Cost effectiveness of a community based prevention and treatment of acute malnutrition programme in Mumbai slums, India

Children in slums are at high risk of acute malnutrition and death. Cost-effectiveness of community-based management of severe acute malnutrition programmes has been demonstrated previously, but there is limited evidence in the context of urban slums where programme cost structure is likely to vary tremendously. This study assessed the cost-utility of adding a community based prevention and treatment for acute malnutrition intervention to Government of India Integrated Child Development Services (ICDS) standard care for children in Mumbai slums. The intervention is delivered by community health workers in collaboration with ICDS Anganwadi community health workers. The analysis used a decision tree model to compare the costs and effects of the two options: standard ICDS services with the intervention and prevention versus standard ICDS services alone. The model used outcome and cost data from the Society for Nutrition, Education & Health Action's Child Health and Nutrition programme in Mumbai slums, which delivered services to 12,362 children over one year from 2013 to 2014. An activity-based cost model was used, with calculated costs based on programme financial records and key informant interviews. Cost data were coupled with programme effectiveness data to estimate disability adjusted life years (DALYs) averted. The community based prevention and treatment programme averted 15,016 DALYs (95% Uncertainty Interval [UI]: 12,246-17,843) at an estimated cost of $23 per DALY averted (95%UI:19-28) and was thus highly cost-effective. This study shows that ICDS Anganwadi community health workers can work efficiently with community health workers to increase the prevention and treatment coverage in slums in India and can lead to policy recommendations at the state, and potentially the national level, to promote such programmes in Indian slums as a cost-effective approach to tackling moderate and severe acute malnutrition

Kritik an Population Attributable Fraction bei genauerem Hinsehen nicht gerechtfertigt

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Potential impact of reduced tobacco use on life and health expectancies in Belgium

Objectives: We investigated the potential impact of reduced tobacco use scenarios on total life expectancy and health expectancies, i.e., healthy life years and unhealthy life years. Methods: Data from the Belgian Health Interview Survey 2013 were used to estimate smoking and disability prevalence. Disability was based on the Global Activity Limitation Indicator. We used DYNAMO-HIA to quantify the impacts of risk factor changes and to compare the “business-as-usual” with alternative scenarios. Results: The “business-as-usual” scenario estimated that in 2028 the 15-year-old men/women would live additional 50/52 years without disability and 14/17 years with disability. The “smoking-free population” scenario added 3.4/2.8 healthy life years and reduced unhealthy life years by 0.79/1.9. Scenarios combining the prevention of smoking initiation with smoking cessation programs are the most effective, yielding the largest increase in healthy life years (1.9/1.7) and the largest decrease in unhealthy life years (− 0.80/− 1.47). Conclusions: Health impact assessment tools provide different scenarios for

Methodological framework for World Health Organization estimates of the global burden of foodborne disease

Background: The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings: The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions: We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level

Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis

Background: Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs). Methods: We estimated the incidence of infections with 16 antibiotic resistance–bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011–12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature. Findings: From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148–763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480–38 430) attributable deaths and 874 541 (768 837–989 068) DALYs. The burden for the EU and EEA was highest in infants (aged <1 year) and people aged 65 years or older, had increased since 2007, and was highest in Italy and Greece. Interpretation: Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases

Unravelling data for rapid evidence-based response to COVID-19: a summary of the unCoVer protocol

Introduction unCoVer - Unravelling data for rapid evidence-based response to COVID-19 - is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic. Methods and analysis From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients' baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded. Ethics and dissemination After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer's activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.info:eu-repo/semantics/publishedVersio

Research Synthesis Methods in an Age of Globalized Risks: Lessons from the Global Burden of Foodborne Disease Expert Elicitation

We live in an age that increasingly calls for national or regional management of global risks. This article discusses the contributions that expert elicitation can bring to efforts to manage global risks and identifies challenges faced in conducting expert elicitation at this scale. In doing so it draws on lessons learned from conducting an expert elicitation as part of the World Health Organizations (WHO) initiative to estimate the global burden of foodborne disease; a study commissioned by the Foodborne Disease Epidemiology Reference Group (FERG). Expert elicitation is designed to fill gaps in data and research using structured, transparent methods. Such gaps are a significant challenge for global risk modeling. Experience with the WHO FERG expert elicitation shows that it is feasible to conduct an expert elicitation at a global scale, but that challenges do arise, including: defining an informative, yet feasible geographical structure for the elicitation; defining what constitutes expertise in a global setting; structuring international, multidisciplinary expert panels; and managing demands on experts' time in the elicitation. This article was written as part of a workshop, Methods for Research Synthesis: A Cross-Disciplinary Approach held at the Harvard Center for Risk Analysis on October 13, 2013

World Health Organization Estimates of the Global and Regional Disease Burden of 11 Foodborne Parasitic Diseases, 2010: A Data Synthesis

We would like to acknowledge the assistance of the WHO Secretariat over the life of the FERG initiative, particularly Amy Cawthorne, Tim Corrigan, Tanja Kuchenmüller, Yuki Minato, Kurt Straif and Claudia Stein. We acknowledge the Institute for Health Metrics and Evaluation (Seattle, WA, USA) for providing data on the global burden of selected diseases.In this data synthesis, Paul Robert Torgerson and colleagues estimate the global and regional disease burden of 11 foodborne parasitic diseases.Yeshttp://www.plosmedicine.org/static/editorial#pee