This book discusses the socioeconomic effects of Right-to-Work (RTW) laws on state populations. RTW laws forbid requiring union membership even at union-represented worksites. The core of the 22 long-term RTW states was the Confederacy, cultural descendants of rigidly hierarchical agrarian feudal England. RTW laws buttress hierarchy and power imbalance which unions minimize at the worksite and by encouraging higher educational attainment, social mobility, and individual empowerment through group validation. Contrary to claims of RTW proponents, RTW and non-RTW states do not differ significantly in unemployment rates. RTW states have higher poverty rates, lower median household incomes, and lower educational attainment on average and median than non-RTW states. RTW states on average and median have lower life expectancy, higher obesity prevalence, and higher rates of all-cause mortality, early mortality from chronic conditions, child mortality, and risk behaviors than non-RTW states. The higher mortality rates result in startlingly higher annual numbers of years of life lost before age 75. Stroke mortality at age 55-64 in RTW states results in nearly 10,000 years annually lost in excess of what it would be if the mortality rate were that of non-RTW states. A review of respected publications describes the physiological mechanisms and epidemiology of accelerated aging due to socioeconomic stress. Unions challenge hierarchy directly at work-sites and indirectly through encouraging college education, social mobility, and community and political engagement. How startling that feudal hierarchy lives in 21st century America, shaping vast differences between states in macro- and micro-economics, educational attainment, innovation, life expectancy, obesity prevalence, chronic disease mortality, infant and child mortality, risk behaviors, and other public health markers! Readers will gain insight about the coming clash between feudal individualism and adaptive collectivism, and, in the last chapter, on ways to win the clash by "missionary" work for collectivism.

This book describes how epigenetic context, in a large sense, affects gene expression and the development of an organism, using the asymptotic limit theorems of information theory to construct statistical models useful in data analysis. The approach allows deep understanding of how embedding context affects development. We find that epigenetic information sources act as tunable catalysts, directing ontogeny into characteristic pathways, a perspective having important implications for epigenetic epidemiology. In sum, environmental stressors can induce a broad spectrum of developmental dysfunctions, and the book explores a number of pandemic chronic diseases, using U.S. data at different scales and levels of organization. In particular, we find the legacy of slavery has been grossly compounded by accelerating industrial decline and urban decay. Individual chapters are dedicated to obesity and its sequelae, coronary heart disease, cancer, mental disorders, autoimmune dysfunction, Alzheimer's disease, and other conditions. Developmental disorders are driven by environmental factors channeled by historical trajectory and are unlikely to respond to medical interventions at the population level in the face of persistent individual and community stress. Drugs powerful enough to affect deleterious epigenetic programming will likely have side effects leading to shortened lifespan. Addressing chronic conditions and developmental disorders requires significant large-scale changes in public policy and resource allocation.

This volume compiles five papers modeling the effects of neoliberal economics on the emergence of Ebola and its aftermath. Neoliberalism is currently the world's primary economic philosophy. It centers international relations around globalizing laissez-faire economics for multinational companies, promoting free trade, deregulating economic markets, and shifting state expenditures in favor of private property. The multidisciplinary teams represented here place both Ebola Makona, the Zaire Ebola virus variant that has infected 28,000 in West Africa, and Ebola Reston, which is currently emerging in industrial hog farms in the Philippines and China, within a multi-plank modeling framework. Using a stochastic extinction model that one group spatializes, environmental stochasticity across the ecologies in which Ebola evolves is treated as an ecosystemic prophylaxis. An agroecological logic gate is developed for epidemic control. A Black-Scholes model explicitly links economic margins across agricultural systems to success in biocontrol. This new control theory is further developed around the data-rate and rate-distortion theorems, a turbulence model, and cognitive symmetry breaking. Lastly, a model of pandemic penetrance is used to explore the domino effects of serious outbreaks amplifying through the cascades of disasters that can follow deadly pandemics. All the models presented are contextualized by socioeonomic geographies specific to outbreak locales.Together the models suggest shifts in regional agroeconomics under the neoliberal doctrine, driving deforestation and monoculture production, destroying the ecosystemic "friction" with which local forests typically disrupt Ebola transmission. The resulting collapse in such an ecological function accelerates pathogen spillover and propagation across the remaining host populations. The failure on the part of current control efforts to assimilate such a structural context may render even an efficacious vaccine dysfunctional. The authors propose an alternate science of disease and an adjunct program of interventions useful to researchers and public health officials alike.

This book applies cutting-edge methods from cognitive and evolutionary theories to develop models of conflict between hierarchically-structured cognitive entities under circumstances of imprecision, uncertainty and stress. Characterized as friction and the fog-of-war by the Prussian military theorist Carl von Clausewitz, such conditions impair institutional cognition in real-time conflict and pose a real and continuing threat to organizations, such as the US military. In a linked collection of formal essays and a mathematical appendix, the book explores different aspects of cognitive and evolutionary process as conducted under the direction of doctrine that acts as a kind of genome for retention of what is learned through Lamarckian evolutionary selection pressures: armies and corporate entities learn from conflict, and incorporate that learning into their ongoing procedures. The book proposes models and policy solutions for strategic competence. A central feature of the book is a formal description of the famous OODA loop of the US military theorist John Boyd in terms of the Data Rate Theorem that links control and information theories. That description is expanded to cover more fully the impact of stochastic fog-of-war effects on tactical and operational scales of conflict. Subsequent chapters examine in more detail the role of doctrine, and the particular effect of embedding culture on cognitive and Lamarckian evolutionary processes associated with conflict on tactical, operational, and strategic scales and levels of organization. A scientifically sophisticated exercise in applied mathematics, history, evolutionary theory, and ecosystem theory, this book will be appropriate for researchers and students interested in defense, security, and international relations, as well as non-academic career professionals in government and industry.

An earlier book by Rodrick Wallace entitled Consciousness: A Mathematical Treatment of the Global Neuronal Workspace Model, introduced a formal information-theoretic approach to individual consciousness implementing approaches developed previously by the cognitive scientist Bernard Baars and the philosopher Fred Dretske. This book takes a more formal 'groupoid' perspective and generalizes the results of that book to processes of 'distributed cognition' characteristic of large institutions that can entertain several, sometimes many, simultaneous 'global workspaces' which must compete for resources while communicating and cooperating. Equivalence classes of 'states' produce a network of language-analogs characterizing interacting cognitive modules which entertain multiple workspaces. Equivalence classes of these language-analogs produce dynamical manifolds describing temporal processes carried out by multiple-workspace institutions.

This book is not an intellectual history or popular summary of recent work on consciousness in humans. Bernard Baars (1988), Edelman and Tononi (2000), and many others, have written such, and done it well indeed. This book, rather, brings the powerful analytic machinery of communication theory to bear on the Global Neuronal Workspace (GNW) model of consciousness which Baars introduced, and does so in a formal mathematical manner. It is not the first such attempt. The philospher Fred Dretske (1981), indep- dent of Baars, long ago outlined how information theory might illuminate the understanding of mind. Adapting his approach on the necessary conditions for mental process, we apply a previously-developed information theory analysis of interacting cognitive biological and social modules to Baars' GNW, which has become the principal candidate for a 'standard model' of consciousness. Invoking an obvious canonical homology with statistical physics, the method, when iterated in the spirit of the Hierarchical Linear Model of regression theory, generates a fluctuating dynamic threshold for consciousness which is similar to a tunable phase transition in a physical system. The phenomenon is, however, constrained to a manifold/atlas structure analogous to a retina; an adaptable Rate Distortion manifold, whose 'topology', in a large sense, reflects the hierarchy of embedding constraints acting on consciousness. This view greatly extends what Baars has characterized as 'contexts.

This book explores mental disorders from a uniquely evolutionary perspective. Although there have been many attempts to mathematically model neural processes and, to some extent, their dysfunction, there is very little literature that models mental function within a sociocultural, socioeconomic, and environmental context. Addressing this gap in the extant literature, this book explores essential aspects of mental disorders, recognizing the ubiquitous role played by the exaptation of crosstalk between cognitive modules at many different scales and levels of organization, the missing heritability of complex diseases, and cultural epigenetics. Further, it introduces readers to valuable control theory tools that permit the exploration of the environmental induction of neurodevelopmental disorders, as well as the study of the synergism between culture, psychopathology and sleep disorders, offering a distinctively unique resource.

This book is a collection of essays that explore commonalities and contrasts between strategy in armed conflict and strategy in public health. The first part uses the asymptotic limit theorems of information and control theories to study strategy as an exchange of messages between adversaries, in the context of underlying power relations. The 'messages' to be exchanged are constructed from an 'alphabet' of tactics available to each contender, in a large sense. The second part of the book explores four case histories from this perspective, ranging across agribusiness-generated pandemics, through tuberculosis and COVID-19. The final chapter attempts a strategic synthesis applicable more specifically to public health than to the remarkably - and disturbingly -- close parallel of armed conflict. Taking a unique approach to public health tactics and strategy this volume will be of interest to social epidemiologists, public health economists, public policy scientists, as well as public health researchers and practitioners.

The vector-borne Zika virus joins avian influenza, Ebola, and yellow fever as recent public health crises threatening pandemicity. By a combination of stochastic modeling and economic geography, this book proposes two key causes together explain the explosive spread of the worst of the vector-borne outbreaks. Ecosystems in which such pathogens are largely controlled by environmental stochasticity are being drastically streamlined by both agribusiness-led deforestation and deficits in public health and environmental sanitation. Consequently, a subset of infections that once burned out relatively quickly in local forests are now propagating across susceptible human populations whose vulnerability to infection is often exacerbated in structurally adjusted cities. The resulting outbreaks are characterized by greater global extent, duration, and momentum. As infectious diseases in an age of nation states and global health programs cannot, as much of the present modeling literature presumes, be described by interacting populations of host, vector, and pathogen alone, a series of control theory models is also introduced here. These models, useful to researchers and health officials alike, explicitly address interactions between government ministries and the pathogens they aim to control.

Steep socioeconomic hierarchy in post-industrial Western society threatens public health because of the physiological consequences of material and psychosocial insecurities and deprivations. Following on from their previous books, the authors continue their exploration of the geography of early mortality from age-related chronic conditions, of risk behaviors and their health outcomes, and of infant and child mortality, all due to rigid hierarchy. They divide the 50 states into those that gave their electoral college votes to Trump and those that gave theirs to Clinton in the 2016 presidential election and compare the two sets for socioeconomic and public health profiles. They deliberately apply only simple standard statistical methods in the public health analyses: t-test, Mann-Whitney test, bivariate regression, and backward stepwise multivariate regression. The book assumes familiarity with basic statistics. The authors argue that the unequal power relations that result in eroding public health in the nation and, in particular, in the Trump-voting states, largely cascade from the collapse of American industry, and they analyze the Cold War roots of that collapse. In two largely independent chapters on economics, they explore both the suppression of countervailing forces, such as organized labor, and the diversion of technical resources to the military as essential foundations to the population-level suffering that expressed itself in the 2016 presidential election. This interdisciplinary book has several primary audiences: creators of public policies, such as legislators and governmental staff, public health professionals and social epidemiologists, economists, labor union professionals, civil rights advocates, political scientists, historians, and students of these disciplines from public health through the social sciences.

The book is a unique exploration of a spectrum of unexpected analogs to psychopathologies likely to afflict real-time critical systems, written by a specialist in the epidemiology of mental disorders. The purpose of this book is to develop a set of information-theoretic statistical tools for analyzing the instabilities of real-time cognitive systems at those varying scales and levels of organization, with special focus on high level machine function.The book should be of particular interest to both industry and academic scientists, and government regulators, concerned with driverless cars on intelligent roads. Many of the same concerns also afflict high-end automated weapons systems. The book should appeal to students, researchers, and industrial and governmental administrators facing the design, operation, and maintenance of real time critical systems ranging across manufacturing facilities, transportation, finance, and military operations.

The monograph applies sophisticated topological symmetry tools to biological applications of information theory, along with a Black-Scholes model invocation of the Data Rate Theorem which links information and control theories. The focus is on statistical mechanics and other models that explore pathological phase transitions - driven by changes in available rates of mitochondrial free energy - in physiological functions, a cutting-edge topic in the study of chronic disease. One of the key focuses is Alzheimer's disease - a relatively simple canonical example.

The creation of economic institutions that can function well under substantial uncertainties -- Black Swans -- is analogous to the dilemmas confronting our hunter-gatherer forefathers in the face of large-scale ecological unpredictability. The ultimate solution was not the development of a super hunter-gatherer technology that could ride out repeated catastrophe, but rather the invention, in neolithic times, of culturally-adapted 'farmed' ecosystems constructed to maximize food yield and minimize risks of famine. Recent advances in evolutionary and ecosystem theory applied to economic structure and process may permit construction of both new economic theory and new tools for data analysis that can help in the design of more robust economic institutions. This may result in less frequent and less disruptive transitions, and enable the design of culturally-specific systems less affected by those that do occur. This unique and innovative book applies cutting-edge methods from cognitive science and evolutionary theory to the problem of the necessary stabilization of economic processes. At the core of this book is the establishment of a statistics-like toolbox for the study of empirical data that is consistent with generalized evolutionary approaches. This toolbox enables the construction of both new economic theories and methods of data analysis that can help in the design of more robust economic institutions. This in turn will result in less frequent and less disruptive Black Swans, and enable as well the design of culturally-specific systems less affected by those that do occur.

This book, based on published studies, takes a unique perspective on the 30-year collapse of pharmaceutical industry productivity in the search for small molecule "magic bullet" interventions. The relentless escalation of inflation-adjusted cost per approved medicine in the United States - from $200 million in 1950 to $1.2 billion in 2010 - has driven industry giants to, at best, slavish imitation in drug design, and at worst, abandonment of research and embracing of widespread fraud in consumer marketing.The book adapts formalism across a number of disciplines to the strategy for design of mutilevel interventions, focusing first on molecular, cellular, and larger scale examples, and then extending the argument to the simplifications provided by the dominant role of social and cultural structures and processes in individual and population patterns of health and illness.In place of "magic bullets", we must now apply "magic strategies" that act across both the scale and level of organization. This book provides an introductory roadmap to the new tools that will be needed for the design of such strategies.

The creation of economic institutions that can function well under substantial uncertainties -- Black Swans -- is analogous to the dilemmas confronting our hunter-gatherer forefathers in the face of large-scale ecological unpredictability. The ultimate solution was not the development of a super hunter-gatherer technology that could ride out repeated catastrophe, but rather the invention, in neolithic times, of culturally-adapted 'farmed' ecosystems constructed to maximize food yield and minimize risks of famine. Recent advances in evolutionary and ecosystem theory applied to economic structure and process may permit construction of both new economic theory and new tools for data analysis that can help in the design of more robust economic institutions. This may result in less frequent and less disruptive transitions, and enable the design of culturally-specific systems less affected by those that do occur. This unique and innovative book applies cutting-edge methods from cognitive science and evolutionary theory to the problem of the necessary stabilization of economic processes. At the core of this book is the establishment of a statistics-like toolbox for the study of empirical data that is consistent with generalized evolutionary approaches. This toolbox enables the construction of both new economic theories and methods of data analysis that can help in the design of more robust economic institutions. This in turn will result in less frequent and less disruptive Black Swans, and enable as well the design of culturally-specific systems less affected by those that do occur.

Steep socioeconomic hierarchy in post-industrial Western society threatens public health because of the physiological consequences of material and psychosocial insecurities and deprivations. Following on from their previous books, the authors continue their exploration of the geography of early mortality from age-related chronic conditions, of risk behaviors and their health outcomes, and of infant and child mortality, all due to rigid hierarchy. They divide the 50 states into those that gave their electoral college votes to Trump and those that gave theirs to Clinton in the 2016 presidential election and compare the two sets for socioeconomic and public health profiles. They deliberately apply only simple standard statistical methods in the public health analyses: t-test, Mann-Whitney test, bivariate regression, and backward stepwise multivariate regression. The book assumes familiarity with basic statistics. The authors argue that the unequal power relations that result in eroding public health in the nation and, in particular, in the Trump-voting states, largely cascade from the collapse of American industry, and they analyze the Cold War roots of that collapse. In two largely independent chapters on economics, they explore both the suppression of countervailing forces, such as organized labor, and the diversion of technical resources to the military as essential foundations to the population-level suffering that expressed itself in the 2016 presidential election. This interdisciplinary book has several primary audiences: creators of public policies, such as legislators and governmental staff, public health professionals and social epidemiologists, economists, labor union professionals, civil rights advocates, political scientists, historians, and students of these disciplines from public health through the social sciences. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

From the ‘punctuated equilibrium' of Eldrege and Gould, through Lewontin's ‘triple helix' and the various visions and revisions of the Extended Evolutionary Synthesis (EES) of Laland and others, both data and theory have demanded an opening-up of the 1950's Evolutionary Synthesis that so firmly wedded evolutionary theory to the mathematics of gene frequency analysis. It can, however, be argued that a single deep and comprehensive mathematical theory may simply not be possible for the almost infinite varieties of evolutionary process active at and across the full range of scales of biological, social, institutional, and cultural phenomena. Indeed, the case history of 'meme theory' should have raised a red flag that narrow gene-centered models of evolutionary process may indeed have serious limitations. What is attempted here is less grand, but still broader than a gene-centered analysis. Following the instruction of Maturana and Varela that all living systems are cognitive, in a certain sense, and that living as a process is a process of cognition, the asymptotic limit theorems of information and control theories that bound all cognition provide a basis for constructing an only modestly deep but wider-ranging series of probability models that might be converted into useful statistical tools for the analysis of observational and experimental data related to evolutionary process. The line of argument in this series of interrelated essays proves to be surprisingly direct.

This book explores mental disorders from a uniquely evolutionary perspective. Although there have been many attempts to mathematically model neural processes and, to some extent, their dysfunction, there is very little literature that models mental function within a sociocultural, socioeconomic, and environmental context. Addressing this gap in the extant literature, this book explores essential aspects of mental disorders, recognizing the ubiquitous role played by the exaptation of crosstalk between cognitive modules at many different scales and levels of organization, the missing heritability of complex diseases, and cultural epigenetics. Further, it introduces readers to valuable control theory tools that permit the exploration of the environmental induction of neurodevelopmental disorders, as well as the study of the synergism between culture, psychopathology and sleep disorders, offering a distinctively unique resource.

Farming Human Pathogens: Ecological Resilience and Evolutionary Process introduces a cutting-edge mathematical formalism based on the asymptotic limit theorems of information theory to describe how punctuated shifts in mesoscale ecosystems can entrain patterns of gene expression and organismal evolution. The authors apply the new formalism toward characterizing a number of infectious diseases that have evolved in response to the world as humans have made it. Many of the human pathogens that are emerging out from underneath epidemiological control are 'farmed' in the metaphorical sense, as the evolution of drug-resistant HIV makes clear, but also quite literally, as demonstrated by avian influenza's emergence from poultry farms in southern China. The most successful pathogens appear able to integrate selection pressures humans have imposed upon them from a variety of socioecological scales. The book also presents a related treatment of Eigen's Paradox and the RNA 'error catastrophe' that bedevils models of the origins of viruses and of biological life itself.

This book is not an intellectual history or popular summary of recent work on consciousness in humans. Bernard Baars (1988), Edelman and Tononi (2000), and many others, have written such, and done it well indeed. This book, rather, brings the powerful analytic machinery of communication theory to bear on the Global Neuronal Workspace (GNW) model of consciousness which Baars introduced, and does so in a formal mathematical manner. It is not the first such attempt. The philospher Fred Dretske (1981), indep- dent of Baars, long ago outlined how information theory might illuminate the understanding of mind. Adapting his approach on the necessary conditions for mental process, we apply a previously-developed information theory analysis of interacting cognitive biological and social modules to Baars' GNW, which has become the principal candidate for a 'standard model' of consciousness. Invoking an obvious canonical homology with statistical physics, the method, when iterated in the spirit of the Hierarchical Linear Model of regression theory, generates a fluctuating dynamic threshold for consciousness which is similar to a tunable phase transition in a physical system. The phenomenon is, however, constrained to a manifold/atlas structure analogous to a retina; an adaptable Rate Distortion manifold, whose 'topology', in a large sense, reflects the hierarchy of embedding constraints acting on consciousness. This view greatly extends what Baars has characterized as 'contexts.

Gene Expression and its Discontents examines a class of probability models describing how epigenetic context affects gene expression and organismal development, using the asymptotic limit theorems of information theory in a highly formal manner. Taking classic results on spontaneous symmetry breaking abducted from statistical physics in groupoid, rather than group, circumstances, the work suggests that epigenetic information sources act as analogs to a tunable catalyst, directing development into different characteristic pathways according to the structure of external signals. The results have significant implications for epigenetic epidemiology, in particular for understanding how environmental stressors, in a large sense, can induce a broad spectrum of developmental disorders in humans. The authors then apply the perspective to a number of chronic diseases broadly associated with obesity, using data at different scales of observation.

An earlier book by Rodrick Wallace entitled Consciousness: A Mathematical Treatment of the Global Neuronal Workspace Model, introduced a formal information-theoretic approach to individual consciousness implementing approaches developed previously by the cognitive scientist Bernard Baars and the philosopher Fred Dretske.

This book takes a more formal 'groupoid' perspective and generalizes the results of that book to processes of 'distributed cognition' characteristic of large institutions that can entertain several, sometimes many, simultaneous 'global workspaces' which must compete for resources while communicating and cooperating.

Equivalence classes of 'states' produce a network of language-analogs characterizing interacting cognitive modules which entertain multiple workspaces. Equivalence classes of these language-analogs produce dynamical manifolds describing temporal processes carried out by multiple-workspace institutions.

Farming Human Pathogens: Ecological Resilience and Evolutionary Process introduces a cutting-edge mathematical formalism based on the asymptotic limit theorems of information theory to describe how punctuated shifts in mesoscale ecosystems can entrain patterns of gene expression and organismal evolution. The authors apply the new formalism toward characterizing a number of infectious diseases that have evolved in response to the world as humans have made it. Many of the human pathogens that are emerging out from underneath epidemiological control are 'farmed' in the metaphorical sense, as the evolution of drug-resistant HIV makes clear, but also quite literally, as demonstrated by avian influenza's emergence from poultry farms in southern China. The most successful pathogens appear able to integrate selection pressures humans have imposed upon them from a variety of socioecological scales. The book also presents a related treatment of Eigen's Paradox and the RNA 'error catastrophe' that bedevils models of the origins of viruses and of biological life itself.

As a follow-up to COVID-19 in New York City: an Ecology of Race and Class Oppression, which showed that decades of discriminatory public policies shaped the Bronx into the epicenter of the first wave of COVID-19, this book examines the build up to the crest and subsequent ebbing of the second wave of COVID-19 across the 62 counties of New York State (NYS) and 152 ZIP Code areas of the four central boroughs of New York City (NYC). Like its predecessor, the sequel examines the vulnerabilities that give rise to spikes in infection rates that form epicenters. Unlike the first wave, NYC was not the epicenter of the second wave; high-incident counties just outside NYS formed an extended initial epicenter and exported COVID-19 to neighboring counties of NYS. Rural NYS counties differed significantly from urban ones socioeconomically and in infection rates during the cresting period. Before the crest, no socioeconomic factor was associated with county infection rates; rather, the major associating factor was political and cultural: percent of the 2020 vote garnered by Trump. Rural counties voted heavily for Trump. This association disappeared post-crest by mid-January 2021. In NYC, the Bronx again behaved like a single high-incidence entity, unlike the other three boroughs that had patches of high and low infection incidence. Among the topics covered: The Second COVID Wave Washes Over New York State The Second Wave Storm-Surges Across New York City Discussion of County Data from the Second Wave of COVID-19 Parsing Meaning From the 152 ZIP Code Data The book closes with a prescription for pandemic response planning based on empowered communities and workers interacting with health departments as equals. The Recurrence of COVID-19 in New York State and New York City is a valuable resource for social epidemiologists, public health researchers of health disparities, those in public service tasked with addressing these problems, and infectious disease scientists who focus on spread in human populations of new zoonotic diseases. The brief also will find readership among students in these fields, civil rights scholars, science writers, medical anthropologists and sociologists, medical and public health historians, public health economists, and public policy scientists.

This book is a collection of essays that explore commonalities and contrasts between strategy in armed conflict and strategy in public health. The first part uses the asymptotic limit theorems of information and control theories to study strategy as an exchange of messages between adversaries, in the context of underlying power relations. The ‘messages’ to be exchanged are constructed from an ‘alphabet’ of tactics available to each contender, in a large sense. The second part of the book explores four case histories from this perspective, ranging across agribusiness-generated pandemics, through tuberculosis and COVID-19. The final chapter attempts a strategic synthesis applicable more specifically to public health than to the remarkably – and disturbingly -- close parallel of armed conflict. Taking a unique approach to public health tactics and strategy this volume will be of interest to social epidemiologists, public health economists, public policy scientists, as well as public health researchers and practitioners.