1. An overview of burden of disease studies in Europe.
- Author
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Charalampous, P., Gorasso, V., Plass, D., Pires, S. Monteiro, Von der Lippe, E., Pallari, E., Mereke, A., Devleesschauwer, B., and Haagsma, J.
- Subjects
COMMUNICABLE disease epidemiology ,NON-communicable diseases ,LIFE expectancy ,CONFERENCES & conventions ,RISK assessment ,WOUNDS & injuries ,PEOPLE with disabilities ,EPIDEMIOLOGICAL research - Abstract
Facing the considerable variation in the computation of disability-adjusted life years (DALY) in the numerous updates of the Global Burden of Disease (GBD) study and many independent studies, the European burden of disease network (burden-eu) launched a series of systematic literature reviews (SLR) to explore the key assumptions used in the European burden of disease (BoD) studies. The SLR will provide an overview of the existing BoD studies and the computational variations used and will also help identifying ways to harmonize the approaches enhancing the comparability of BoD estimates. The SLR was split in four parallel reviews: noncommunicable diseases (NCDs), communicable diseases (CDs), injuries and risk factors. For the first three, the search strategy included terms describing the population (GBD area ‘‘European region’’) and the BoD measures (years lived with disability, years of life lost, and DALYs). We included studies published between January 1990 and April 2020, without language restrictions. The search strategy was run in PubMed, Web of Science, Cochrane, and Embase. OpenGrey, OAIster, CABDirect, WHO and targeted public health agency websites were screened for grey literature. In addition, burden-eu members were asked to supplement the list of publications with any material available within their national public health institutes. Data extraction focused on methodological information. The title, abstract and full-text screening resulted in the final inclusion of 165 papers regarding NCDs, 189 with CDs, and 124 papers regarding injuries. The final list includes peer-reviewed articles and reports showing a variability in data sources used (e.g. patient medical records, disease registries, insurance claims sources) and model assumptions (e.g. use of multi-morbidity adjustments, use of disability weights). Further data extraction and analysis is in process, and will be presented during the workshop. [ABSTRACT FROM AUTHOR]
- Published
- 2021