Assessing the promise of biofortification: A case study of high provitamin A maize in Zambia

AbstractIntroductionBiofortification is the breeding of new varieties of staple foods for increased micronutrient content. It is seen primarily as a complementary, rural-targeted strategy for better reaching remote populations. This paper presents an ex ante analysis of HarvestPlus’ provitamin A maize (PVAM) in Zambia and highlights an empirical approach based on the Zambian 2005/06 Living Conditions Monitoring Survey (LCMS). Because more than 115 countries regularly conduct a Household Consumption and Expenditure Survey (HCES), the approach developed in this LCMS-based study can be applied in many other countries to analyze varietal adoption and conduct ex ante studies.MethodsData from the LCMS and health statistics were used to characterize baseline indicators of vitamin A intake and Disability Adjusted Life Years (DALYs) lost. The introduction and scaling up of PVAM was modeled based on program plans, expert opinion and data on key adoption parameters. An adoption function was specified and expressed in terms of the percent of farmers expected to adopt PVAM over the next 30years. A logistic regression adoption function was estimated and used to identify the specific LCMS households adopting, producing and consuming PVAM each year. Information from the IFPRI International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) of yearly maize production and demand were used to produce annual estimates of PVAM planted, harvested and consumed. Taking into account an LCMS-empirically-informed, specified market structure, individuals’ additional vitamin A intake was calculated. The number of DALYs saved were estimated using the change in vitamin A intake. Combining these estimates with cost data, the cost-effectiveness of PVAM was calculated.ResultsAssuming an adoption ceiling of 20% over 30years, implementation of PVAM will result in average additional intake of 12% of the Estimated Average Requirement (EAR), a 3 percentage point reduction in the prevalence of inadequate intake, and savings of 23% of total DALYs. Impacts are concentrated among farming households that have adopted PVAM and consume it from their own production. Their consumption will result in an average additional vitamin A intake of 172μg/day, more than 3 times the additional 54μg/day among the entire population. Among this group, the reduction in the prevalence of inadequate intake will be more than 5 times the national average (17.5 percentage points). Valuing a DALY at $1000, PVAM’s cumulative value of DALYs saved comes to exceed its cumulative total costs starting in 2019. Over 30years the cost-effectiveness of PVAM in Zambia was estimated to be$24 per DALY saved, making it very cost-effective.ConclusionThe methodologies employed in this study provide insights and inputs that can be used to target farmers who are most likely to adopt, to measure their vitamin A intake and to craft messages to promote adoption. PVAM is a long term investment that shows great promise in becoming a highly cost-effective addition to the public health arsenal for combatting micronutrient deficiencies if the 20% adoption rate can be achieved and maintained. Doing so will require effective marketing strategies, including efforts to couple this nutrition-sensitive intervention with nutrition-specific activities, such as targeted nutrition messaging and education, in order to increase the likelihood that adopting farmers will prioritize production for home consumption

Food fortification - a feasible, cost-effective option in the fight against vitamin A deficiency in South Africa

No Abstrac

[Introduction to] The Medical Offset Effect and Public Health Policy: Mental Health Industry in Transition

Does the timely treatment of mental illness result in a drop in the cost of health care, and if so, what is the cost effectiveness? This study provides an overview, synthesis, and analysis of the medical offset effect. It demonstrates that a medical offset effect does exist and the size of the effect is significant. A behavioral model provides a precise method for ascertaining the dimensions of medical offset and an explanation of the underlying causal relationships. The offset effect for an important population group is analyzed through the use of Medicaid patient data from Georgia and Michigan. This clear, concise book will provide students, researchers, mental health professionals, insurance companies, and government agencies with an understanding of the current and potential future relationships between general medical care and mental health care services.The Medical Offset Effect begins with the historical and structural evolution of the mental health industry since World War II. The book then reviews medical offset literature. The behavioral model is followed by an empirical analysis and the book concludes with a general analytical framework for the development of a national mental health policy in light off the medical offset effect.https://scholarship.richmond.edu/bookshelf/1067/thumbnail.jp

A Behavioral Model of the Medical Offset Effect

Persons who suffer from mental illness consume a disproportionate—and some maintain an inappropriate—amount of general (somatic) health services. Many mental health care providers assert that the timely treatment of mental illness will generate a subsequent reduction in the use of non-mental health care. Although this alleged phenomenon—termed the medical offset effect—has been intensively studied for two decades, these efforts have not produced anything approaching a consensus concerning the very existence of the effect. Different definitions and measures of the concept, different experimental designs, different research agendas, methodologies, and statistical techniques have contributed to researchers more often than not talking past one another. Furthermore, the findings of the overwhelming majority of offset studies have been vitiated by a variety of methodological shortcomings. Most of these shortcomings share a common etiology: the failure of researchers to explicitly either describe or analyze the behavioral foundations of the relationships they are trying to observe and measure. Research efforts have been largely devoted to identifying factors associated with the offset, rather than explaining the offset. In this article we develop a behavioral model for explaining the medical offset and providing (a priori) justification for positing particular relationships and, concomitantly, selecting and analyzing particular variables for study. This approach holds greater promise for enabling future research to incrementally advance our knowledge and understanding of the complex behavioral processes involved in the medical offset effect

Simulating Radiating and Magnetized Flows in Multi-Dimensions with ZEUS-MP

This paper describes ZEUS-MP, a multi-physics, massively parallel, message- passing implementation of the ZEUS code. ZEUS-MP differs significantly from the ZEUS-2D code, the ZEUS-3D code, and an early "version 1" of ZEUS-MP distributed publicly in 1999. ZEUS-MP offers an MHD algorithm better suited for multidimensional flows than the ZEUS-2D module by virtue of modifications to the Method of Characteristics scheme first suggested by Hawley and Stone (1995), and is shown to compare quite favorably to the TVD scheme described by Ryu et. al (1998). ZEUS-MP is the first publicly-available ZEUS code to allow the advection of multiple chemical (or nuclear) species. Radiation hydrodynamic simulations are enabled via an implicit flux-limited radiation diffusion (FLD) module. The hydrodynamic, MHD, and FLD modules may be used in one, two, or three space dimensions. Self gravity may be included either through the assumption of a GM/r potential or a solution of Poisson's equation using one of three linear solver packages (conjugate-gradient, multigrid, and FFT) provided for that purpose. Point-mass potentials are also supported. Because ZEUS-MP is designed for simulations on parallel computing platforms, considerable attention is paid to the parallel performance characteristics of each module. Strong-scaling tests involving pure hydrodynamics (with and without self-gravity), MHD, and RHD are performed in which large problems (256^3 zones) are distributed among as many as 1024 processors of an IBM SP3. Parallel efficiency is a strong function of the amount of communication required between processors in a given algorithm, but all modules are shown to scale well on up to 1024 processors for the chosen fixed problem size.Comment: Accepted for publication in the ApJ Supplement. 42 pages with 29 inlined figures; uses emulateapj.sty. Discussions in sections 2 - 4 improved per referee comments; several figures modified to illustrate grid resolution. ZEUS-MP source code and documentation available from the Laboratory for Computational Astrophysics at http://lca.ucsd.edu/codes/currentcodes/zeusmp2

The National Fire and Fire Surrogate Study: Effects of Fuel Reduction Methods on Forest Vegetation Structure and Fuels

Changes in vegetation and fuels were evaluated from measurements taken before and after fuel reduction treatments (prescribed. re, mechanical treatments, and the combination of the two) at 12 Fire and Fire Surrogate (FFS) sites located in forests with a surface. re regime across the conterminous United States. To test the relative effectiveness of fuel reduction treatments and their effect on ecological parameters we used an information-theoretic approach on a suite of 12 variables representing the overstory (basal area and live tree, sapling, and snag density), the understory (seedling density, shrub cover, and native and alien herbaceous species richness), and the most relevant fuel parameters for wild. re damage (height to live crown, total fuel bed mass, forest floor mass, and woody fuel mass). In the short term (one year after treatment), mechanical treatments were more effective at reducing overstory tree density and basal area and at increasing quadratic mean tree diameter. Prescribed. re treatments were more effective at creating snags, killing seedlings, elevating height to live crown, and reducing surface woody fuels. Overall, the response to fuel reduction treatments of the ecological variables presented in this paper was generally maximized by the combined mechanical plus burning treatment. If the management goal is to quickly produce stands with fewer and larger diameter trees, less surface fuel mass, and greater herbaceous species richness, the combined treatment gave the most desirable results. However, because mechanical plus burning treatments also favored alien species invasion at some sites, monitoring and control need to be part of the prescription when using this treatment