Henk Hilderink

Comparative impact assessment of child pneumonia interventions

OBJECTIVE To compare the cost-effectiveness of interventions to reduce pneumonia mortality through risk reduction, immunization and case management. METHODS Country-specific pneumonia burden estimates and intervention costs from WHO were used to review estimates of pneumonia risk in children under 5 years of age and the efficacy of interventions (case management, pneumonia-related vaccines, improved nutrition and reduced indoor air pollution from household solid fuels). We calculated health benefits (disability-adjusted life years, DALYs, averted) and intervention costs over a period of 10 years for 40 countries, accounting for 90% of pneumonia child deaths. FINDINGS Solid fuel use contributes 30% (90% confidence interval: 18-44) to the burden of childhood pneumonia. Efficacious community-based treatment, promotion of exclusive breastfeeding, zinc supplementation and Haemophilus influenzae type b (Hib) and Streptococcus pneumoniae immunization through existing programmes showed cost-effectiveness ratios of 10-60 International dollars (I

Opportunities and Challenges for Investigating the Environment-Migration Nexus

) per DALY in low-income countries and less than I

Perspectives on Global Change: Uncertainty and risk: dystopian futures

120 per DALY in middle-income countries. Low-emission biomass stoves and cleaner fuels may be cost-effective in low-income regions. Facility-based treatment is potentially cost-effective, with ratios of I

Evaluación comparativa del impacto de las intervenciones contra la neumonía en la niñez

60-120 per DALY. The cost-effectiveness of community case management depends on home visit cost. CONCLUSION Vaccines against Hib and S. pneumoniae, efficacious case management, breastfeeding promotion and zinc supplementation are cost-effective in reducing pneumonia mortality. Environmental and nutritional interventions reduce pneumonia and provide other benefits. These strategies combined may reduce total child mortality by 17%.

Downscaling drivers of global environmental change Enabling use of global SRES scenarios at the national and grid levels

Environmental change is an acknowledged factor influencing human migration. Analytical research regarding the relationship between the environment and human migration has increased in recent years yet still faces numerous hurdles, partly due to limited availability of suitable data. We review available data and methodologies for investigating the environment-migration nexus, identifying data inconsistencies resulting from the combination of different sources and illustrating the underlying reasons for them. We discuss a number of methods for investigating the environment-migration relationship, including frameworks and concepts; surveys; empirical, quantitative methods; and simulation approaches. Based on this overview, we offer recommendations for improved analyses of the environment-migration nexus including reporting data inconsistencies and uncertainties, combining approaches and data sources, and developing multiple-study approaches.

The health impacts of globalisation: a conceptual framework

This chapter explores dystopian futures. After a summary of the uncertainties and risks discussed for each of the subsystems, integrated experiments are presented in which world view and management style throughout the world system are at odds. We also investigate the effectiveness of various response options and of the timing of certain policy measures . Introduction In the previous chapter we outlined possible futures which are based on coherent sets of assumptions about how the world system functions and how it is managed. These are called utopias and constitute the diagonal elements in the matrix presented in Figure 10.7. In a way, they are idealised and therefore implausible images of the future. In this chapter we first present some simulation experiments in which dystopian trends are explored with the integrated TARGETS 1.0 model. This is a prelude to the next section in which we analyse in more detail images of the future where world view and management style are at odds. These are referred to as integrated dystopias (see Chapter 11) and they are actually more plausible because they contain real-world tensions between diverging world views and management styles. Two major chains which cause feedback loops are presented as a framework discussing some interesting dystopian futures and to give an assessment of associated risks. Finally, we explore the adequacy of response actions in terms of intensity and timing, and the consequences of allocating insufficient investments to the food, water and energy sectors.

The use of scenarios as the basis for combined assessment of climate change mitigation and adaptation

Introduction Progress in reducing mortality from pneumonia in children under 5 years of age has been relatively slow in many parts of the developing world, where about 155 million clinical pneumonia episodes and 2 million deaths occur annually. (1,2) Risk factors for pneumonia include stunting and underweight) (1,3,4) suboptimal breastfeeding, (5,6) lack of immunization (7,8) and indoor air pollution from household use of solid fuels. (9-12) There is evidence that effective and appropriate management of clinical cases is possible (13,14) at health-care facilities (15) and in the community, (16) but this level of management is often lacking. Efforts to control pneumonia are needed to meet Millennium Development Goal 4 (MDG 4), to reduce child mortality in the world by two-thirds by 2015. (17) Often, a package of priority interventions is developed to address MDG targets and reduce child mortality. (4,6,18-20) Cost-effectiveness analysis has become vital in deciding what interventions to implement and scale up. (21) Single-candidate interventions to reduce pneumonia have been evaluated in general economic terms, (6,11,18,22-24) but no comprehensive analysis has focused on pneumonia control. Different interventions can affect incidence of case fatality, with differences noted across age groups. Population risk interventions can target specific subpopulations, while immunization is intended for all infants. Preventive interventions of this kind may reduce the incidence of pneumonia, whereas case management influences case fatality after falling ill. Both types of interventions can reduce pneumonia mortality. The aim of this study was to compare the impact of eight preventive and curative interventions at the population level (6,25-27) and to identify the intervention mixes that generate the highest possible level of child health at the lowest cost. Methods To estimate the population health effects and total costs of pneumonia interventions from a health-care perspective, we applied demographic life tables for the 40 countries with the highest mortality (list available at: http://oldwww.bmg.eur.nl/ personal/niessen/Webtable%20Countries%20by%20Region. doc The tables were used to estimate the health effect of risk factors, as well as the reductions in incidence and case fatality in population cohorts, simultaneously and consistently. (6,25-27) Detailed descriptions of concepts, methods, background papers, regional studies and data are available at: WHO-CHOICE (CHOosing Interventions that are Cost Effective) at: www.who.int/choice/en. Box 1 provides an overview of the approach. We considered the epidemiological characteristics and level of health care of each of the 40 countries, as well as the coverage levels of the expanded programme on immunization (EPI) and of facility-based case management. Due to the large uncertainties involved in the epidemiologic, effectiveness and cost estimates, we included a high and a low cost-effectiveness scenario for each mix of interventions. Each countrys life table provides summary estimates of how pneumonia affects mortality and morbidity, expressed in terms of disability-adjusted life years (DALYs) lost. The tables also provide estimates of the effect and cost of mixed health interventions, in United States dollars (US

Vulnerability of humans and the environment: challenges and opportunities

) for the year 2000, with a 3% discount rate according to health economics guidelines. We combined estimated health gains and costs per intervention to identify the sets of health interventions that maximized child health at different budget levels by providing the greatest health yield per dollar spent. The life tables were implemented in C++ (a general programming language) using M language (a language for working with data and building domain models). The script with M-equations is available at: http:// old www.bmg.eur.nl/persona/niessenl GAPP_LOW.MPdf.pdf Epidemiologic and demographic data The life tables used in the model were based on the recently published WHO country data, which draw on reviews of incidence and mortality for childhood and neonatal pneumonia. …