the ≤ 10 m LECZ, with the variation depending on the elevation and population data sources used. The variations are considerably greater at more disaggregated levels, when finer elevation bands (e.g., the ≤ 5 m LECZ) or differing delineations between urban, quasi-urban and rural populations are considered. Despite these variations, there is general agreement that the LECZ is disproportionately home to urban dwellers and that the urban population in the LECZ has grown more than urban areas outside the LECZ since 1990. We describe the main results across these new elevation, population and urban-proxy data sources in order to guide future research and improvements to characterizing risk in low-elevation coastal zones (https://doi.org/10.7927/d1x1-d702, CIESIN and CIDR, 2021)

Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States

The collection, processing, and analysis of remote sensing data since the early 1970s has rapidly improved our understanding of change on the Earth’s surface. While satellite-based Earth observation has proven to be of vast scientific value, these data are typically confined to recent decades of observation and often lack important thematic detail. Here, we advance in this arena by constructing new spatially explicit settlement data for the United States that extend back to the early 19th century and are consistently enumerated at fine spatial and temporal granularity (i.e. 250m spatial and 5-year temporal resolution). We create these time series using a large, novel building-stock database to extract and map retrospective, fine-grained spatial distributions of built-up properties in the conterminous United States from 1810 to 2015. From our data extraction, we analyse and publish a series of gridded geospatial datasets that enable novel retrospective historical analysis of the built environment at an unprecedented spatial and temporal resolution. The datasets are part of the Historical Settlement Data Compilation for the United States (https://dataverse.harvard.edu/dataverse/hisdacus, last access: 25 January 2021) and are available at https://doi.org/10.7910/DVN/YSWMDR (Uhl and Leyk, 2020a), https://doi.org/10.7910/DVN/SJ213V (Uhl and Leyk, 2020b), and https://doi.org/10.7910/DVN/J6CYUJ (Uhl and Leyk, 2020c)

The tree cover and temperature disparity in US urbanized areas: Quantifying the association with income across 5,723 communities

Urban tree cover provides benefits to human health and well-being, but previous studies suggest that tree cover is often inequitably distributed. Here, we use National Agriculture Imagery Program digital ortho photographs to survey the tree cover inequality for Census blocks in US large urbanized areas, home to 167 million people across 5,723 municipalities and other Census-designated places. We compared tree cover to summer land surface temperature, as measured using Landsat imagery. In 92% of the urbanized areas surveyed, low-income blocks have less tree cover than high-income blocks. On average, low-income blocks have 15.2% less tree cover and are 1.5˚C hotter than high-income blocks. The greatest difference between low- and high-income blocks was found in urbanized areas in the Northeast of the United States, where low-income blocks in some urbanized areas have 30% less tree cover and are 4.0˚C hotter. Even after controlling for population density and built-up intensity, the positive association between income and tree cover is significant, as is the positive association between proportion non-Hispanic white and tree cover. We estimate, after controlling for population density, that low-income blocks have 62 million fewer trees than high-income blocks, equal to a compensatory value of $56 billion ($1,349/person). An investment in tree planting and natural regeneration of $17.6 billion would be needed to close the tree cover disparity, benefitting 42 million people in low-income blocks

Looking Back, Looking Forward: Progress and Prospect for Spatial Demography

In 2011 a specialist meeting on the “Future Directions in Spatial Demography” was held in Santa Barbara, California (Matthews, Goodchild, & Janelle, 2012).1 This specialist meeting was the capstone to a multi-year National Institutes of Health training grant that had supported workshops in advanced spatial analysis methods increasing used by population scientists.2 Early-career scholars who had participated in the training workshops and senior demographers and geographers drawn from across the United States participated in the specialist meeting.3 The application process to attend the 2011 meeting, required that each of the forty-one attendees submit a statement that reviewed challenges and identifed new directions for spatial demography, including gaps in current knowledge regarding innovations in geospatial data, spatial statistical methods, and the integration of data and models to enhance the science of spatial demography in population and health research. Reading again some of the ruminations of these scholars is an interesting exercise in its own right. The level of optimism back in 2011 was high, and especially regarding anticipated changes in computational capacity, leveraging big data (including volunteered geographic information), developments in data systems (including new data high resolution data products and online resources such as multi-scale map interfaces and dashboards), and in methods such as time–space models, agent-based models, microsimulation, and small-area estimation. There were also several challenges identifed including, but not limited to, study designs, data integration, data validation, confdentiality, non-representative data, historic data, defnitions of place, residential selection and mobility as well as two overarching challenges related to the role and contribution of spatial demographers in interdisciplinary population and health research, and many, many comments on training issues. Substantively the attendees research focused on all forms of interaction between people and place (and the reciprocal relations between the people in social, built, and physical environment contexts) covering the gamut of demographic processes from reproductive health to mortality, though with perhaps an overrepresentation of researchers in areas related to population and environment research, racial and residential segregation, and migration.The R25 Training Grant was funded through the Eunice Kennedy Shriver National Institutes of Child Health and Human Development (NICHD 5R-25 HD057002; Principal Investigator: Stephen A. Matthews).

Looking Back, Looking Forward: Progress and Prospect for Spatial Demography

In 2011 a specialist meeting on the “Future Directions in Spatial Demography” was held in Santa Barbara, California (Matthews, Goodchild, & Janelle, 2012).1 This specialist meeting was the capstone to a multi-year National Institutes of Health training grant that had supported workshops in advanced spatial analysis methods increasing used by population scientists.2 Early-career scholars who had participated in the training workshops and senior demographers and geographers drawn from across the United States participated in the specialist meeting.3 The application process to attend the 2011 meeting, required that each of the forty-one attendees submit a statement that reviewed challenges and identifed new directions for spatial demography, including gaps in current knowledge regarding innovations in geospatial data, spatial statistical methods, and the integration of data and models to enhance the science of spatial demography in population and health research. Reading again some of the ruminations of these scholars is an interesting exercise in its own right. The level of optimism back in 2011 was high, and especially regarding anticipated changes in computational capacity, leveraging big data (including volunteered geographic information), developments in data systems (including new data high resolution data products and online resources such as multi-scale map interfaces and dashboards), and in methods such as time–space models, agent-based models, microsimulation, and small-area estimation. There were also several challenges identifed including, but not limited to, study designs, data integration, data validation, confdentiality, non-representative data, historic data, defnitions of place, residential selection and mobility as well as two overarching challenges related to the role and contribution of spatial demographers in interdisciplinary population and health research, and many, many comments on training issues. Substantively the attendees research focused on all forms of interaction between people and place (and the reciprocal relations between the people in social, built, and physical environment contexts) covering the gamut of demographic processes from reproductive health to mortality, though with perhaps an overrepresentation of researchers in areas related to population and environment research, racial and residential segregation, and migration.The R25 Training Grant was funded through the Eunice Kennedy Shriver National Institutes of Child Health and Human Development (NICHD 5R-25 HD057002; Principal Investigator: Stephen A. Matthews).