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This article introduces bayesian spatial smoothing models for disease mapping—a specific application of small area estimation where the full universe of data is known—to a wider audience of public health professionals using firearm suicide as a motivating example. Besag, York, and Mollié (BYM) Poisson spatial and space–time smoothing models were fitted to firearm suicide counts for the years 2014-2018. County raw death rates in 2018 ranged from 0 to 24.81 deaths per 10 000 people. However, the highest mortality rate was highly unstable, based on only 2 deaths in a population of approximately 800, and 80.5% of contiguous US counties experienced fewer than 10 firearm suicide deaths and were thus suppressed. Spatially smoothed county firearm suicide mortality estimates ranged from 0.06 to 4.05 deaths per 10 000 people and could be reported for all counties. The space–time smoothing model produced similar estimates with narrower credible intervals as it allowed counties to gain precision from adjacent neighbors and their own counts in adjacent years. bayesian spatial smoothing methods are a useful tool for evaluating spatial health disparities in small geographies where small numbers can result in highly variable rate estimates, and new estimation techniques in R software have made fitting these models more accessible to researchers. [ABSTRACT FROM AUTHOR]

Residential segregation is a common aspect of the urban experiences of African-Americans in the United States (US), yet few studies have considered how segregation might influence perinatal health. Here, we develop a conceptual model of relationships between segregation and birth outcomes and test the implications of the model in a sample of 434,376 singleton births to African-American women living in 225 US Metropolitan Statistical Areas (MSAs). Data from the National Center for Health Statistics 2002 birth files were linked to data from the 2000 US Census and two distinct measures of segregation: an index of isolation (the probability that an African-American resident will encounter another African-American resident in any random neighborhood encounter) and an index of clustering (the extent to which African-Americans live in contiguous neighborhoods). Using multilevel regression models, controlling for individual- and MSA-level socioeconomic status and other covariates, we found higher isolation was associated with lower birthweight, higher rates of prematurity and higher rates of fetal growth restriction. In contrast, higher clustering was associated with more optimal outcomes. We propose that isolation reflects factors associated with segregation that are deleterious to health including poor neighborhood quality, persistent discrimination and the intra-group diffusion of harmful health behaviors. Associations with clustering may reflect factors associated with segregation that are health-promoting such as African-American political power empowerment, social support and cohesion. Declines in isolation could represent positive steps toward improving birth outcomes among African-American infants while aspects of racial contiguity appear to be mitigating or indeed beneficial. Segregation is a complex multidimensional construct with both deleterious and protective influences on birth outcomes, depending on the dimensions under consideration. Further research to understand racial/ethnic and economic health disparities could benefit from a focus on the contributory role of neighborhood attributes associated with the dimensions segregation and other social geographies. Keywords: Birthweight; Prematurity; Fetal growth; African-Americans/Blacks; Urban health; USA; Racial residential segregation

Emerging infectious diseases are the focus of increased attention and even alarm in the scholarly and popular literature. The emergence of new diseases and the resurgence of older and previously recognized infectious diseases both in developing and developed country poses challenges for understanding the ecological web of causation, including social, economic, environmental and biological components. This paper is a synthesis of the major characteristics of emerging diseases, in an interdisciplinary context. Political ecology is one framework for analysis that is promising in developing a modified ecology of disease.

The inherent concern of disease ecology with integrating the social and physical aspects of human existence has significantly contributed to the development of medical geography as an acknowledged subfield of geography. The integrative framework utilized by disease ecologists has also enabled medical geographers to consolidate the theoretical approaches of urban, economic, cultural, biogeographic and other subdisciplines.

Most studies of disease distribution, in medical geography and other related disciplines, have been empirical in nature and rooted in the assumptions of logical positivism. However, some of the more newly articulated philosophies of the social sciences, and of social theory, have much to add in the understanding of the processes and mechanisms underlying disease distribution. This paper represents a plea for creative synthesis between logical positivism and realism or structuration, and uses specific examples to suggest how disease distribution, as a surface phenomenon, can be explained using deeper analysis. Key words - medical geography, social theory, epistemology

Abstract The goal of this paper is to both understand and depathologize clinically significant mental distress related to criminalized contact with psychoactive biotic substances by employing a framework known as critical political ecology of health and disease from the subdiscipline of medical geography. The political ecology of disease framework joins disease ecology with the power-calculus of political economy and calls for situating health-related phenomena in their broad social and economic context, demonstrating how large-scale global processes are at work at the local level, and giving due attention to historical analysis in understanding the relevant human-environment relations. Critical approaches to the political ecology of health and disease have the potential to incorporate ever-broadening social, political, economic, and cultural factors to challenge traditional causes, definitions, and sociomedical understandings of disease. Inspired by the patient-centered medical diagnosis critiques in medical geography, this paper will use a critical political ecology of disease approach to challenge certain prevailing sociomedical interpretations of disease, or more specifically, mental disorder, found in the field of substance abuse diagnostics and the related American punitive public policy regimes of substance abuse prevention and control, with regards to the use of biotic substances. It will do this by first critically interrogating the concept of "substances" and grounding them in an ecological context, reviewing the history of both the development of modern substance control laws and modern substance abuse diagnostics, and understanding the biogeographic dimensions of such approaches. It closes with proposing a non-criminalizing public health approach for regulating human close contact with psychoactive substances using the example of cannabis use.