The population cost-effectiveness of interventions designed to prevent childhood depression

BACKGROUND AND OBJECTIVES: Depression in childhood and adolescence is common and often persists into adulthood. This study assessed the population-level cost-effectiveness of a preventive intervention that screens children and adolescents for symptoms of depression in schools and the subsequent provision of a psychological intervention to those showing elevated signs of depression. The target population for screening comprised 11- to 17-year-old children and adolescents in the 2003 Australian population.

METHODS: Economic modeling techniques were used to assess the incremental cost-effectiveness of the intervention compared with no intervention. The perspective was that of the health sector, and outcomes were measured by using disability-adjusted life-years (DALYs). Multivariate probabilistic and univariate sensitivity testing was applied to quantify variations in the model parameters.

RESULTS: The modeled psychological intervention had an incremental cost-effectiveness ratio of $5400 per DALY averted, with just 2% of iterations falling above a $50 000 per DALY value-for-money threshold. Results were robust to model assumptions.

CONCLUSIONS: After school screening, screening and the psychological intervention represent good value-for-money. Such an intervention needs to be seriously considered in any national package of preventive health services. Acceptability issues, particularly to intervention providers, including schools and mental health professionals, need to be considered before wide-scale adoption.

Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist

The successful use of a targeted therapy is intrinsically linked to the ability of a companion diagnostic to correctly identify patients most likely to benefit from treatment. The aim of this study was to review the characteristics of companion diagnostics that are of importance for inclusion in an economic evaluation. Approaches for including these characteristics in model-based economic evaluations are compared with the intent to describe best practice methods. Five databases and government agency websites were searched to identify model-based economic evaluations comparing a companion diagnostic and subsequent treatment strategy to another alternative treatment strategy with model parameters for the sensitivity and specificity of the companion diagnostic (primary synthesis). Economic evaluations that limited model parameters for the companion diagnostic to only its cost were also identified (secondary synthesis). Quality was assessed using the Quality of Health Economic Studies instrument. 30 studies were included in the review (primary synthesis n = 12; secondary synthesis n = 18). Incremental cost-effectiveness ratios may be lower when the only parameter for the companion diagnostic included in a model is the cost of testing. Incorporating the test's accuracy in addition to its cost may be a more appropriate methodological approach. Altering the prevalence of the genetic biomarker, specific population tested, type of test, test accuracy and timing/sequence of multiple tests can all impact overall model results. The impact of altering a test's threshold for positivity is unknown as it was not addressed in any of the included studies. Additional quality criteria as outlined in our methodological checklist should be considered due to the shortcomings of standard quality assessment tools in differentiating studies that incorporate important test-related characteristics and those that do not. There is a need to refine methods for incorporating the characteristics of companion diagnostics into model-based economic evaluations to ensure consistent and transparent reimbursement decisions are made.

Modeling the cost effectiveness of child care policy changes in the U.S.

INTRODUCTION: Child care facilities influence diet and physical activity, making them ideal obesity prevention settings. The purpose of this study is to quantify the health and economic impacts of a multi-component regulatory obesity policy intervention in licensed U.S. child care facilities. METHODS: Two-year costs and BMI changes resulting from changes in beverage, physical activity, and screen time regulations affecting a cohort of up to 6.5 million preschool-aged children attending child care facilities were estimated in 2014 using published data. A Markov cohort model simulated the intervention's impact on changes in the U.S. population from 2015 to 2025, including short-term BMI effects and 10-year healthcare expenditures. Future outcomes were discounted at 3% annually. Probabilistic sensitivity analyses simulated 95% uncertainty intervals (UIs) around outcomes. RESULTS: Regulatory changes would lead children to watch less TV, get more minutes of moderate and vigorous physical activity, and consume fewer sugar-sweetened beverages. Within the 6.5 million eligible population, national implementation could reach 3.69 million children, cost $4.82 million in the first year, and result in 0.0186 fewer BMI units (95% UI=0.00592 kg/m(2), 0.0434 kg/m(2)) per eligible child at a cost of $57.80 per BMI unit avoided. Over 10 years, these effects would result in net healthcare cost savings of $51.6 (95% UI=$14.2, $134) million. The intervention is 94.7% likely to be cost saving by 2025. CONCLUSIONS: Changing child care regulations could have a small but meaningful impact on short-term BMI at low cost. If effects are maintained for 10 years, obesity-related healthcare cost savings are likely.

Economic Bias of Weather Forecasting: A Spatial Modeling Approach

The value of accurate weather forecast information is substantial. In this paper we examine competition among forecast providers and its implications for the quality of forecasts. A simple economic model shows that an economic bias geographical inequality in forecast accuracy arises due to the extent of the market. Using the unique data on daily high temperature forecasts for 704 U.S. cities, we find that forecast accuracy increases with population and income. Furthermore, the economic bias gets larger when the day of forecasting is closer to the target day; i.e. when people are more concerned about the quality of forecasts. The results hold even after we control for location-specific heterogeneity and difficulty of forecasting.

Modeling Potential Tiger Habitat in Hupingshan-Houhe and Mangshan-Nanling National Nature Reserves, China

After declining steadily for several decades, the South China tiger (Panthera tigris amoyensis) is now thought to be extinct in the wild. However, there is some hope of reintroduction, with Hupingshan-Houhe and Mangshan-Nanling National Nature Reserves in southern China seeming to hold the most promise. Our study used slope, elevation, vegetation, and landcover variables to construct a rough habitat suitability index for tigers in these two parks. According to our model, there are areas of suitable habitat within both parks. However, there are some important variables that we were unable to include in our model, such as human population density and prey availability. Considerable in-depth research will be necessary to evaluate the suitability of these locations before reintroduction is considered.

Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Prevalence of Refractive Errors in a Brazilian Population: The Botucatu Eye Study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Polymorphisms and Haplotypes in the Interleukin-4 Gene are Associated With Chronic Periodontitis in a Brazilian Population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Association of Haplotypes in the CXCR2 Gene with Periodontitis in a Brazilian Population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Management of vomplex systems: Modeling the biological pest control

The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction. © 2008 World Scientific Publishing Company.

Modeling Habitat Split: Landscape and Life History Traits Determine Amphibian Extinction Thresholds

Habitat split is a major force behind the worldwide decline of amphibian populations, causing community change in richness and species composition. In fragmented landscapes, natural remnants, the terrestrial habitat of the adults, are frequently separated from streams, the aquatic habitat of the larvae. An important question is how this landscape configuration affects population levels and if it can drive species to extinction locally. Here, we put forward the first theoretical model on habitat split which is particularly concerned on how split distance - the distance between the two required habitats - affects population size and persistence in isolated fragments. Our diffusive model shows that habitat split alone is able to generate extinction thresholds. Fragments occurring between the aquatic habitat and a given critical split distance are expected to hold viable populations, while fragments located farther away are expected to be unoccupied. Species with higher reproductive success and higher diffusion rate of post-metamorphic youngs are expected to have farther critical split distances. Furthermore, the model indicates that negative effects of habitat split are poorly compensated by positive effects of fragment size. The habitat split model improves our understanding about spatially structured populations and has relevant implications for landscape design for conservation. It puts on a firm theoretical basis the relation between habitat split and the decline of amphibian populations. © 2013 Fonseca et al.

ECOLOGICAL MODELING OF TALITROIDES TOPITOTUM (CRUSTACEA: AMPHIPODA)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Simulating Population Genetics of Pathogen Vectors in Changing Landscapes: Guidelines and Application with Triatoma brasiliensis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Reintroducing the red-billed curassow in Brazil: Population viability analysis points to potential success

Reintroduction can be enhanced by data from long-term post-release monitoring, which allows for modeling opportunities such as population viability analysis (PVA). PVA-relevant data were gathered via long-term monitoring of reintroduced red-billed curassows at the Guapiacu Ecological Reserve (REGUA), located in Rio de Janeiro, Brazil, over 25 months. In the present article, we (1) assess the robustness of the reintroduction plan, (2) evaluate the viability of the current reintroduced population, and (3) examine mitigation options to increase the viability of this population. VORTEX indicates that the initial plan, fully implemented, was likely to establish a viable population at REGUA. The current population is unviable; the best mitigation strategies are to eliminate hunting altogether, or at least reduce it by half, and to supplement ten immature pairs in 2015. A positive long-term outcome at REGUA is still possible; we encourage the Brazilian government and private stakeholders to consider population supplementation, both to achieve success at REGUA and to improve the evidence base for future reintroductions. (C) 2014 Associacao Brasileira de Ciencia Ecologica e Conservacao. Published by Elsevier Editora Ltda.

Modeling amino acid requirements of poultry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)